Designing a data strategy that delivers value

The first step in any data initiative is developing a strategy. What are the key considerations?

Many across the private, public and third sector believe that leveraging data is the domain of ecommerce giants, retail businesses with deep pockets, or tech firms with Silicon Valley muscle. Yet in an age when innovation is fast being commoditised, data science can now offer incredible and achievable benefits to any organisation. The first step involves unlocking the value of data.

“Top executives in every sector realise that they sit on lots of data, however, utilising it can seem daunting. Creating a data strategy is the first decision. This is about laying the foundations for data empowerment. It’s the beginning of a journey and the most important call to make,” explains Giles Horwood, managing director of Simpson Associates, a leading UK data analytics consultancy, with over 30 years’ experience.

However, many organisations experience inertia in any push to become data-driven. Concerns around skills, developing processes, technology delivery, budgets and uncertain outcomes stymy investment, but these roadblocks can be overcome.

“The big issue is how to get going. With a short, sharp assessment, you can understand where you are when it comes to data maturity. It doesn’t need to be a long-drawn-out process. But any data audit needs to be methodical, working out what’s valuable and what’s not. What this starts to do is generate an organisation-wide conversation about data, which is a crucial step,” details Horwood from Simpson Associates, which works with a vast range of organisations including the Natural History Museum, Barratt Developments, UK police forces and the Royal British Legion.

Starting small and then scaling matters. Every organisation must show early wins and ROI when it comes to data-science projects

There are misperceptions that unlocking the value of data is eye-wateringly expensive and all encompassing. In many cases, today, a data science, proof-of-concept can be easily rolled out within weeks, not months. This can also work on discrete data silos and use cases. Results can be achieved quickly, demonstrating a return on investment.

“If you get your data strategy right from the start, you can deliver value rapidly and efficiently. Eighty percent of data science involves preparing the data. Having a foundation and methodology in place, knowing where you are, what you need and how you get there, is vital. This then unlocks the potential for any use case whether it’s machine learning, artificial intelligence or data analytics,” states the managing director of Simpson Associates, which is a Microsoft Gold partner, holding four gold competencies in data and business intelligence.

Demonstrating initial gains with a data strategy is important. It draws people, processes and culture into the equation – after all, valuing data is a change-management issue, but it requires a strong framework to drive it forward. The right questions need to be asked, while knowledge and experience is needed to articulate what ‘good’ looks like.

“It is crucial to understand how to get the best out of your data otherwise any strategy will fail. That is why we deploy a robust data-maturity assessment. Understanding what the best use cases are in that industry, the market environment and how that sector values data is also crucial,” says Horwood from Simpson Associates, which has recently earned the Great Place to Work Certification.

“Starting small and then scaling matters. Every organisation must show early wins and ROI when it comes to data-science projects, which can then be championed internally for further digital-transformation projects. It also opens up the potential for valuing data in new ways from boosting productivity to monetising data-led services. In the current economic climate, there are efficiency gains to be made using data to do more with less.”

“There’s so much potential. We’re only just getting started,” states Horwood.

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