This article explains why an AI business strategy is essential, what pitfalls organizations face, and how to design an approach that drives growth, trust, and innovation. Drawing on insights from our Prompt & Response webcast, you will find practical steps, real-world analogies, and lessons that turn hype into impact.

Why AI strategies fail without a clear vision

Most organizations start with enthusiasm. They launch AI projects to explore chatbots, analytics, or generative AI pilots. But enthusiasm alone does not guarantee success. Multiple studies report that roughly eight to nine out of ten pilots never reach production. IDC (with Lenovo) found 88% of AI POCs fail to scale, RAND estimates more than 80% fail overall, and Capgemini reports similar numbers.

The issue is often a missing AI vision. Leaders may explore AI because “others are doing it,” not because they’ve defined what AI can address in their own business process. A well-crafted AI strategy requires more than experiments. It must align with business priorities, resources, and customer expectations so that AI initiatives are aligned with overall business objectives.

Imagine hiring a team of brilliant architects without telling them what kind of house you need. You’ll get beautiful sketches, but no home you can live in. That’s what happens when companies adopt AI without defining overall business outcomes.

What makes a successful AI strategy in 2025?

A successful AI strategy connects four dimensions:

• Business value: AI must deliver measurable business value, such as efficiency gains or revenue uplift.
• Data strategy: Without quality data for AI initiatives, the best ai model will fail.
• Culture: AI adoption depends on people trusting AI and seeing it as support, not a threat.
• Technology and governance: The right AI platforms, combined with AI governance, ensure reliable responsible AI principles and readiness for ai regulations.

Companies that master these elements unlock value from AI. They move beyond demos and into production AI that generates sustainable business outcomes.

How to develop AI business strategy that works

To develop an AI strategy, start with the same discipline you apply to other business strategies. Define your AI vision, objectives, and guardrails. Then ask: what business problems AI could solve better than humans alone?

An effective AI strategy does not chase shiny tools. It asks where AI will create impact. For instance:

• In customer service, AI assistants can handle repetitive queries, freeing humans for empathy-driven tasks.
• In finance, AI systems can flag fraud faster than traditional monitoring.
• In HR, AI tools can recommend training paths based on skills and career goals.

The lesson is simple. A robust AI strategy begins by mapping opportunities to business objectives and designing an effective AI strategy that can scale across the overall business strategy.

Common challenges in AI adoption

AI adoption is rarely only a technical issue. Employees often resist, worried about job loss. Leaders fear compliance risks. Data teams struggle with inconsistent systems. IDC highlights unclear ROI, lack of AI talent, and data quality gaps as top blockers.

Consider a retail bank testing AI applications for churn reduction. Technically, the AI solution works. But adoption fails because staff do not trust the predictions. Without training and cultural support, the AI initiative remains unused.

This is why responsible use of AI matters. Communicate openly, involve employees, and show how AI supports rather than replaces them. AI adoption succeeds when people feel empowered, not threatened. 

The role of governance and responsible AI

No comprehensive AI strategy works without AI governance. Rules on privacy, fairness, and explainability are not optional. With evolving AI regulations such as the EU AI Act, companies must ensure transparency and monitor AI in production. Deloitte’s 2024 research confirms governance and compliance are now the main barriers to scaling AI.

“New regulations, such as the EU AI Act, clearly state that user protection, algorithm transparency, and the ability to demonstrate compliance with ethical principles are no longer just good practice — they are mandatory. AI Governance will therefore become not an option, but a necessary standard for any organization that wants to use AI in a scalable and trusted way. And that’s a good thing – because it means that Artificial Intelligence is truly maturing as a business tool” – summarized Marek Czachorowski, Head of Modern Data Practice at Inetum, in a recent “Business Insider” interview.

A responsible AI framework protects both brand trust and customers. This includes systems to ensure your AI systems remain compliant, auditable, and aligned with responsible AI principles.

Think of governance as the traffic lights of AI. Without them, everyone drives fast, but accidents are inevitable. With them, AI flows smoothly and safely, and it integrates into the overall business strategy.

Choosing the right AI use cases

Organizations often ask: Where should we start? The answer lies in selecting AI use cases that balance feasibility with impact. Leaders succeed when they concentrate on fewer, high-value areas instead of scattering resources across dozens of AI projects.

Examples:

• Automating compliance checks for marketing campaigns with AI marketing agents.
• Using AI agents to classify support tickets in real time.
• Letting AI services suggest optimal inventory levels.

These are specific AI applications that can be piloted quickly, scaled easily, and deliver early business value. Remember: AI initiatives shouldn’t just be experiments. They must connect to business models and KPIs.

“The era of experimentation is coming to an end – the era of responsibility is starting. Over the past few years, many companies have been testing the capabilities of AI in smaller, controlled projects. Today, we are seeing a clear shift: security, regulatory compliance, and full transparency of operations are becoming priorities”. – Marek Czachorowski, Head of Modern Data Practice.

Steps to building an AI roadmap

A practical AI roadmap can be built in five steps:

1. Explore AI opportunities: brainstorm cases for AI with business stakeholders.
2. Prioritize: score use cases by impact and feasibility.
3. Pilot and learn: implementing an AI project on a small scale to test assumptions.
4. Scale and integrate AI: move from prototype to AI deployment and integration of AI into workflows.
5. Monitor AI: continuously check outcomes, compliance, and adoption.

These steps to building an AI roadmap ensure that AI initiatives are aligned with overall business priorities. Accenture reports that scaling even one strategic AI innovation makes companies nearly 3 × more likely to exceed ROI.

The importance of data in AI development

Every AI initiative lives or dies by data. Poor data means poor outcomes. A data strategy is the backbone of developing an AI strategy.

To succeed, organizations must:

• Integrate siloed sources for a single view of the customer.
• Improve data quality to ensure that AI learns from accurate inputs.
• Build governance to track data for AI initiatives responsibly.

Imagine training a chef with spoiled ingredients. The result will not impress anyone. The same is true for AI: investing in AI without clean data wastes resources.

Enabling business outcomes through AI implementation

AI implementation is not about deploying AI tools for their own sake. It is about leveraging AI to reach business outcomes.

When companies implement AI initiatives, they should track both technical and financial impact. Does predictive maintenance cut downtime? Do customers feel more trust?

This is where AI strategy implementation must include KPIs that deliver measurable business value. Otherwise, AI remains a cost, not a growth driver.

Building trust with responsible AI principles

Trust is the foundation of AI adoption. Customers will not accept “black box” AI systems. Leaders will not risk AI investments if AI outcomes are unpredictable.

Embedding ethical AI, fairness, and responsible AI principles reassures stakeholders. Think of it as a contract: AI delivers results within agreed limits. This creates winning AI approaches that scale sustainably and enable AI as part of normal operations.

Practical accelerators from the Prompt & Response webcast

In Prompt & Response #2, we presented a five-hour AI discovery workshop to accelerate building an AI strategy. The format includes four stages:

• Inspiration,
• Demystification,
• Ideation,
• Strategizing.

It is a lightweight way to support AI initiatives, explore AI capabilities, and align AI thinking within the organization.

An AI strategy is a comprehensive blueprint for people, process, and technology. Strategy is a comprehensive plan that leaders must own. AI strategy requires courage and foresight.

Why AI strategy is vital for future business

A strategy is a comprehensive plan for success. In 2025, an AI strategy is vital. Organizations that hesitate risk being left behind as competitors use AI to personalize services, cut costs, and innovate faster. Accenture notes that leaders expect major gains, including 11% cost reduction and 13% productivity improvement, within 18 months.

The impact of AI is comparable to the internet revolution. Just as firms that ignored the web lost relevance, those without an AI plan will fall behind. AI is essential to modernize traditional business models and unlock growth.

Summary: what to remember when developing AI strategy

• Above all, AI strategy requires courage, imagination, and leadership to rethink business models.
• AI strategies fail when they lack vision or connection to business objectives.
• A comprehensive AI strategy balances business value, data strategy, culture, technology, and AI governance.
• Successful AI adoption requires trust, training, and communication.
• Governance and compliance are non-negotiable, design for responsible AI and evolving AI regulations early.
• Focus on AI use cases that are feasible, scalable, and impactful.
• Build an AI roadmap step by step: explore AI, prioritize, pilot, scale, monitor AI.
• Data quality is the foundation of every AI model and AI development process.
• AI initiatives are aligned when they create measurable business outcomes.

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Frequently asked questions about AI business strategy

What is an AI agent in marketing, and why does it matter in 2025?

An AI agent is more than a chatbot. It’s an intelligent system designed to act, decide, and iterate autonomously – not just used for content creation. In Prompt & Response, we explored how an AI marketing agent can:

• select the right audience,
• draft personalized notes,
• check every line against compliance rules before sending anything out.

Why does this matter in 2025? Because customers expect precision. Spray-and-pray outreach no longer works. Every marketer knows the frustration of sending broad messages that erode trust. AI agents in marketing address this head-on: they enable “segment of one” campaigns, tailoring offers based on real-time data and keeping every message safe from compliance mistakes.

