Data maturity: the strategic perspective.

This is how we understand the strategic perspective:

In order to develop Advanced Analytics within a company in the long term, the topic needs to be given an appropriate place in the strategic considerations of a company. We distinguish between two aspects: the strategy and the maturity of the organization. To ensure that the topic of Advanced Analytics is clearly defined, companies need the organizational prerequisites to bring the strategy to life. The strategic perspective thus links planned approaches and initiatives with the actual capabilities of the organization. One dimension cannot be developed efficiently without the other: Planning remains vague if it cannot be implemented; conversely, implementation without strategic planning is rarely effective.

If Advanced Analytics is not anchored in the organization, even the best strategy will not lead to any improvement. However, Advanced Analytics cannot be anchored in the organization without a long-term vision of how competitive advantages can be achieved through the targeted use of data.

The relevance of the strategic perspective – with room for improvement

If one looks at the study results in detail with regard to strategy and organization, it becomes clear that only very few companies consider data to be an important strategic parameter of the organization.

Although 29.2% of the companies state that Advanced Analytics is important to them, at the same time only every fifth company has a central unit that supports data-driven decisions and anchors them in the company. Only 8.1% of the companies use data to further develop offers and their own company. 

It can be seen that data is still being neglected in the strategic considerations of companies – a real strategic anchoring of the topic only occurs in a minority of companies.

The organizational side of Advanced Analytics  

As described above, (often abstract) strategic considerations require an integration with the organization – i.e. its capabilities, structures and responsibilities – in order to implement real data-driven applications.

In our study we were able to show that almost all employees of the surveyed companies (85.1%) have at least gained initial practical experience with the use of data. Nevertheless, the transfer to the organization is not yet successful – less than 10% of the companies manage to gain an entrepreneurial advantage through the use and analysis of data.

Rookies and pros – strategy makes the difference

One of the central findings of our study is that there are two groups of companies in terms of data maturity: Rookies and Pros. Rookies usually already collect data but do not integrate it into their processes. Pros, on the other hand, are particularly well positioned in the dimensions of strategy, processes and technologies. 

The chart shows that the differences are greatest in these dimensions.

It is therefore not primarily a question of technology or data, but of a stringent approach. In order to become a truly data-driven organization, it requires a clear vision and planning, the necessary resources and clear responsibilities when it comes to data, as well as processes that help to transfer the findings into the organization. Many companies make the mistake of looking at Advanced Analytics from a purely technical or data perspective. In order to establish truly successful data-driven applications profitably, clear planning is required that is oriented towards the specific requirements and challenges of your own company.

This is how the data strategy succeeds

Whether a data strategy is successfully implemented depends on whether the considerations promise concrete added value for the company and its employees – and whether the planned projects really fit the individual requirements. The first step is not to implement specific tools or to train employees in the area of data science: It is much more important to analyze where and how the company is already working data-driven, where it sees challenges and which use cases are desirable.

At Merkle, we have developed our Data Strategy to guarantee this fit. 

We work comprehensively but pragmatically in three defined project steps: an analysis, a vision phase and a transformation phase.

On the basis of the most important use cases, we develop your optimal target picture – from a technical, economic and customer-centric perspective. In doing so, we examine which requirements your company already masters and where there are still gaps. 

Finally, we identify the next relevant steps to close the gaps to your target image. In this way we ensure that projects are planned in such a way that they have the maximum effect and build on each other in a meaningful way. 

This is how your personal roadmap to a data-driven organization is created. 

Download the study today and request an assessment of your data maturity!