Getting started with data - many organisations want to and do this in one way or another. That seems sensible, but is it? Is working with data the same as data-driven work? And does just starting with it not lead to disappointments?
Definition
Data is a broad concept, and so is working with data. At its core, it is about making evidence-based decisions or distilling signals about opportunities, threats or anything else from combining data. In other words, data is often the starting point of entrepreneurship. It triggers critical reflection, or provokes new insights. Data and data analysis are methodical. It is therefore a means and not an end. All together, this means that data-driven work must be embedded to add value to the organisation.
Conclusion? We all work with data in one way or another - data-driven work goes much further and requires a well-considered plan.
'Data-driven work should contribute to better decisions in business operations. These are often precisely small things. Not everything stems from a lofty analysis around a strategic topic. The day-to-day gains are often to be found in the small things.'
Prerequisites
The primary requirement for data-driven work is that your data is in order. Once the data is in order, with data analysis you can often take the same decisions much more easily and in any case with factual substantiation. With a visually attractive dashboard you get a tool in hand to work with results instead of compiling an error-prone spreadsheet. This tooling is not only interesting for specialists - also the management team or - perhaps especially - the commercial people within the organisation. The dataset underlying the dashboard is after all the same for everyone. The whole organisation looks at the same truth!
And while we are at it: how great is it when the dashboard - read: dataset - is linked with that of colleagues from another department, or from another country? Suddenly you see that you can better arrange the shelves/aisles in your logistics centre based on order lists from sales. Or that your colleagues in Spain need help purchasing a certain raw material because you do it more cheaply. Working with data regularly delivers remarkable insights.
In short: it starts with better substantiation of decisions you currently take based on learned knowledge and experience. With data-driven work you add the data present in your company to that!
Objectives
Besides data quality, it is important that the purpose of data is clearly understood by everyone, otherwise you risk colleagues seeing data-driven work as a threat. Besides keeping the goal sharp, it is also essential to actually develop data products that are needed. So not because the data happens to be there. Sales already know perfectly well that parasols sell better in summer than in winter. But do they also know when and how to start the parasol clearance sale, taking into account current stock and price elasticity?
Is your best-selling product also 'shipping costs'?
However, be careful about involving too many data sources simultaneously in your decision-making. It is essential to understand the data well before drawing all sorts of conclusions.
Soft skills
Datalab knows how organisations can get started with data. Technology and training are important, but planting the data-driven mindset in the DNA of organisations is at least as important.
Want to know more? Get in touch with us and discuss the wishes and possibilities. Free of charge, of course.