Digitalization is on the agenda in every business and includes everything from digitalizing documents to developing new products and services through intelligent collection of data and advanced data analytics. But what defines an ambitious and explorative data project and what does it take to succeed?
The range of digitization projects is broad. Therefore, it's important to be aware that not all projects are alike, and they need different degrees of focus. There are very different requirements for how a data project should be implemented, depending on where on the Data Maturity Curve the project is positioned.
A data project with a well-defined business assignment, is easy to understand and has a broad acceptance from the employees. In such a project, only some degree of leadership involvement is necessary as well as a minor transformation in the organization when the solution is implemented.
However, it's a different game when projects set off in new business ideas. There are high ambitions and curiosity to use data intelligence in developing new services, products or workflows. Companies spot new business opportunities without being fully able to define these. In this case, there is a need to launch an explorative data project.
Businesses achieve better project performance and faster return on investment when explorative data projects are thought through to completion from the very beginning.
An explorative data project must be in line with the company's strategic focus. Especially when the project outcome is expected to have an impact on the company’s core products, services, and processes. It will require an intensive transformation in the business to take on the solution and top management involvement and explicit support are essential to succeed; from start to end.
The project's purpose and results will most likely change during the course of the project. Therefore, the project should be monitored closely. When the partial results during project development take a different direction than originally planned, new decisions must be made. This isn't necessarily a problem as long as it follows the company's strategic direction. During the process you will gain information, you thought was impossible to gain, and you will experience that you can't gain the information, you expected to gain.
Not all explorative projects should be implemented. If the project - despite updates in purpose and expectations to outcome - can't create the expected business benefits, the project must be closed down. It shouldn't be seen as a failure. You have become more experienced in working with data projects, have gained more insight into what data you have available and what purposes it can be used for. Like any other product development initiatives, not all ideas should be carried into effect.
Choosing the right resources makes a difference. By choosing the right competences for the data project, you generate the necessary foundation for being able to produce results with high quality. If the right resources aren't available, you should wait or reconsider your priorities. Choose the right data partner if your company doesn't have Data Science competences available. The right mix of competences in the project team has a significant impact on the result.
The transformation is what releases the business benefits. Just as a good project result is within reach, the risk of not achieving the expected benefits is present. There is a need to invest in the necessary transformation required for new products or services to be effectively incorporated in the business. As for example, the sales force may need to have a deeper understanding of the product to trust it and thereby be able to sell it. It may also be that the solution entails new work routines in production. In all cases, adjustments must be made. The result is just as good as the weakest link.
Try to think the data project to an end. Consider the potential directions that may evolve. Companies achieve better project performance and faster profits if the possible outcomes of an explorative data project are thought through before launching the data project. Consider the limitations and challenges that the project encounters in implementation as well as the directions one can imagine that the new product or service can take along the way - and still be relevant. This exercise supports business management to have realistic expectations to the project and be able to make the right decisions as the project evolves. This doesn't compromise the agile approach in the project execution.
THE STRENGTH LIES IN THE PERSONAL MEETING
Do you have an urge to discuss the starting point for your upcoming data project, contact Birgitte Dahl.
ABOUT Rooftop Analytics
Rooftop Analytics has solid experience in implementing solutions based on data and algorithms with significant business value. We understand the prerequisites for succeeding and finding the solution, which best matches your company's needs. We offer our competences for establishing and executing the project as well as for the relevant business transformation. We are happy to take on the role as project manager in close cooperation with your company.