How AI marketing tools change the way campaigns are built

Think of your last email campaign. You probably spent weeks preparing content, segmenting audiences, and waiting for compliance approval. Now imagine the same campaign being drafted, vetted, and approved in minutes with help of AI marketing agents.

The workflow looks like this:

• A targeting agent selects customers based on data-driven signals.
• A marketing agent tailors the copy, using natural language that reflects your brand’s voice.
• A compliance agent reviews tone, claims, and legal constraints, automating 80% of manual checks.
• A human reviews the messages and gives a final “go”.

The result? Faster campaign execution, higher personalization, and reduced risk. For marketing teams, this feels like getting an extra colleague — an AI assistant who never gets tired of reviewing copy.

From traditional marketing to AI marketing automation

Traditional marketing relied on intuition, manual data pulls, and creative brainstorming. AI marketing automation introduces precision: instead of blasting generic newsletters, AI tools tailor each outreach based on customer activity.

Marketers can now:

• Automate repetitive marketing tasks without losing control.
• Integrate AI features directly into their existing marketing stack.
• Optimize campaign timing, wording, and targeting using signals based on real-time data.

Just as spreadsheets once transformed finance, AI-powered agents are now reshaping marketing operations.

What are the benefits of AI agents for marketing teams?

Let’s break it down:

1. Time savings – campaign assets in minutes, not days.
2. Hyper-personalization – offers tailored to individual behaviors, not just segments.
3. Compliance by design – every campaign includes an audit trail, reducing sleepless nights for legal teams.
4. Scalable creativity – generative AI combined with marketer insights to tailor messages across multiple channels.

According to McKinsey, personalized campaigns can drive 10–15% revenue uplift. The benefits extend beyond marketing teams. Customers receive fewer irrelevant offers and gain more trust in the brand.

How does AI outreach work in practice (and why does it feel human)

One highlight from our webcast demo was seeing AI outreach in action. Imagine entering a simple product brief and letting an AI agent tailor hundreds of one-to-one messages, each checked for compliance before being released.

It’s like hiring a team of AI-powered agents who perform sales and marketing activities tirelessly. They:

• Follow the rules.
• Integrate with your data.
• Optimize the message structure instantly. 

Still, agents cannot fully replace human oversight. Marketers remain the editors who ensure authenticity.

Common frustrations: why marketing AI agents don’t replace human creativity

As Beata, our head of marketing, put it: “Sometimes AI-generated content feels generic. I can spot it instantly.” 

AI systems generate at scale, but agents don’t always capture brand nuance. That is why human input remains vital. Marketers fine-tune tone, context, and cultural references. The lesson is simple: marketing AI agents are intelligent, but they’re not artists.

How do AI agents handle data, compliance, and trust?

Every marketer dreams of full automation, but compliance is the non-negotiable backbone. GDPR fines, the EU AI Act uncertainties, and ethical risks make caution essential.

As Wiktor Zdzienicki, Inetum’s AI & Data Practice Leader, reminded us: “Garbage in, garbage out.” Poor data quality means poor results. AI systems must work with clean, unified customer data to succeed.

That is why AI agents integrate compliance at every step. They timestamp each decision, route sensitive cases to human review, and keep regulators off your back.

What are real use cases for AI agents in marketing campaigns?

From banks to telecoms, use cases for AI are expanding. Imagine:

• A retail bank using an AI marketing agent to target customers eligible for loan offers without violating GDPR.
• A telecom firm reducing churn by letting an agent tailor offers during live customer service calls.
• A B2B company automating email marketing at scale while ensuring every claim is accurate.
• An e-commerce retailer using AI agents to analyze data from 50,000 products in Google Ads, segment items by performance, allocate budgets dynamically, and optimize ROAS across campaigns.

These examples show how AI agents for marketing improve both marketing performance and compliance. They allow teams to perform marketing functions across multiple channels, while staying aligned with marketing objectives.

The future of AI: marketing operations via agentic AI and multimodal campaigns

Looking ahead, the future of AI lies in agentic AI: systems that not only generate content but act independently across business processes. Imagine a generation agent that drafts text, a knowledge base agent that sources references, and a compliance agent that approves, all running in the background.

In marketing in 2025, multimodality will matter most. Agents can even generate images, videos, or personalized graphics, tailoring assets for each customer. This is where agents operate like true colleagues, enhancing marketing effectiveness while marketers focus on strategy.

Top 7 benefits of AI marketing agents in 2025

1. Time savings through automation of campaign workflows
2. Hyper-personalization at scale (“segment of one”)
3. Compliance by design with GDPR and EU AI Act
4. Built-in predictive analytics to anticipate customer needs
5. Audit trails for defensible compliance
6. Integration with CDP and marketing platforms without rip-and-replace
7. Improved customer trust and engagement

The rise of AI marketing agents

AI marketing agents stand out for three reasons:

1. Speed: they process massive data sets in seconds.
2. Predictive analytics: they forecast customer needs and market trends.
3. Compliance: they automate rule-checks and create audit trails.

Instead of relying on fragmented spreadsheets or manual reviews, marketers get clear insights that improve campaign targeting. By combining efficiency, personalization, and analytics, AI agents are transforming marketing strategies.

For companies willing to embrace them, the payoff is clear. Smarter campaigns, faster launches, and a stronger competitive edge in a crowded digital landscape.

Key takeaways for marketers planning their next steps in AI technologies

• AI marketing tools are no longer experimental – they’re core to enterprise marketing.
• An AI marketing agent can help automate workflows, integrate with your stack, and deliver compliance-ready campaigns.
• AI agents are transforming marketing, but agents cannot fully replace human creativity – marketers remain the final editors.
• Data quality, trust, and compliance are as important as personalization.
• The best AI approach combines generative AI, analytics, and human oversight.
• By 2025, AI agents for digital marketing will be standard, not optional.

The big question for every marketer is no longer if you should use AI, but how fast you can implement it responsibly to grow your business.

Ready to make AI compliance work for you?

With Inetum’s 4,000+ AI & Data experts and proven track record in banking, telecom, and enterprise marketing, we turn agentic AI from buzzword into business impact. Talk to our AI experts

Frequently asked questions about AI marketing agents

Understanding key project management skills

According to the PMI (Project Management Institute) Pulse of the Profession Report, 62% of projects that value soft skills were completed within budget in organizations. How can you use this knowledge in your software development project?

The skills needed for project management in the IT industry (but not only) cover a wide spectrum, from technical knowledge to interpersonal skills. These skills are essential for effectively and efficiently planning, executing, monitoring, maintaining, and completing projects.

The most important soft skills for project management include the basic competencies necessary to oversee and effectively and efficiently complete projects. These skills include the ability to plan and organize tasks, manage resources, make decisions, solve problems, communicate effectively, and work in a team. They also include risk management, maintaining quality control and understanding and applying project management methodologies and tools. These skills are essential in any role that involves overseeing a project from concept to completion, ensuring that it is delivered on time, on budget, and to the required quality standards. But what does it look like in terms of specific responsibilities and duties? Let’s look at the soft skills of a project manager’s role.

The best skills for Project Manager

According to the Standish Group CHAOS Report, projects led by leaders with highly developed soft skills had a 54% higher team satisfaction rate. This is why an effective project manager is adept at balancing hard and soft skills. To become a better project manager and navigate the intricacies of software development project management, hard skills such as technical knowledge, scope management, and time management should be skillfully combined with interpersonal skills.

These soft skills, including effective communication, leadership, and conflict resolution, enable project managers to build strong relationships with project team members. By integrating technical and leadership skills, successful project managers can manage projects to achieve the best possible results while improving employee well-being in the work environment.

Difference between hard skills and soft skills

Project management skills include both hard technical competencies and soft interpersonal abilities. While hard skills provide the foundational knowledge and expertise required to manage projects effectively, soft skills are crucial for building relationships, leading teams, and navigating the complexities and challenges that arise during project execution.

Technical skills for project management

While technical skills provide the foundational expertise necessary to execute specific tasks within a project, soft skills are indispensable for managing people and relationships. Technical proficiency ensures that project objectives are met efficiently, whereas soft skills are crucial for leading teams, managing stakeholders, and adapting to the dynamic and often unpredictable nature of projects.

1. Technical expertise: Proficiency in specific tools, methodologies, and techniques relevant to project management, such as project management software (e.g., Microsoft Project, JIRA), risk assessment methodologies, budgeting techniques, and scheduling.
2. Scope management: Clearly defining project scope, managing scope changes, and ensuring that project deliverables align with stakeholder expectations. 
3. Time management: Planning, scheduling, and controlling project timelines, including creating realistic schedules and managing dependencies.
4. Cost management: Budgeting, estimating costs, monitoring expenditures, and ensuring projects stay within approved budgets.
5. Quality management: Understanding quality standards, ensuring adherence to requirements, and implementing Quality Assurance and control measures throughout the project lifecycle.
6. Risk management: Identifying potential risks, assessing their impact and likelihood, developing risk response strategies, and monitoring risks throughout the project.
7. Procurement management: Knowledge of procurement processes, contract management, vendor selection, and ensuring purchased goods and services meet project requirements.

