Three main issues
In our work at Royal HaskoningDHV, we often see our clients struggle with three main issues when it comes to becoming ‘data-driven’.
1. Maintaining a view of costs and benefits
If the goal of becoming data driven remains an abstract idea, then other topics will inevitably take precedence. After all, there are lots of competing subjects of discussion and areas for investment within an organisation. And time, resources, and the attention of management is limited.
Therefore, it’s important to have a concrete idea of what your data initiatives mean in practice – including, above all else, what benefits they will provide and what it will cost to achieve them.
2. Overfocusing on enablers
We also often see organisations focus intently on a single aspect of data transformation. For example, establishing a data management organisation, or building a data infrastructure. This is fine, but only if you remember to keep your larger goal in mind at all times.
A data management organisation or a data infrastructure is just a tool or enabler that make it possible to realise certain benefits. But it can be easy to overinvest in these things. Instead, you should set up only what is necessary to achieve your immediate goals, and then scale up when you find success. Too much focus on enablers alone could put you under constant pressure to explain the value they will add. And if that value doesn’t materialise quickly enough, you may find the plug pulled from your project. To be successful, therefore, it’s important to have an understanding of your costs and benefits, and ensure that investments never run too far ahead of their returns.
3. Not focusing on tangible results
Focusing on tangible results from the start can help transform data-driven working from being an abstract concept to a real and achievable thing. To do this, you need to avoid generalities and begin by choosing a specific application of data. This application should be derived from your overall business strategy.
And again, this process should be incremental. Start with a minimum viable product (MVP) to test whether the theory behind your application works in practice. Then build on this.
At the beginning of this process, your primary goal should be to increase the knowledge, awareness, and understanding among all stakeholders. Then, when stakeholders see concrete results, they will likely conceive new business applications and will be prepared to invest more. In many cases, this leads to a greater legitimisation of data processes, and can result in the implementation of structural solutions, like data management organisations and data-centric architectures.
If you’re organisation is struggling to take its first steps into a data-driven world, or if you’d just like some advice or guidance, we can help to assess your situation and choose the right approach for you. To find out more about how we can help, get in touch.