How do you build a data strategy tailored to your organization?

There is certainly nothing new about organizations using data, but we have come a long way. Initially, companies gathered data from various systems in a data warehouse. The drawback being that the data management was handled by a central team and the turnaround time of reports was likely to seriously  run up. Moreover, these data engineers needed to have a solid understanding of the entire business. Over the years that followed, the rise of social media meant the sheer amount of data positively mushroomed, which in turn led to the term Big Data. As a result, tools were developed to analyse huge data volumes, with the focus increasingly shifting towards self-service.

The latter trend now means that the business itself is increasingly better able to handle data under their own steam. Which in turn brings yet another new challenge: as is often the case, we are unable to dissociate technology from the processes at the company or from the people that use these data. Are these people ready to start using data? Do they have the right skills and have you thought about the kind of skills you will be needing tomorrow? What are the company’s goals and how can employees contribute towards achieving them? The human aspect is a crucial component of any potent data strategy.

How to make the difference with data?

In practice, the truth is that, when it comes to their data strategies, a lot of companies have not progressed from where they were a few years ago. Needless to say, this is hardly a robust foundation to move on to the next step. So let’s hone in on some of the key elements in any data strategy:

• Data need to incite action: it is not enough to just compare a few numbers; a high-quality report leads to a decision or should at the very least make it clear which kind of action is required.
• Sharing is caring: if you do have data anyway, why not share them? Not just with your own in-house departments, but also with the outside world. If you manage to make data available again to the customer there is a genuine competitive advantage to be had.
• Visualise: data are often collected in poorly organised tables without proper layout. Studies show the human brain struggles to read these kinds of tables. Visualising data (using GeoMapping for instance) may see you arrive at insights you had not previously thought of.
• Connect data sets: in the case of data sets, at all times 1+1 needs to equal 3. If you are measuring the efficacy of a marketing campaign, for example, do not just look at the number of clicks. The real added value resides in correlating the data you have with data about the business, such as (increased) sales figures.
• Make data transparent: be clear about your business goals and KPIs, so everybody in the organization is able to use the data and, in doing so, contribute to meeting a benchmark.
• Train people: make sure your people understand how to use technology, but also how data are able to simplify their duties and how data contribute to achieving the company goals.

Which problem are you seeking to resolve with data?

Once you have got the foundations right, we can work up a roadmap. No solution should ever set out from the data themselves, but at all times needs to be linked to a challenge or a goal. This is why ACA Group always organises a workshop first in order to establish what the customer’s goals are. Based on the outcome of this workshop, we come up with concrete problem definition, which sets us on the right track to find a solution for each situation.

The integration of data sets will gain even greater importance in the near future, in amongst other things as part of sustainability reporting. In order to prepare and guide companies as best as possible, over the course of this year, we will be digging deeper into some important terminologies, methods and challenges around data with a series of blogs.

If in the meantime, are you keen to find out exactly what ‘Data Mesh’ entails, and why this could be rewarding for your organization?