Read also: How to build a good team? Personality types and soft skills for agile working in Scrum

Essential project management soft skills

Soft skills are an integral part of a project manager’s toolkit, as they significantly influence how effectively a project manager collaborates with team members, stakeholders, and clients. These skills drive successful project outcomes and include communication, leadership, negotiation, and managing conflicts, as well as time management and dealing with stakeholders.

Communication skills

Effective communication lies at the heart of successful project management. It involves conveying ideas, instructions, and expectations clearly and persuasively to both team members and project stakeholders. This skill encompasses good listening skills to understand others’ perspectives and articulating thoughts concisely to ensure everyone is aligned and informed throughout the project lifecycle.

Leadership

Effective leadership is fundamental to the success of any project. It involves the ability to inspire and motivate the project team, ensuring that everyone remains focused and driven towards achieving project goals. This skill requires a project management professional to clearly articulate the project vision, set motivating goals, and provide the necessary support to overcome obstacles. Leadership skills also entail effective delegation, conflict management strategies, and decision-making that align with the project’s objectives and benefit all stakeholders. The essence of effective leadership lies in creating a positive and productive environment where each team member feels valued and motivated to contribute their best.

Negotiation

Negotiation is a crucial skill, encompassing the ability to reach mutually beneficial agreements. It involves clearly defining and negotiating the project scope, budgets, timelines, and resources to ensure that all parties are aligned and that the project can proceed smoothly. This skill requires understanding the interests and constraints of all parties involved and communicating needs and limitations effectively. 

Successful negotiation aims to find common ground and resolve differences constructively, leading to agreements that satisfy all stakeholders while keeping the project on track. The ability to negotiate well helps in managing expectations and preventing conflicts, ultimately contributing to the overall success of the project.

Time management skills

Managing time effectively is crucial to ensure tasks are completed on schedule and project deadlines are met. This skill requires project managers to prioritize activities based on their importance and urgency, allocate resources efficiently, and adapt to changes in project timelines without compromising quality or objectives.

Conflict management skills

Conflict resolution is essential for maintaining a productive and harmonious team environment. It involves addressing and resolving disagreements constructively, ensuring that conflicts do not hinder project progress. This skill requires the ability to listen actively to all parties involved, understand their perspectives, and facilitate open and honest dialogue. By mediating disputes and guiding the team towards mutually acceptable solutions, a project manager helps to restore focus and collaboration. 

Stakeholder management

Effective stakeholder management is crucial for ensuring that all parties involved in a project are engaged and satisfied. It involves actively managing relationships with stakeholders by understanding their needs and expectations and keeping them informed throughout the project lifecycle. This skill includes regular communication, addressing concerns promptly, and incorporating stakeholder feedback into project planning and execution. Successful stakeholder management helps build trust and support, which is essential for achieving project goals and securing necessary resources. By maintaining positive and transparent relationships, a project manager can ensure stakeholder alignment and foster a collaborative environment that contributes to the project’s success.

The importance of soft skills in project success: Why do you need to develop soft skills?

Soft skills in project management significantly contribute to project success by enhancing communication effectiveness, facilitating seamless teamwork, and nurturing a positive project culture. Effective communication ensures that project goals and expectations are clearly understood by all stakeholders, minimizing misunderstandings, and maximizing alignment.

Teamwork is strengthened through the ability to motivate and inspire team members, resolve conflicts constructively, and encourage collaboration. Moreover, a positive project culture fosters an environment where creativity and innovation can thrive, enabling teams to devise innovative solutions and adapt to evolving project requirements.

FAQ

While technical debt may sound similar to financial debt, if you accrue technical debt it can lead to major headaches down the road for your IT department, software project, or product team. In this article, we’ll dive into what technical debt is, why it matters, and how to identify and manage it effectively.

What Exactly is Technical Debt? + Definition of Technical Debt 

Before we get into the detail, let’s start with a definition to understand what exactly is technical debt: 

Technical debt is the cost of speeding up your software development process, with bugs, fixes, and workaround solutions adding up to create operational IT issues over time. Put simply, it’s the debt the organisation builds when choosing an easy solution in the short term rather than building a comprehensive solution for the long term. 

Just like financial debt, as you add more technical debt to your architecture, the impact compounds over time, leaving you at risk of a complete failure in your IT network or critical applications. 

But no organisation is without debt. Debt occurs naturally as technology advances, with legacy code, unsupported systems, and new features meaning organisations are always carrying a certain level of debt. The trick though is to manage technical debt effectively to stay ahead of future catastrophes.  
 
Also read: 

• Clean Architecture   
• Legacy system modernization  

What is The Risk of Tech Debt, And Why is it Important? 

If your level of technical debt gets too high, it’ll start to have a negative impact on your business. It’ll also impact future projects, reducing their long-term viability, scalability, and maintainability. 

To bring this to life, here are some of the key risks and negatives of too much technical debt. 

1. Decreased software quality: Quick fixes and workarounds tend to create bugs, vulnerabilities, and poor-quality code that degrades over time. This will reduce the speed of your software and cause slow down.
2. Reduced development speed: Trying to build on an unsteady foundation makes everyone’s job harder. Unmaintained, tangled code slows down future feature development and makes changes riskier, reducing the effectiveness of your agile development and scrum teams.
3. Increased costs: If you continue to take on technical debt, eventually, you’ll be forced into rewrites or be required to invest in creating a whole new code-base from scratch. Both of these options are expensive, incurring extra cost and taking the time of valuable resources.
4. Competitive disadvantage: If your software products begin slowing down, not only will they fail to meet business needs, but they’ll put you at a disadvantage in the market. If this continues for a period of time, it won’t be long until the company’s bottom line suffers!
5. Developer frustration: As a software developer, you want to be working on innovative and exciting projects. If instead teams must spend their time unpicking technical debt, there’s a chance they’ll get demoralized and may look for a new job elsewhere.

Over time, technical debt acts becomes a heavier and heavier ball around the ankle of your organization, slowing everything down and making it harder to more forward.

The Types of Technical Debt – 5 Technical Debt Examples 

Technical debt isn’t just related to your software code. In reality, there’s actually several areas where the cost of technical debt can build up, especially in fast moving agile teams. 

Here are five common examples of different types of technical debt from areas you may not expect. 

1. Code debt: Perhaps the most well-known type of technical debt, code debt, comes from software development teams taking shortcuts during their coding sprints. Whether it’s writing messy code, skipping refactoring, or copying/pasting dodgy code snippets, this poor quality accumulates over time into a bug-ridden mess.
2. Documentation debt: If your team don’t tidy up behind themselves, it’ll lead to documentation and design debt. If code comments, specification documents, change logs, or architectural diagrams are incomplete, teams won’t know how things work, which risks creating further unintentional technical debt in the future.
3. Testing debt: If software engineering teams fail to properly unit test, regression test, or integration test their code, there’s a chance it will fall over in the future. Poor testing is one of the leading causes of technical debt, as testing phases get skipped when timelines are tight.
4. People debt: Technical debt is often considered to be a technology-only problem, when in fact debt also comes from your development team. Lack of training, outdated skills, and inexperience in certain technologies all create debt in your team over time.
5. Technology debt: Infrastructure debt and debt arising from a chosen technology is another, more strategic source of technical debt. Using outdated frameworks, legacy tech stacks, and unsupported coding languages leads to environments falling behind and opening themselves up to security risks.

What Causes Technical Debt?

While it’s easy to see that technical debt is bad, no one sets out to create intentional debt. There are many factors that lead to development teams incurring debt, these include:

• Prioritizing speed and tight deadlines
• A lack of defined processes and standards within the development team
• Unrealistic expectations from stakeholders
• Limited budgets forcing teams into poor technology decisions
• Lack of resourcing to provide adequate time to properly design or document solutions
• Poor testing or pressure to approve code by senior team members
• Not allowing time for identifying, analyzing, and fixing existing technical debt

Basically, any time short-term goal that is prioritized over the long-term greater good is likely to create some form of technical debt.

3 Ways to Measure Technical Debt In Your Company 

Now that we know why technical debt occurs, it’s time to start detecting it within your own IT environment. Here are three metrics you can monitor to detect whether technical debt is building up. 

1. Code quality reviews: Tracking the quality of your code is the primary way to understand how much technical debt may be entering your environment. Code coverage stats, static code analysis, code complexity/maintainability scores, and linting errors are all indicators of environmental tech debt that could go on to cause operational problems.
2. Bug/issue tracking: Tracking your levels of bugs and software issues is a great indicator of technical debt. Poor quality is a direct contributor to software problems, so a rapidly growing bug backlog may indicate broader problems that are contributing to technical debt.
3. Velocity metrics: Technical debt slows down development teams. If your project management tools are showing that your team’s productivity is dropping, a tech debt-riden environment could be an underlying factor.

