A data-driven organization is an organization that works according to the principle that policy and decisions are made on the basis of data. Data can consist of experience and professional knowledge, but also of facts and data that are collected during the execution of the organizational activities.
Policy, decisions and improvement processes are often mapped out ‘at the top’ of an organization on the basis of observations, years of experience or a gut feeling. But making a decision based on just these things can come with some risk.
We would prefer to make decisions (small and large) on the basis of complete and correct information.
An example of data-driven working is making organizational goals measurable. In this way, for example, it can be assessed whether a change has been successful or whether adjustments need to be made. Data-driven working takes the use of data one step further than just assessing goals at a specific point in time. This includes monitoring data such as facts and findings over shorter periods of time. This leads to real-time insights about the current state of affairs within an organization. This not only ensures that an employee can perform his or her work better and faster, but also that there is more coordination and agreement between different employees or even parties involved.
By working data-driven, you ensure that decisions and policy are substantiated by facts and information that are collected from the implementation during the process. Hard insights with regard to lead time, quality and costs can strongly substantiate or refute the gut feeling. This has the advantage that the quality of decisions and policy increases. This also ensures transparency and accountability: after all, it is known on the basis of which information a decision has been made.
“Organizations that want to be future-proof should work process-based and data-driven. Insight into the course and the execution of processes is required to base decisions and policy on facts and information from business operations.”
In addition to decision-making and policy-making, data-driven working also has fundamental advantages in day-to-day operations. When the right information is available to the right people at the right time within the organization, day-to-day operations can be performed more efficiently and less error-prone. The information required to perform an activity naturally depends on the organization. It is therefore important to map out the information need with both decision-makers and executive employees. In this way a complete picture is created of the required information. In this way, the executive employees enjoy a smoother process and the management of the required performance indicators.
To get an idea of the meaning of data-driven working in practice, we take a case of a liquorice factory as an example. There are complaints that the draft liquorice tastes too salty. A random sample indeed shows that the draft liquorice is too salty. The recipe is adjusted and the complaints about the too salty draft liquorice are reduced. If the aim of this improvement process is ‘less salty draft drop’, then the process appears to have been successful. The cause of the problem, however, was sought in the recipe, but perhaps it was one of the employees who calculated the salt in kilograms instead of grams. A sample only provides a snapshot, while a data-driven approach would lead to production information during the execution of the process. This makes it possible to provide employees with the right information at the right time, to monitor them continuously and to intervene when necessary.
An IT system that facilitates this data-driven approach is a ‘workflow management system’. You can read more about that in this blog.