Why your data strategy ends up gathering dust
The gap almost everyone recognises, but few manage to bridge
- Article
- Strategy & Transformation
Most data strategies do not fail on paper, but when it comes to putting them into practice: in the gap between the ambition set out in the boardroom and what the organisation actually does with data on a day-to-day basis. This is the first article in a series of articles about how to enable successful SME transformations.
Sound familiar? After months of workshops, interviews and PowerPoint presentations, you finally have a data strategy on the table. Professionally designed, ambitious in tone and backed by management. And then… not much happens.
Data products fail to get off the ground: dashboards go unused, predictive models never make it into day-to-day operations, and the energy that went into developing the strategy gradually fades as everyday priorities take over.
This is far from unusual. We see it time and again among leadership teams and transformation managers who are serious about making better use of data. Not because they lack ambition. Quite the opposite. The problem lies elsewhere: in the gap between what the strategy promises and what the organisation is capable of delivering.
This gap has two dimensions:
- Awareness (the strategic understanding and leadership needed to make data-driven decisions)
- Ability (the organisation's capability to put data to work in practice).
We'll explore both in greater detail using the A2 Matrix as part of the baseline assessment in article 3, which we’ll publish later on.
Research highlights just how significant this gap is: only a quarter of organisations perform strongly on both dimensions¹. And among hundreds of organisations studied, just 38% possess the digital capabilities and 35% the leadership capabilities required for genuine transformation².
The urgency has never been greater. Dutch SMEs are among Europe's frontrunners when it comes to AI ambition. The question has shifted from 'Why data and AI?' to 'Where's the value?'. Organisations that fail to turn their strategy into action risk falling visibly behind.
In this article, you’ll discover:
- why data strategy initiatives stall
- which patterns we encounter most often
- what organisations that succeed consistently do differently
We won't start with technology or architecture. We'll start with the question that really matters: What's standing between our data strategy and real business value?
More data ≠ more value
Many decision-makers assume the solution to their data challenges is simply more: more data, more tools, more dashboards, more analysis. We invest in a modern data platform, expand the data team, build a data warehouse and expect everything else to fall into place.
But data only creates value when people actually use it. And people use it when they understand what's in it for them, when it fits into their everyday workflows, and when someone takes ownership of the outcome.
Research into big data and strategy points to the same conclusion: large volumes of data and advanced technology only deliver a return when they're supported by a clear strategy and the organisational capabilities needed to put them to good use³, ⁴.
At its heart, the problem isn't technical. It's human. And that's precisely why a successful data strategy requires more than sound architecture. It requires clear answers to three questions that organisations rarely ask upfront:
- Who is accountable if it doesn't work?
- How will we know in six months whether we're on track?
- What specifically needs to change in the way people work every day?
The four reasons data strategies stall
From our experience working with SMEs, four recurring patterns explain why data strategies lose momentum.
1. Unclear objectives
The strategy sets a direction, but doesn't define the desired outcome. 'Becoming more data-driven' isn't a goal; it's an intention. Without concrete, measurable outcomes, organisations lack the clarity needed to prioritise initiatives and make decisions.
2. Fragmented initiatives
A data strategy rarely translates into one coordinated programme. In practice, there are often ten initiatives running in parallel, with little communication between them. They compete for attention and resources, pulling the organisation in different directions at the same time.
3. Lack of buy-in beyond the data team
Data initiatives often originate within a central team. But the value needs to be realised across the wider organisation. If other departments aren't involved early enough, they're unlikely to see the initiative as their responsibility.
4. No visible results in the first 90 days
If nothing changes for people outside the project team during the first few months, confidence starts to fade. Successful transformation programmes deliberately build in early wins. Not as a PR exercise, but as tangible proof that change is possible.
What successful strategy and transformation programmes do differently
They don't start with technology. They start with a diagnosis.
This diagnosis looks at both the technical and human barriers within the organisation. The accompanying Transformation Diagnosis Canvas helps you assess both aspects across the dimensions of Awareness and Ability (more on this in Chapter 3).
Successful transformation managers focus on one specific bottleneck within a single team or business area and demonstrate what's possible there. Crucially, they assign ownership to people, not systems.
This is an article by Elias Hassing
With a background in product management and over 15 years of experience leading international development teams, Elias helps organisations develop their data strategy. With his expertise in product development and experience as Head of Product at companies such as Coolgradient and Infinitas Learning, Elias guides digital transformations from strategy to execution.
Principal Data Strategy Consultantelias.hassing@digital-power.com
This is an article by Guus van Loon
With more than 10 years of experience in data, strategy and innovation, Guus helps organisations turn complex ambitions into sustainable business value. As Head of Research & Development at a market research scale-up, he worked on strategic challenges for international clients. He is a valuable bridge between technical specialists and business stakeholders, as well as a trusted adviser to senior management.
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Sources:
1. Westerman, G., Tannou, M., Bonnet, D., Ferraris, P. & McAfee, A. (2012). The Digital Advantage: How Digital Leaders Outperform Their Peers in Every Industry. MIT Center for Digital Business & Capgemini Consulting.
2. Bonnet, D. & Westerman, G. (2021). The New Elements of Digital Transformation. MIT Sloan Management Review, 62(2).
3. Mazzei, M.J. & Noble, D. (2017). Big Data Dreams: A Framework for Corporate Strategy. Business Horizons, 60(3).