Combining quantitative metrics like the above with direct feedback from developers is a great way to paint the picture of your technical debt to senior management. 

A Quick Guide to Help You Reduce Technical Debt 

Once you’ve identified the amount of technical debt you hold, you need to plan for some intentional technical debt reduction. Reducing debt load doesn’t happen on its own, so you need to take proactive and deliberate steps to bring it back under control.  

Here’s a quick 4-step guide to help you on your technical debt reduction journey: 

• To begin, it’s all starts by making the reduction of technical debt a priority. If you don’t, it will always drop to the bottom of the list, leaving the problem to simply get worse over time. To do this, you need to get buy-in from senior stakeholders, accepting that parts of your development spring, resource plans, and product roadmaps will have to be sacrificed.

• Next, you must decide on a technical debt strategy. Paying off technical debt can be done in several ways, but the two most common are re-factoring and big bang. Re-factoring requires you to review and update your codebase bit-by-bit, aiming to minimise disruption while slowly bringing down bad debt. A big bang approach is more a more fundamental way of addressing technical debt, essentially starting again by re-developing in parallel. Each has their pros and cons in terms of time, cost, and effectiveness and will likely be determined by the scale of your current debt, the commitment to reducing it, and the resources you have available.

• Once you’ve established a strategy, next you must determine your cost and resourcing model. The key question here is whether you want to take the technical debt project forward in-house or use an outsourced partner. Dedicated in-house resources have the existing knowledge of your codebase, but may quickly get burnt out trying to undo years of unintentional debt. On the other hand, while an outsourced partner may take a little longer to get up to speed, they bring a different perspective, benefiting from best practice and a fresh pair of eyes.

• No matter the approach you choose, you need to agree on the standards, processes, and tools you’ll use to reduce technical debt over time. This includes an automated testing scripts, code review standards, and style guides that will establish how your improved code will look. As we’re seeing in all areas of IT, AI-tools are flooding the market to help you automatically identify and update technically compromised code, helping turbocharge your technical debt recovery.

Technical Debt Happens – Let Us Help You Manage Technical Debt 

Technical debt is the result of making short-term tactical decisions that impact the long-term stability of your IT environment. It’s an inevitable part of software development, but left unchecked, it can cause havoc on your IT environment. 

At Inetum, we’re experts at guiding organizations across the globe to re-imagine their IT capabilities, helping them reduce risk, improve efficiency, and drive operational excellence. If you’d like to hear more about Technical Debt, how to spot it, and how to begin paying off debt, join us for an in-depth webinar on the 5th June, at 11:30 CEST.  

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Whether it’s a project management process or a high-level business one, by the end of this article, you’ll be ready to get started with SIPOC. We’ll dive deeper into what it is, the benefits it can bring you, and walk through a 7-step process to help you build your first SIPOC diagram.

What is SIPOC?

SIPOC is a process management tool that helps teams visualize workflows to gain greater understanding and identify improvements. Specifically, SIPOC stands for Suppliers, Inputs, Processes, Outputs, and Customers, with each of these a lens to assess the workflow, break it down, and fully understand the component parts. 

Let’s break each area of SIPOC down into more detail. 

1. Suppliers – Here, you’ll identify any suppliers contributing to the workflow, naming them and calling out the specific goods/services they provide. 
2. Inputs – Next, you’ll consider the inputs to the process, such as a customer request, purchasing raw materials, or knowledge from stakeholders. Capturing the set of inputs helps identify the things you need to keep the workflow ticking over. 
3. Processes – Now, you’re looking for any key process steps that make up the overall workflow. For example, in a border software development process, you’ll have individual sub-processes for code development, testing, and release. 
4. Outputs – As a fourth step, you’ll identify any outputs of the process. While it’s easy to think of this as physical goods or services, this could also include other factors such as decisions, recommendations, or communications. 
5. Customers – To finish off, consider the customer at the final step of the SIPOC process. This includes who the customer is, the needs of the customer, and the experience the customer receives as part of the overall workflow. 

The SIPOC model prompts teams to consider all of these crucial elements of any process. As a visual tool, SIPOC helps understand the entire process and identify where improvements could be made. A SIPOC table, or a SIPOC diagram, is the key output of a SIPOC exercise, providing an artifact for stakeholders to visualize process-related issues and take actions for improvement.

Read also: Disciplined Agile Delivery: Framework, Phases and more (nearshore-it.eu)

SIPOC Model vs. Lean Six Sigma Projects vs. COPIS

Because the world of business process management is small, there’s often a lot of confusion between SIPOC, Lean Six Sigma, and COPIS. But the good news is, if you’re new to all three, it’s actually really simple! 

Lean Six Sigma is an overarching methodology for process improvement that includes various stages of analysis and implementation. Referred to as the Six Sigma DMAIC, those stages are Define [D], Measure [M], Analyze [A], Improve [I], and Control [C]. 

Within Lean Six Sigma, the SIPOC template is recognized and used as a crucial tool in the ‘Measure’ stage of DMAIC, helping teams to identify all the different areas of a flow before any work starts to improve business processes. So, the good news is that SIPOC is part of the Six Sigma methodology, not something different.

The comparison between SOPIC and COPIS is even more simple. COPIS, which stands for Customer, Outputs, Process, Inputs, Suppliers, is just SIPOC re-ordered. This nuance is because some companies like to put customer requirements at the start of the process to encourage teams to be more customer-focused in any new process they develop. They complete the process in exactly the same way, just in a different order!

The Benefits of SIPOC – Process Improvement & More

SIPOC is a tried and tested methodology for improving business processes, and there are many reasons it’s so popular. Let’s look at some of the key benefits you can receive by following the SIPOC process. 

• Helps with problem-solving. SIPOC provides a structured way to evaluate a business problem by breaking it down into component parts. If you’re struggling to solve a process problem, there’s a good chance SIPOC can help.
• Provides clarity for the team. Lagre organizations are complicated places, but a SIPOC diagram documents everything in a clear and simple process map. This high-level overview provides clarity for the team and helps everyone move forward. 
• It’s simple to put into practice. You don’t have to be a super-experienced project professional to start using SIPOC, thanks to its simplicity and structure. This means anyone can build a SIPOC map without years of training or spending lots of money. 
• You’ll start speaking a common language. Because SIPOC is so popular, it’ll help you have better conversations with suppliers and customers, as there’s a good chance they’ve used it, too! 
• Efficiency = value. Of course, the most significant value of using SIPOC is the end result. Gaining process efficiencies can save you time, resources, and money, meaning it has a direct impact on the bottom line of your business. 

How to Create a SIPOC Diagram – 7-Step Guide

Now that you know all about SIPOC, how it’s used within other business process improvement methodologies, and the benefits a SIPOC diagram provides, it’s time to get on and start building your own. 

To help, let’s go through a 7-step guide, breaking down the elements of the process to help you get started immediately. 

1. Select your business process. The first step is to choose a business process that needs a SIPOC review. This might be a process that causes problems, is old and clunky, or even just central to your business operations.
2. Define the process. While SIPOC reads with Suppliers first, in reality, you always start by defining the process steps first. To do this, detail an overview of the business process’ high-level steps, including the actions and who does them.
3. Identify the outputs. Note down the outputs from the process, keeping things simple with facts and nouns. Remember, outputs aren’t just goods and services but can be information, decisions, or communications, too.
4. Include your customers. Next, define who your customers are that benefit from the process. These won’t always be traditional money-paying customers, but may be internal stakeholders such as board members of system users.
5. List the inputs required. Now, list the inputs by considering the resources, knowledge, and decisions needed for the workflow. A SIPOC diagram doesn’t need to be war and peace, so keep this high level.
6. Identify the suppliers. This section lists the suppliers associated with each of the processes’ inputs. A supplier is anyone externally with direct input on the process, so make sure you include them all.
7. Get the diagram out there. Congratulations! You’ve completed your first SIPOC diagram and can share it with the team. Use the diagram as a central reference point to bring clarity, identify weaknesses, and implement improvements to your business process moving forward. 

Below, you’ll see a SIPOC example to illustrate what you’ll create. A format like this shows the overview of the process in one place, including your inputs and outputs, customers, suppliers, and process steps. 

It’s Time to Get Improving With SIPOC

When it comes to improving business processes, there aren’t many better frameworks than SIPOC. A SIPOC diagram is a tool used to visualize any process you want, highlighting the suppliers, inputs, process steps, outputs, and customers for any operational flow. 

Whether you’re running a project or just looking to optimize your business, it’s a great tool to help you and the team bring clarity, speak a common language, and solve complex business problems. 

Speaking of complex business problems, if you’re still struggling to fix a burning business issue, why not contact us at Inetum to see if we can help?  Inetum Consulting helps clients across the globe define the strategic target, direction, timing, and speed of their transformation plans, as well as provide operational support to implement solutions into your core business processes.

If you’d like to hear more, schedule a meeting with our specialist:

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But coordinating all of this is hard. To get it right, project managers need tools and techniques to help them out, and one of the most popular is RASCI. A RASCI matrix is essential to clearly define the different roles and responsibilities for everyone within the project, ensuring they’re all clear on what to do and when. 

