data-driven company

When an Ambitious Data Intelligence Initiative Needs to Succeed

The data-driven business is on the agenda in most companies, addressing everything from digitalization of documents, to developing new products and services through intelligent data collection and the use of predictive analytics. But what defines an ambitious data intelligence initiative, and what does it take to succeed?

When a data intelligence initiative is ambitious; that is, when data science and the use of predictive analytics are included in the development of new products and services, then the complexity of executing the initiative increases. The effort to use the solution and obtain the necessary buy-in from employees, customers and partners is also critical and challenging to obtain.

The range of data intelligene initiatives are multiple. Therefore, it's important to be aware that not all initiatives are alike, and they need a different degree of focus. There are very different requirements for how a data intelligence initiative should be implemented, depending on where on the Maturity Curve the project is positioned. However, there are several significant factors that come into play and they should be identified before the initiative is launched.

Birgitte Dahl, CEO, Rooftop Analytics

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Businesses achieve better project performance and faster return on investment when the data intelligence initiative is thought through to completion from the very beginning.

Set the Right Framework for the Ambitious Data intelligence Initiative

An ambitious data intelligence initiative must be in line with the company's strategic focus. Especially when the initiative’s 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 initiative’s purpose and results will most likely change during execution. Therefore, the initiative 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 achieve.

Not all ambitious data intelligence initiatives should be implemented. If the initiative - despite updates in purpose and expectations to outcome - can't create the expected business benefits, the initiative must be closed down. It shouldn't be seen as a failure. You have become more experienced in working with initiatives, have gained more insight into what data you have available and what purposes it can be used for. Like any other product development initiative, not all ideas should be carried into effect.

Choosing the right resources makes a difference. By choosing the right competencies for the data intelligence initiative, 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 business data science competences available. The right mix of competences in the project team has a significant impact on the result - and progress to completion.

The transformation is what releases the business benefits. Just as a good 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 into 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 intelligence initiative to an end. Companies achieve better execution, and obtain the gains faster, if the initiative as a whole is thought to end before it is launched. From the limitations and challenges that the project can expect to face during implementation, to the directions one can imagine that the initiative can take along the way - and still be relevant. It does not exclude the agile approach in the project execution, but provides possible directions the project team can act on once it gets started.

THE STRENGTH LIES IN THE PERSONAL MEETING

Do you have an urge to discuss the starting point for your upcoming data intelligence initiative, contact Birgitte Dahl.