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#25 TOP3 mistakes in starting data strategy

Today is the time to share the TOP3 most common challenges that the most of our +100 customers we met have faced first when starting their data business. There are certainly other challenges that are often encountered, but in general, we can say that by avoiding and actively reducing these subsequent challenges, we will very often have a better chance to success.

The first challenge is purely business. In fact, only those companies that have led the data business or data strategy utilization initials from the company’s top management have succeeded in generating a visible impact on the business. Where top management has proactively taken on a greater role immediately in calculating, managing, measuring, and resourcing the business impact of a data strategy, the success rate has multiplied. At the same time, this means that before engaging the technology team, management has already formed a vision for the value creation and investment of individual use cases, as well as the payback period.

Another major challenge is management at too high or general a level. An overall data strategy and data business consists of individual components and sub-implementations, each of which is an individually measurable, concrete implementation, each of which is part of a strategy. Without a practical plan and measurable functions, a data strategy will never take place. An example of this can be a very important step data modeling, i.e. designing a data model from a customer perspective. When a customer-driven data model is modeled from a 360 view, customer data will be modeled to include all customer information such as billing, purchases, customer feedback, marketing, support requests, roaming, and more where an individual customer can be identified. By modeling all customer data into this data model, a competitive factor is reached, from which the customer's willingness to pay, willingness to buy or customer churn can be predicted. If implementations like this are not defined at the core of the data strategy, the overall implementation will often remain just talk. Disassemble the data strategy in the management team, try to understand the key components and what needs to be resolved first in order to quickly achieve value creation and capture.

The third major mistake is to purchase key parts of the data strategy from IT suppliers due to your own resource expertise, resource availability, urgency, or provided references, but is a very poor approach due to the life cycle of the strategy. Individual implementations of a data business or data strategy can be purchased from outside or ordered on a turnkey basis, but the management of the entire strategy, to suit your own business environment, the implementation of vendor-locked operations and choices must be able and made by your own management, even with the help of consultants. Virtually all data strategy projects outsourced from the first steps have had to be transformed over a few years due to silage-like and expensive implementations. So lead yourself up close and active right from the first steps.

As you can see, none of these challenges are technical or technological but completely management challenges. From this point of view, I would say that technologies, consultants and know-how can always be purchased outside, but the best management of your company must be harnessed first.


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