In this article, we’ll dive deep into RASCI, looking at what it is, the benefits it can deliver, and how it compares to other project team models such as RACI. Then, to finish, we’ll share 5 crucial best practices to help you maximize your chances of project success!

What is RASCI? + RASCI vs RACI & a RACI Chart Example

RASCI, also known as the RASCI Matrix, the RASCI Framework, or the RASCI Responsibility Matrix, is a tool used in project management to assign roles to individuals within a project team. 

RASCI is an acronym that breaks down individuals’ roles for specific tasks. These roles are Responsible, Accountable, Supporting, Consulted, and Informed – we’ll get into more detail on what they mean later on! You’ll also commonly come across RACI as well as RASCI – they are used interchangeably, as a RACI is a slightly leaner version of the tool that doesn’t include the Supporting role. 

Converting RASCI or RACI into a chart format gives everyone on the project complete visibility of what they should be doing, helping to avoid confusion, delays, and conflict. For example, within a software development project, different team members will be responsible for designing, developing, and testing the software, with subject matter experts consulted or supporting where required.

Here’s a great example from the team at Smartsheet that demonstrates how a RACI matrix is used in practice. Here, you see the project tasks and deliverables listed on the left-hand side of the matrix and the individual job roles across the top. Through the middle of the chart, R’s, A’s, C’s, and I’s connect the dots to show who is responsible, accountable, consulted, and informed for each task. 

RASCI Matrix Explained – Role and Responsibilities for Project Management

Now that we know what the RASCI model is, it’s time to get into the detail of what it all means. To help you do that, let’s look at each of the roles in turn to understand exactly what they mean. 

Responsible

The responsible person is often seen as the most important for any task as they are in charge of completing it. Other terms such as task owner or task lead may be used here as the responsible role also plans the tasks and directs others to support as required.

Accountable

The accountable person verifies, signs off, and is held to account for the task being completed. In many instances, the person who is responsible and accountable for the task is the same to allow for complete ownership.

The key way to distinguish the person responsible and the person accountable is to ask yourself – Who will be in trouble if this task doesn’t get completed? Answer that question, and you’ll identify the one accountable. 

Supporting

The supporting role may not have any responsibilities, but they are still incredibly important to the project’s success. These individuals provide input and supplementary work to help the project progress. 

Rasci Chart Explained – Source

Consulted

Similar to the previous role, those who are Consulted provide input on the project. The slight difference here is that the inputs focus more on reviewing, validating, or auditing the project’s tasks rather than actively contributing to their completion. 

This similarity between Supporting and Consulted is why the simpler RACI model is often used instead of RASCI.

Informed

In any project, there will be a group of stakeholders who need to be informed about a particular task. The informed group does not actively participate in the project but may be impacted by the project’s milestones, deliverables, or outcomes. 

The Benefits of a RACI and RASCI Chart For Your Project

As we mentioned earlier, RACI and RASCI are commonly used tools to help project managers keep control of their deliveries. Here are some of the benefits you can achieve by using RASCI in your own projects:

• Remove confusion by clearly defining the responsibilities of individuals
• Improve team efficiency by having clear owners to complete each task
• Improve the speed of decision-making with well-defined accountable owners
• Clearly break down project tasks to help you better plan each part of the project lifecycle
• Reduce conflicts between team members around ownership and responsibilities
• Align stakeholders on what people or teams are doing and when
• Improve morale by providing clear ownership, responsibility, and autonomy
• Bring clarity to resource management by having a clear picture of everyone’s involvement in the project

As you can see, a RACI chart is a project management must-have to ensure everyone directly involved in the project knows what they’re doing for each task or deliverable. Get that right, and you’ll see other areas of your project improve too!

5 RASCI Best Practices to Take Away

Creating a RASCI responsibility assignment matrix is a simple task if you know how to do it right. To finish up, let’s look at some RASCI top tips to help you when you first start to create your own! 

1. Make RASCI a collaborative process. While a RASCI chart is used to assign multiple people to each task, it shouldn’t be created by the project manager alone. To maximize the effectiveness, building a chart should be a collaborative process with the whole team. This will help you identify all the work to complete and help you get a collective opinion on the best individuals or teams for each task. 
   
2. Each task can only have one Accountable person. As you build your chart, you’ll find that many tasks or deliverables will require the input of many team members. While the people responsible for each task can be shared, it’s best practice to only ever have one accountable owner. This is because ultimate leadership needs to come from one voice to avoid confusion and a lack of ownership. 
   
3. Regularly review as the project progresses. Your RACI chart shouldn’t be a once-in-time document, it should evolve and update as the project progresses. Many things can change during the life of a project, including team re-structures, the project scope, and the resources assigned. As such, it’s best practice to review your RACI every 2-3 months to ensure all clearly defined roles have the right owner. 
   
4. No empty boxes. A RACI chart is designed to bring certainty to your project, so leaving any boxes blank will only cause confusion. Sometimes, an individual may not need to be consulted, and no one needs to be kept in the loop. That’s okay, but make sure that every task of your RACI is marked with something, even if it’s an ‘N/A’, to show it has been actively considered and not just forgotten. 
   
5. Align stakeholders to ensure buy-in. The RASCI method only works if everyone is aligned and bought into the process. Most project teams will assign their Project Sponsor as the approver of their RASCI chart to ensure it’s been aligned with a senior audience. This helps create ultimate clarity for the sponsor on who is directly responsible for each task throughout the project lifecycle.
   
6. Use a project management tool to help. Like many things in project management, completing your RACI allocation is much easier with a tool that helps the process. These tools provide easy visualization of who is responsible for a task, who is the person in charge, and who needs to be involved. This is especially useful for complex projects where you may have a long list of names that need to help out. 

It’s Time to Start Creating a RASCI Matrix

A RASCI matrix is a great project management technique to clearly define who is responsible for completing tasks and deliverables within a project. Used well, it can provide clarity for the team, enable effective decision-making, and improve all-around team effectiveness. 

If your RACI is defined, but you’re still struggling to get some momentum on your project, why not contact us at Inetum to see if we can help? Inetum Consulting helps clients across the globe define the strategic target, direction, timing, and speed of their transformation plans, as well as provide operational support to implement solutions into your core business processes.

If you’d like to hear more, schedule a meeting with our expert.

Streamline Your Application Maintenance

Leszek Jaros, our Head of Telco and AMS Practice, is here to help you navigate the complexities of Application Maintenance Services. Book a consultation to boost your application's efficiency

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 FAQ

Do we use data and money the same way? 

A large amount of raw data from the different sources we deal with these days requires the support of business analytics tools, which can help business leaders to make informed decisions and predict upcoming events. I mentioned that data is the most valuable asset that companies have. But do we know how to monetize it? One of the speakers at the Data 2030 Summit conference in Stockholm, which I attended, suggested this simple exercise to participants: imagine that data in your organization is treated the same way as money.

Do you know who has access to it and to what extent? Who brings it into the organization and who spends it? And what if it turns out that money comes into various bank accounts and in different currencies? 

Data-driven decision-making (DDDM) 

It is the same with data – the quantity of data comes from different sources (CRM systems, Excel files, dedicated systems) and can be used effectively or not. Often, even with well-structured data and access to information, the business does not know how to make use of it. To start using data to their advantage, business leaders need to know the questions they want to answer. This is why the role of analysts, whose job is not only to prepare reports but also to draw conclusions from the data, is invaluable. Such work is made easier today by Business Intelligence class solutions. 

What is a data-driven organization? 

Data-driven organizations: 

• Use data to make decisions – a data-driven enterprise bases all its decision-making processes on data, from cost optimization decisions to implementing new business strategies on an international scale. 
• Ensure data is available to everyone – using data at every level of an organization is an important element (it is called data democratization, or data democracy). Data-driven decision-making is not just for executives. In a data-driven organization, both professionals and managers use data and analytics to their advantage. 
• They drive business strategy based on data – decision-makers use data not only to analyze past business events but also to predict future ones. These predictions are therefore based on facts rather than intuition or experience.  

Using data to inform – a data-aware approach 

There is a large group of organizations that can be described as “data-aware”. They use analytics and make decisions with data, but only in specific areas. These organizations operate very similarly to data-driven companies but they do not usually perform prospective analyses and therefore rely only on historical data.

Harnessing data: analytics vs. intuition 

The reasons mentioned above result from limited trust in data at some companies. There are also organizations that reject the data-driven model. These companies prefer to rely on the experience or intuition of their staff. This might be due to a lack of suitable self-service analytics tools to allow them to create different scenarios for the future. The lack of metrics and dashboards makes it difficult to be proactive and make strategic business decisions that align with business goals. 

Creating a data culture 

What is a data-driven culture? In a data-driven culture, decisions are made based on particular figures and information from data. In practice, this means moving away from basing decisions on premonitions to promoting data analysis regardless of department and position. 

