- Flexibility comes from standardization
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- The best way to predict the future is to be its architect
- Controller and Pricing
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The tension between individual control and governance, resolved quite simply.
An article from Jens Ropers, trainer and partner of CA controller akademie
From the experience gained in the exchange with CFOs and heads of management, a clear trend emerges. The dynamic and complex environment in which companies operate today means that the potential of data and advanced analytics should be utilized and, at the same time, KPIs and control logics are changed more frequently than before. While management and business units demand flexibility and speed, IT (and often also controlling) focuses on compliance with data governance specifications and postulates standardization, data security and the single source of truth. This creates a considerable amount of tension that must be resolved satisfactorily.
Transparency and responsibility are the basis
Companies, that have successfully resolved this tension, focus on governance in their first step. For the questions of which governance-relevant content (at the current time) must be used by which addressees for which purposes, the required data elements are recorded and clearly defined in as granular a form as possible. All KPIs used are now composed of the predefined data elements, clearly defined again, and stored in a freely accessible glossary. The business units use the glossary and the available data elements together with the controlling business partners to “assemble” KPIs for new requirements. The process described and the associated collaboration are the responsibility of and regulated centrally in the Business Intelligence Competence Center (BICC), as are the standards and notation principles for data visualization. This ensures that there is complete transparency regarding all KPIs used in the company and how they are calculated, while complying with all internal and external specifications.
Closed loops and experimental fields become a success factor
If the existing data elements are no longer sufficient to generate the information required for controlling, rapid expansion should be the top priority in a dynamic world. For this to succeed, a closed loop can be used in the second step, within which the business units use extended data models and further analyses to generate new data elements and aggregate them into KPIs with their controlling business partners (supported by special data roles, if necessary) as part of a self-service approach. The cycle is based on the corporate structure and the different information needs present there. The starting point are the data elements of the company BI. These are used in downstream divisional BI and departmental BI where relevant. For specific and emerging requirements, individual data elements and KPIs are developed in the respective business unit. The crucial factor here is maximum transparency about all activities taking place and about all arising issues. This is ensured via the BICC, the composition of which should be geared for this. All data elements and KPIs newly created in the decentralized units of the company are fed into the corporate glossary and can thus also be used by all other business units, including the data structures and calculation logic. This closes the circle again.
Data literacy for managers ensures that the control really succeeds
Above, we described how quickly and flexibly new KPIs can be created that meet governance requirements. However, this says nothing at all about the quality of the obtained KPIs in terms of their management relevance. In view of the increasing complexity, it seems to make sense to closely involve the responsible managers in the development of the KPIs so that their experience and, above all, the latest assessments and expectations can be included. Of course, this principle has always applied. What has changed significantly in the digital age is the knowledge of what is possible with data and what is not.
This is why specialists and managers need data literacy, because for them, decisions based on a black box are not an option! The ability to deal with data in a planned manner and to consciously use and question it in the respective context is referred to as data literacy, which could be described as data competence. Even if the operational handling of data, its analysis and interpretation is largely reserved for controllers and data scientists, all those responsible for managing the company should be familiar with the data basis used for calculations and the underlying data structures and assumptions and should also be able to “ask questions of the data” based on their day-to-day business needs. Only in this way can relevant conclusions be drawn from the data and the path “From Data to Decision” be followed successfully.
Questions for Controlling
The following control questions can help you start a goal-oriented discussion in your company:
- Do you have a (virtual) organizational unit, such as a BICC, to discuss all governance and flexibility issues and determine the approach that fits your company context?
- Are all your KPIs clearly defined, is this definition regularly maintained, and is it available for all employees to view in a central location?
- Do you use something like the standardized data elements described here to aggregate different KPIs from it?
- Do you have full transparency of all activities and measures that are currently taking place as part of the development of KPIs relevant to management?
- Is there decentralized space for experimentation and could you imagine integrating it in the sense of a closed loop?
- Are there measures to create data literacy among all employees of the company?