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Create business value from data: increase sales revenue and EBITDA, make the company more efficient and improve work efficiency. Great-sounding buzzwords, but how can a production company or a service provider achieve that the data collected by operators and administrators can bring a demonstrable benefit like in the books?
In recent years, more and more middle managers have realized in their field how data efficiency can be increased, and their teams’ working time can be spent on higher value-added tasks instead of repetitive, automated activities. At Hiflylabs, we have firsthand experiences about the process, as we have been helping these changes for over 20 years.
However, the initiatives largely stop at the local levels, there is no comprehensive corporate concept behind them, we have also met countless times that one and another department of a large company approached us independently with the idea of different Business Intelligence solutions.
These local, i.e. bottom-up initiatives can be very effective, boost employee satisfaction, optimize, and in most cases make the department measurably more efficient, but most large enterprise units do not operate on their own, but together with other business units as part of a corporate stream. Think of a simple purchasing process where the customer sends their order to the purchasing and then the purchasing, after making its own modifications, forwards the data to manufacturing or invoicing and so on, a complex corporate data stream is built with plenty of channels.
More and more corporate executives and boards have recognized that it is more worthwhile to look at this data stream as a whole, meaning that there should be a role that can handle these processes end-to-end. He/She is also able to facilitate local discounts, transfer best practices to other units, and exploit the potential of an organization’s data assets. This kind of demand has created one of the youngest executive positions in large corporations, namely the Chief Data Officer (CDO).
Which are the tasks that should be managed and supported centrally?
In the same way as with any other corporate position, , different companies, different cultures have defined different tasks and roles for the centralized data officer. In this section, we summarize the key elements that our experience and key players in the data industry consider to be the most important tasks to be managed centrally.
> Create a data culture: First and foremost, the company’s employees shall get to know the data-based culture* and its significance. This means not only a change in mindset or fixing entrenched habits, but also transparent processes in which data is handled in a transparent way that is known to everyone, and colleagues understand the significance of their particular task at a later stage. (Related blog post: Indirect value of data projects)
> Improv data quality: Although improving data quality is not directly the responsibility of an executive-level leader, the definition of policies, the existence of return measurement systems, and the definition of expectations fall into this category. That is, a CDO cannot be expected to have the right quality of HR data, for example, as this is the responsibility of the business leader, but it is the CDO’s job to have a definition that tells you what is right and a policy that tells you how to achieve that.
> Eliminate data territorialism and promote data ethics: Once we have a good (or less good) data asset and colleagues understand the potential of enterprise-level exploitation, it is up to the CDO to make it available to professionals. Have a central data storage unit** where data from different organizational units can be linked. It should be emphasized here that, in addition to data that spans an organization, metadata is also of paramount importance, think only of data integrity issues. It is important to know which data reached the end-user, in what way, with the help of which transformations and calculations the given KPI was created, from which system the source data came, who last edited it, etc.
> Data interpretation: Our company has worked on numerous data science projects in recent years, and if a single key lesson was to be named based on these projects, it would certainly be related to data interpretation. If we do not understand the basic contexts and behavior of the analyzed area, we can use any complex data analysis model, but we will not be able to draw reliable conclusions. That is, it is not enough to make the data available and traceable, we need to help colleagues understand it. Providing the opportunity to understand data is a cross-organizational activity, so this is clearly the responsibility of the CDO.
> Promote self-service solutions: Once we have an available data asset, which we understand, we have an opportunity to start our analyses, without involving colleagues who create reports and dashboards, or with minimal help. Experts in each field have such in-depth knowledge of their field that a data analysis expert rarely acquires. That is, if a CDO seeks to exploit data assets, it is certainly in its best interest to present some data analysis methods and tools to experts in each field, who can easily come to terms with deeply hidden relationships by combining their years of expertise with a suitable tool.
> C-suits partnership: As we will see later, in contrast to the name of the CDO, in many cases he/she is not at the level of C-managers in the corporate hierarchy, yet there is a definite need for coordinated work between her/him and the other managers. Because of his/her purpose, he/she is a cross-domain organizational unit, so he/she can help other managers achieve their goals and work in a coordinated way between different units (e.g., between finance and marketing, etc.).
> Promote data ethics: In data circles, it may not be necessary to mention, but recently in the wake of several cases (Facebook, Cambridge Analytics) the ethical use of data has come to the fore. If you have a central data officer, it is definitely his or her responsibility to take steps together with information security professionals to prevent data misuse.
As can be seen from the above, the role of the CDO is fundamentally not specific to the SME sector, but rather plays an important role in a large corporate environment. In a data-driven future, for many companies, these tasks and responsibilities are not concentrated in the hands of one person but belong to other roles. Continuing the series, we examine where these tasks typically end up within a company, if there is no central CDO – if they end up somewhere at all -, and if there is a CDO, where they are located in the organization. We also provide an overview of current Hungarian CDOs (or people with different names/positions but similar responsibilities).
*if you are interested in what we mean by “data-based culture”, let us know in a comment and we will write a post about it
**of course we are talking about a theoretical unit, not physical systems