When a company develops a data-driven culture, it puts the emphasis on data. It realizes its importance, the benefits it can bring, and just as many risks (e.g. of misinterpretation or cyber security issues). It teaches employees to use data to minimize errors in their decision-making process. The right culture within a company helps to simplify this and reduces risks. 

Use data to answer critical questions in any industry 

We have become accustomed to associating data analytics with advertising, media, and e-commerce. It is also a powerful tool in the hands of marketing, sales, and accounting departments. A data-driven approach supports: 

• Marketing activities – in this context, they most often help to assess the effectiveness of social media activities, not to mention website traffic analysis or user flow analysis. 
• Sales activities – in sales, it would be sales funnel analysis and sales channel effectiveness respectively. 
• E-commerce activities – shopping basket analysis and seasonality of sales. 

However, the door to using data analytics tools and being data-driven is open to any company, regardless of the industry. Our collaborations and Business Intelligence implementations in the healthcare (GE Healthcare) and construction (Skanska) industries attest to this. 

Expert knowledge Is MongoDB the perfect database system for e-commerce?? Read the text!

The advantage of data-driven companies 

Data-driven organizations “play with open cards” when it comes to data and gain several trump cards as a result, such as: 

• Efficiency – primarily due to the fact that the data in the organization is structured. This creates the opportunity to generate accurate reports. A recent study conducted by Deloitte and compiled in the “High Impact People Analytics” report showed that high-performance organizations make analytics tools available to employees at all levels. 
• Transparency – making analytics tools accessible to managers at all levels of the organization not only increases productivity but also improves organizational transparency. 
• Engagement – access to data and the trust shown gives employees a sense of responsibility which, in turn, increases their engagement and impacts productivity. 
• Speed – the business decisions of a data-driven organization are made based on specific data and facts. This dramatically increases the speed of decision-making. By analyzing real-time data and past data patterns, the decision-making process not only becomes faster but also gives companies confidence that they are making the right decisions. 

Obstacles to becoming data-driven 

Despite the benefits, many companies still do not have a well-developed platform for analyzing and storing data. Data is stored in different locations and organizations do not have a system to manage it. Most often, who should have access to which data and to what extent is not clearly defined. 

Why does this happen? In 2021, we conducted a survey called “Use of Business Intelligence tools in Poland”, which confirmed our assumptions – almost 40% of respondents did not use data analytics tools in their companies. The most frequently cited constraints were a limited budget, insufficient data for analysis, and a lack of analytical knowledge and competence in the organization. Having an IT structure that includes hiring the right data teams and building a data culture are the first steps that companies aspiring to become data-driven should take. 

IT leaders use a data-driven approach 

Among the world’s top companies, we can easily identify those whose business is strongly linked to IT. The common denominator for giants such as Google, Apple, and Samsung is that they use data to make decisions. For example, the Data-Driven Decision Intelligence Model introduced in many divisions of the Samsung brand is now used not only in business processes but also, for example, in supply chain management in logistics or marketing. Samsung Research is just one example of a solution for data acquisition, storage and processing. Such tools, based on the latest cloud technologies and deep learning, are becoming increasingly popular among large companies. 

Expert knowledge Qlik Sense SaaS. Cloud Analytics for enterprises What is the difference between Qlik versions and what options they give users? Read the article!

Data-driven decision-making – summary 

In recent years, the importance of data has increased significantly, resulting in more requests for data analytics systems. These systems are no longer being used only by the largest companies, but also by specialized modern businesses wishing to use analytics to predict trends rather than just examine historical data – not to mention data visualization. 

Embracing Advanced Data-Driven Strategies

As more organizations recognize the transformative impact of data on business strategy, the journey towards becoming truly data-driven becomes central to competitive advantage. Advanced data-driven strategies not only streamline operations but also enhance responsiveness to market changes and consumer needs. It’s essential for businesses to explore comprehensive insights on why and how data-driven decision-making can revolutionize their decision-making processes. For a deeper understanding of these strategies and their profound impact on corporate success, consider exploring our detailed analysis in data-driven decision making

Self-service tools such as Microsoft Power BI, Tableau or Qlik Sense, thanks to their intuitiveness and use of data science solutions, offer everyone enormous business opportunities to gain a deeper understanding and build strategies to move the business forward. The first step to becoming data-driven is to collect data, which many companies are already doing today. However, in order to start making decisions based on it, you need to know which systems it comes from and which of them will be valuable in the decision-making process. These are some of the steps we help our clients with. We share our data skills and knowledge to build awareness by carrying out implementations of Business Intelligence systems. 

Sound interesting, right? By the end of this article, you’ll know whether DAD might be right for you. To help, we’ll dive into the detail of exactly what it is, how the framework, lifecycle, and team roles fit together, and compare it to other popular frameworks such as Scrum and XP. 

Let’s get started!

What is Disciplined Agile Delivery?

Disciplined Agile Delivery (DAD, or sometimes referred to as DA for Disciplined Agile) is a people-first, hybrid Agile approach to software delivery and IT project management. 

Based on an agile methodology and with continuous delivery principles in mind, DAD provides development teams with a set of comprehensive, end-to-end delivery lifecycles that streamline processes and guarantee excellent results.

While relatively new to most, it draws on frameworks you’ll already know and may have already used. Specifically, it takes inspiration from XP, Scrum, Agile, and Lean, combining many of those toolkits to create a range of structured, hassle-free, scaled agile frameworks. 

The History of The Framework

DAD was born in one of the most advanced, well-known, and influential tech companies, IBM. Although used in practice since 2009, the framework was introduced to the world by Scott Ambler and Mark Lines in their book ‘Disciplined Agile Delivery: A Practitioner’s Guide to Agile Software Delivery in the Enterprise‘ in 2012.

The first exploratory iteration of DAD as a way of working was focused on providing more structured processes and decision-making governance. By adding structure and governance to DevOps and agile ways of working, teams immediately began to see tangible results with DAD. Over time, the concepts evolved into ‘Disciplined DevOps‘ before going on to become a commonplace framework across the wider software development industry.

Nowadays, the broader methodology of DAD has extended beyond just software development. It is now a common approach to agile delivery in business areas such as finance, procurement, IT infrastructure, and IT strategy development.

The Lifecycle and Phases Explained

One of the best things about the Disciplined Agile Delivery Framework is that it has something for everyone, depending on how you apply it. 

At the highest level, DAD focuses on the entire system lifecycle, providing structure and guidance from project initiation through to the ultimate retirement of a system. 

Source – Project Management Institue

Below this high-level lifecycle is a wide range of sub-frameworks to choose from. Most of them focus on variations of the key three delivery phases (Inception, Construction, and Transition) as these concentrate on getting working software into the hands of users. Examples of these sub-frameworks include: 

• Agile Lifecycle. Great for Agile projects, the Agile lifecycle is based on Scrum but extended to cover pre-work such as strategy development and stakeholder alignment.
• Lean Lifecycle. A Kanban-based lifecycle that’s great for new, lightweight teams that want to combine Kanban, Lean, and Agile principles.
• CI/CD Agile Lifecycle. Same as number one, but focusing on long-lived, stable product teams.
• CI/CD Lean Lifecycle. Same as number one, but focusing on long-lived, stable product teams.
• Lean Startup Lifecycle. Great for teams looking for easily consumable guidance on strategy and efficient delivery in a startup environment.
• Program Lifecycle. Great for strategic managers focusing on scaling and bringing together a team of teams.

The Disciplined Agile Delivery Roles – How Does The Team Fit Together? 

Like all agile frameworks, DAD has a set of defined roles that help teams deliver smoothly and effectively.

While DAD doesn’t set out to prescribe exact details to teams, building an agile team that can still self-organize, work collaboratively, and delivers on its stakeholders‘ requirements is essential. For that reason, the DAD framework requires the following key roles: 

1. Stakeholders. Like many other frameworks, in DAD, a stakeholder is defined as someone who can impact or is impacted by the solution being built. Your project will have a variety of stakeholders, from end-users to senior management. The key thing for DAD is identifying your stakeholders early and involving them regularly in your projects. 
2. Team Member. Team members are those who directly contribute to building the solution, e.g., programming, designing, testing, or planning. Like all Agile teams, team members contribute skills that the team needs, but DAD recognizes (unlike other frameworks) that those skills may not always be in direct development. Like with stakeholders, you’ll have many team members across your project.
3. Team Lead. Much like a Scrum Master or Agile Coach in other methodologies, the Team lead facilitates and guides the team instead of taking on technical responsibility. The Team Lead should act as a servant leader, continuously looking for ways to optimize team performance, capture agile data that drives improvement, and help remove blockers and issues.
4. Product Owner. The Product Owner is the one individual on the team that represents the customer, either through or in direct collaboration with the stakeholders. Each DAD team will have a dedicated Product Owner who helps answer questions, manages communication with stakeholders, and champions the team’s work.
5. Architecture Owner. Where many frameworks fail is that they forget to consider the bigger picture. To overcome this, DAD explicitly includes the Agile Modeling role of the Architecture Owner. The Architecture Owner looks holistically at the system design, the longer-term plans, and the risks to the system and the project. Unlike the other DAD roles, the Architecture Owner can be a dual role and is often held by the Team Lead as they are the most senior and have the most technical knowledge.

