Insights
What I see in projects, the questions they raise, and what I learn from them.
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User experience
Why the customer journey often gets lost between tools, and how to find it again
A customer rarely goes through a single touchpoint before buying. They visit the website, open an email, call customer service or return through social media. Each step leaves a trace in a different system. The problem is not a lack of information about the journey, but the fact that it is scattered across systems that do not communicate well enough.
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Business analysis
Why a clear requirements document saves time for the whole team, not just IT
A requirements document is often seen as a technical document, mainly intended for the team that will build the solution. In reality, it is first and foremost a tool for creating clarity. A clear requirements document helps business teams articulate what they need, the technical team understand what it has to build, and management weigh priorities before decisions become costly to change.
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Automation
Why an automated process needs to be understood before it is built
When faced with a slow process, the temptation is to jump straight to the technical solution. Write the script, connect the systems, deliver quickly. This approach rarely works first time and often costs more than expected because an essential step has been skipped: understanding the real process before turning it into an automation.
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User experience
What digital marketing and business analysis have in common, from both sides of the equation
Marketing and business analysis are rarely considered together. One seems to belong to the world of creativity and customers, the other to processes and rigour. In practice, both disciplines address the same fundamental question from different angles: understanding a real need before proposing a solution.
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Applied AI
Why keeping a human in the loop isn't excessive caution, but a condition for success
When it comes to AI in a business, human validation is sometimes presented as a temporary step, to be removed once the system becomes reliable enough to operate on its own. That view is too simple. For tasks that can have consequences for the business, keeping someone able to check, correct or take over is part of the system's design, not just a feature of its early stages.
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Applied AI
What AI can genuinely do in an SME today
Artificial intelligence is part of almost every business conversation, yet few companies know exactly what it can do for them today. Between the claims that promise to automate everything and the caution that leads companies to do nothing, there is a more practical middle ground. It is narrower than the promise, but already useful for certain types of business work.
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Data management
The difference between having data and having usable data
Many organisations think they lack data when they already have a great deal of it. The problem is not necessarily the absence of data, but its condition. Information exists, but it may be poorly structured, inconsistent, difficult to access or too old to be useful at the right moment. That distinction completely changes the nature of the work required.
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Automation
How to recognise a task worth automating, and one that isn't
Not every repetitive task is worth automating. Some take time, but happen too rarely, vary too much or are too complex to formalise to justify the investment. Others could be automated, but only after simplifying the process around them. Knowing the difference helps avoid spending an automation budget in the wrong place.
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Business analysis
Choosing a CRM: 5 questions to ask before comparing tools
Comparing CRMs based on their features is a step that comes too early in most projects. Before opening a comparison table of tools, a few internal questions can clarify what the organisation actually expects from the future system. This helps avoid choosing a solution that does not fit the organisation's reality, however good it may look on paper.
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Applied AI
AI project in business: 8 questions to ask before you start
An AI project that starts with choosing a tool often starts on the wrong foot. Before comparing technical solutions, eight straightforward questions can help establish whether the problem is genuinely suited to AI, whether the necessary data exists, and whether the organisation is ready to test a solution under the right conditions.
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Data management
Why your reports contradict each other, and how to fix it
Two reports meant to measure the same thing sometimes give different numbers. The problem does not necessarily come from the calculation itself. It often comes from the definition: two people, two teams or two tools are not measuring exactly the same reality, even when they use the same word to describe it.
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Business analysis
What separates a good user story from a bad one, with concrete examples
The user story has become a common way of describing a need in a digital project. Its simple structure, "as a, I want, so that", hides a real difficulty. A user story can follow that structure perfectly while still leaving much of the need open to interpretation. The questions then surface during development, when decisions are more costly to change.