Outside of this, there may be several supporting roles, such as Subject Matter Experts, Specialists, Domain Experts, and Independent Testers or Integrators.

Read also: Guide to Scrumban methodology

Disciplined Agile Delivery vs. Scrum vs. XP – Why Might DAD Be Better For You?

As we’ve seen throughout this article, DAD was built on the foundations of other frameworks, such as Scrum and Extreme Programming. 

If you’re currently operating Scrum, XP, or any other agile software development framework, here are some reasons you may choose to transition to Disciplined Agile Delivery. 

• More Complete Lifecycle: DAD provides you with a complete end-to-end framework and lifecycle covering everything from the solution concept to the eventual retirement. There is where DAD goes beyond Scrum and provides fuller support for your entire software development operation, including strategy design, deployment, and production. 
• Structure & Adaptability: DAD provides a solid base of structure and support while also building in adaptability to flex for your own business needs. Other Agile methodologies can be very prescriptive, giving delivery teams no freedom to express themselves within their end-to-end process. Thanks to the many options within DAD, such as Disciplined DevOps, Lean Lifecycle, and Program Lifecycle, you can find something that works for you. 
• Constant Updates. As DAD becomes increasingly popular, new updates, thought leadership, and varieties are being developed, helping you and other users stay ahead of your ever-changing environment. Unlike Scrum, which is set in stone, this allows DAD to remain resilient and modern moving forward.

Read also: Agile Software Development: Extreme Programming (XP) Explained

To Wrap Things Up…

If you’re looking for a way to deliver agile software development while maintaining structure, good governance, and control, the Disciplined Agile Delivery (DAD) framework might be for you. Modeled on some of the best and most popular methodologies, such as Scrum and XP, DAD provides everything you and your team need to deliver great results for your business stakeholders. 

At Inetum, we provide all the services necessary to achieve IT excellence in everything you do. Whether it’s disruption, efficiency, or scaling your operation, our team of experts can help you go to the next level by helping you choose, implement, and scale your chosen delivery methodology. 

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What are project management skills?

Put simply, project management skills are the mix of competencies, learned behaviors, and personal attributes you need to be a great project manager that consistently delivers project success.

While there are hundreds of skills you may need depending on the type of project you’re delivering, there are a core set of skills every project manager needs as a foundation (hint, we’ll cover those later on!).

As a general rule, those skills are broken down into two categories: soft skills (e.g. interpersonal and communications skills) and hard skills (e.g. technical and trained skills). Especially on the highest risk and most important projects, it’s key to have a good blend of those hard and soft skills to ensure you’re ready for any situation.

How to develop your project management skills

It doesn’t matter if you’re just starting your career as a project manager or you’re a seasoned professional, it’s important to keep improving your project management skills. When it comes to developing those skills, there are three main routes to consider:

• Education – Given project management is such a large and varied industry, there are so many training materials online to help you learn the most important project management skills. It’s as easy as running a Google search or heading onto platforms such as Udemy to get started, with paid courses providing 1:2:1 tuition or specialist knowledge.
• Qualifications – If you want to take your education one step further, many project professionals turn to formal qualifications to dive deeper into certain aspects of project management and gain external recognition. One of the most popular qualification routes is through the Project Management Institute, but qualifications such as Prince2, AgilePM, and MSP are also available.
• Experience – As you develop as a project manager, practical experience and skills are the most important ways to improve and grow. Especially when it comes to soft skills, these will only improve through working on different problems, dealing with different stakeholders, and delivering different goals.

If you’re on the route to becoming a project manager, we’d suggest aiming for 70% experience, 20% education, and 10% qualifications to help you maximize your personal development.

Soft skills for project management – why are they important?

Many people will argue that the best project managers are those who master project management soft skills. 

But what do we mean when we talk about soft skills?

Soft skills are defined as the ‘personal attributes that enable someone to interact effectively and harmoniously with other people.’

Given project management is a people-focused profession, your ability to work well with team members and stakeholder is crucial for success. Examples of core soft skills include communication, leadership, motivation, and relationship building.

Read also: The Key Leadership Skills You Need for The 21st Century Workplace

Technical skills and hard skills for project management – why are they important?

Hard skills are also essential skills for project management. 

Hard skills are defined as the ‘specific abilities, capabilities and skill sets that an individual can possess and demonstrate in a measured way.’

In project management, these are the specific tools and techniques you need to master to run a project from start to finish. These include planning, budgeting, stakeholder management, risk management, and quality management. 

While many people use the words ‘technical skills’ and ‘hard skills’ interchangeably. But in subfields of project management, such as IT or software development, you may also need dedicated technical skills such as coding or software testing to help you effectively manage the change at hand. 

Project management skills list – The 20 skills you need to succeed as a project manager

Great, we know all about project management skills, the types, and why they’re so important to keep developing. Now it’s time to explore a list of project management skills that are the most important to guarantee your success. 

1. Communication

As a good project manager, you’ll need to communicate regularly with clients, managers, and team members. to keep your project moving. In the modern world, you’ll need to do this through many channels, including in-person meetings, phone calls, and video conferences.

Excellent communication skills help you earn your team’s trust, convey ideas, and lead your team to successful project outcomes.

2. Leadership

As the leader of your project, a key project management skill you’ll need is leadership. 

Leadership is important for many reasons. You’ll use your leadership skills to set the tone for the project, define the vision and expectations, deal with unexpected twists and turns, and resolve conflict. Leadership skills go hand-in-hand with other skills, such as communication, motivation, and problem-solving, to make you an all-around effective role model.

3. Decision making

One of the critical skills needs to be a project manager is decision-making. You’ll need to make tough calls on things line tasks management, budgets, scope, and risks to keep things moving while maintaining control. Strong decision-making will also help you set expectations, earn respect, and set clear expectations for the team. 

4. Problem-solving

When managing complexity, effective project managers need to solve problems quickly. It’s common for issues to arise, such as scheduling conflicts or delays, but a project manager’s job is to solve those problems and lead the way forward for the team. 

Problem-solving is one of the most important soft skills for project managers, and as such, we’d recommend putting it into your development plan, no matter your level of project management experience. 

5. Conflict management

When people work together in business, you must expect conflict to occur. As the central figure in a project team, you’ll need to master conflict management to keep everyone happy. 

Project managers are often the ones to facilitate and mediate a conversation, helping the team present their ideas and opinions in a constructive way, and find common ground to identify a potential solution. This helps the project move forward and deliver their objectives.

6. Motivation

The best project managers can motivate their teams to keep them operating at their most productive level. Of all the soft skills mentioned in this article, maintaining motivation can be one of the most difficult as every individual reacts and works differently. 

To do this, the best project managers alternate between providing constructive criticism, giving rewards, and celebrating milestones to keep morale high and productivity high.

7. Relationship building

Project managers are often expert networkers, building strong relationships with stakeholders, team members, and clients to create an army of project allies. 

The best way to build relationships within the team is to run team-building activities, while also taking dedicated time to learn about people’s lives, what matters to them, and how you can all work together to achieve your individual goals. 

To build great relationships, emotional intelligence and self-awareness are a must to ensure you push and pull at the right times, avoid conflicts, and create long-lasting bonds.

Read also: Personality types and soft skills for Agile workers. How to make a good Agile team?

8. Organization

Project managers are responsible for organizing the entirety of their projects. As such, they need organizational skills to see the bigger picture and manage individual tasks and actions. Organization skills also help to keep the project on track, including managing resources, timelines, and budgets.

Organization is one of the basics of project management, so if you’re new to the profession, make an investment to become organized as quickly as possible. 

9. Time management

All projects have deadlines, milestones, and goals, and managing them is a major part of the project management role. As such, you need the time management skills to keep your own time in check, as well as oversee the time management of those around you.

Project managers employ many different ‘hacks‘ to help with team time management, including scheduled meetings, timeboxing, prioritization, and to-do lists to help them focus on the right things at the right times.

10. Planning and Scheduling

Effective project planning and project scheduling, and ultimately creating a project plan, is crucial to the success of any project. Without project management planning and scheduling, there’s no way to monitor that a project is on track, assess progress vs goals, and give guarantees that objectives can be met.

There are many techniques and tools project managers can use to help with their planning, including the critical path method, PERT, and Gantt charts.

11. Budgeting and Financial Management

No projects come for free, so one of the most important skills in the entire project management field is to know how to budget and manage tour finances. 

While you don’t need to be a qualified accountant, you do need to understand how to cost for different resources, track expenditures, and consider concepts such as inflation, capitalization, and depreciation. While we’ll come onto it later, many project managers use a budget management tool to ensure their finances are always healthy.

12. Risk Management

Projects are inherently risky places to work, with twists and turns around every corner. To improve your project environment, the best project managers need to identify, assess, manage, and mitigate risk. 

This includes developing contingency plans, working with experts, and putting plans in place to mitigate events before they cause serious problems. Risks can be industry specific or general and can vary from legal to business risks to reputational risks.

13. Project Methodology

A key to project success is to determine which project management methodology to use within your project. While Agile and Waterfall are the most common high-level approaches, there are a range of project management processes, project management techniques, and project management tools to utilize. 

Both traditional project management and agile project management techniques have pros and cons, so the devil really is in the detail to select the correct one. This becomes easier over time, but it’s important to base your selection on the needs of your stakeholders, your budget available, the risks of your environment, and the level of detail available to you when you begin.

14. Technical Knowledge

As we discussed earlier on, if you’re working on specific types of projects, you may need an element of technical knowledge. This will work on a case-by-case basis to know what skills you need for your technical environment. 

This could range from simple skills, such as how to use computer systems or workplace technology, through to being able to write your own software code, test scripts, and deploy new features.

15. Quality Management

In the same way project managers track timelines and costs, they also need to ensure the project delivers to the right level of quality. Many project management methodologies include structured tools, techniques, and frameworks for managing quality that can help you ensure you deliver what your project needs.

Read also: The Complete Guide to Agile Project Management

16. Task Management

If you want to be a great project manager, you need to master the art of task management. While it’s a pretty tactical, low-level skill, it’s one of the crucial skills needed to keep your project moving. 

Many project managers manage tasks through action and to-do lists, ensuring everyone understands the tasks that are assigned to them, when they should be completed by, and the consequences if they are late or of poor quality. It’s important to ensure you manage your own tasks effectively to set a good example to the team and keep your project’s progress on track. 

17. Project management software

Ever looked at a successful project manager and wondered how they do it? Chances are they’re using project management software to make their lives 100x easier. Project management tools such as Jira, Asana, Monday.com, and ClickUp are great for keeping the team’s work in one, easy-to-access place. 

The size and scale of these tools vary from simple task management software to full enterprise-scale reporting and monitoring. Wherever you are in your project management journey, an effective project manager must master their PM tool, so take the time to learn what’s used in your business.

18. Scope management

If you don’t have a strong grasp of your project scope, there’s a good chance your project will fail. Project scope defines exactly what you’re going to do (and what you’re not going to do), and an effective project needs to deliver the project goals. 

As a project manager, your job is to manage the scope throughout, including identifying the scope, managing any changes, and ensuring the full scope is delivered at the end. Like budget or quality management, there are many frameworks out there for managing scope, so take the time to find one that works for you. 

19. Stakeholder management

The best project managers know how to get the best out of their project stakeholders. Stakeholder management is one of the essential project management skills every project management professional needs.

This all begins with stakeholder analysis, before putting a plan in place to manage each stakeholder effectively to keep them on side with your project’s objectives. 

20. Facilitation

If you want to be an effective project manager, you need to use your interpersonal skills to bring people together, brainstorm new ideas, and come up with solutions. 

One of the most important skills to use to achieve this is facilitation, be that in team meetings, one to one’s, or in a large group setting. When choosing the right project management approach, more and more project managers adopt a servant leadership style that focuses on bringing the best out of others through facilitation rather than pushing forward their own ideas. 

To Wrap Up…

Project management is one of the most exciting, rewarding, and challenging career paths out there. But, if you can master the hard, soft, and technical skills, you too can be a great project management professional. 

Our list of 20 skills is just the start of your journey, and we’d encourage you to learn project management skills throughout your career to keep growing and developing your own effectiveness. 

If you’re a CTO, Change Leader, or Transformation Director looking to bring new ideas, skills, and solutions to your business, why not check out the Inetum website? We offer services across transformation, digital, and innovation that could help you and your team move to the next level and deliver even better results. Read more about how we deliver value here.

Elevate Your Application Development

Our tailored Application Development services meet your unique business needs. Consult with Marek Czachorowski, Head of Data and AI Solutions, for expert guidance.

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What is the You Build It You Run It Model? 

Put simply, the “You Build It You Run It” model brings two teams into one by combining delivery and operations responsibilities for a software product together into one development team. 

Because one team manages the product through its entire lifecycle, you may also hear this referred to as building ‘long-lived teams.‘ That’s because with YBIYRI, gone are the days of short-term delivery teams, as team members manage everything, including the scoping, DevOps, live traffic, production support, and eventually, the decommissioning of the product.

YBIYRI is an operating model that’s grown since Wener Vogels, CTO of Amazon, developed the concept in 2006. Here are his views on why it’s so effective.

Giving developers operational responsibilities has greatly enhanced the quality of the services, both from a customer and a technology point of view. The traditional model is that you take your software to the wall that separates development and operations, and throw it over and then forget about it. Not at Amazon. You build it, you run it. This brings developers into contact with the day-to-day operation of their software. It also brings them into day-to-day contact with the customer. This customer feedback loop is essential for improving the quality of the service.

This model is especially popular with organizations looking to create new services, manage real-time operations, and drive automation within lean, agile teams. It’s also more engaging for the dev teams themselves as they get to work within cross-functional teams with a variety of specializations. 

The Benefits – Efficiency, Incident Management, and Code Quality

There’s a reason that YBIYRI has grown in popularity across IT departments everywhere, and that’s because it generates tangible value within their organizations. 

Let’s look at three of the key benefits of You Build It You Run It:

• Efficiency – Rather than delivery and operational teams handing over code, documentation, and knowledge, long-lived teams own and manage the product from start to finish. That makes development, deployment, and service management faster, with synergies between continuous delivery and operations easier to achieve thanks to a fast feedback loop.
• Incident Management – Because on-call product teams know the system inside out, they can resolve issues faster from initial notification to full incident resolution. This knowledge helps reduce downtime, improve application operability, and build reliability and trust between IT and business operators.
• Code Quality – By making development teams responsible for the full lifetime of the application, they have skin in the game. This ensures the quality from the product team is top-notch, which improves the chances of delivering what customers want, reduces the number of defects, and helps accelerate and automate processes.

Read also: The Complete Guide to Agile Project Management

The Drawbacks – Cost of Change, Re-Training, and Competing Priorities

But like with all operating models, You Build It You Run It isn’t without its faults – after all, there’s no silver bullet when running a successful IT department. 

If you’re considering YBIYRI, here are some of the drawbacks to consider: 

• Cost of Change – Like any big organizational change, you need to consider the costs if you want to move from the traditional model to YBIYRI. Not only will you need to make some people changes, but you may also need to make changes to your infrastructure, including decommissioning and decoupling certain applications. Depending on the extent of the change, you may also need to bring in external teams, such as agile coaches or product owners, to guide the transformation.
• Re-Training – As you transition, developers’ experience will be dominated by re-training, upskilling, and cross-skilling. As teams become responsible for new things, you may need to re-train them in areas such as AWS, cloud infrastructure, a new toolchain, or even new development languages. 
• Competing Priorities – Long-lived teams must constantly choose between building new features and keeping the lights on. This can cause the pipeline to become delayed, high amounts of rework, or a bottleneck in production as teams get pulled by different priorities.

3 Questions To Help You Understand If You Build It You Run It Is Right For You

So, now that you know all about YBIYRI and its positive impact on platform engineering and digital services teams everywhere, it’s time to decide if it’s right for you. Trying asking yourself these three questions to help figure that out: 

1. Do you currently have high incident volumes? Teams that operate YBIYRI often see fewer incidents, as the model helps them detect, resolve, and fix incidents faster by retaining dedicated knowledge in the team.
2. Do you struggle to deploy working software regularly? If that sounds like you, there’s a chance that your DevOps engineers aren’t following a continuous deployment roadmap. You Build It You Run It can enable that by bringing the entire software environment together in one place. 
3. Is there a conflict between your delivery and operations team members? This is super common across all IT departments, but it doesn’t need to be that way. With YBIYRI, everyone forms part of one super team that’s packed with autonomy, harmonized working, and full lifecycle responsibility.

If you’ve answered ‘yes’ to any of the above questions, the YBIYRI model could well be right for you. This is especially true because the model can come in many different shapes and sizes depending on your organization. This could start with a small team of agile practitioners (e.g., a single product team) or scale up to a full, self-service DevOps capability.

Read also:

• The Guide to Project Management Tools for Software Development Teams
• Remote team management in Scrum

To Wrap Up…

YBIYRI is fast becoming the guiding philosophy for IT and product teams everywhere. While there’s no single playbook for delivering great software, teams that share the responsibilities for both delivery and operations see benefits such as increased efficiency, improved code quality, and an ability to respond to incidents faster.   

If you want to take your software development capabilities to the next level, you need an IT Services advisor you can trust. At Inetum, our specialized advisory services are personalized to your vision as the CIO, covering everything from digital strategy to operational reality, with experts here to offer guidance every step of the way. 

Elevate Your Application Development

Our tailored Application Development services meet your unique business needs. Consult with Marek Czachorowski, Head of Data and AI Solutions, for expert guidance.

Schedule a meeting