Why IT and business should join hands
In order to pursue successful data management, business and IT must work together and not in parallel. Nevertheless, these two areas still act antipodally in many companies. For many companies, this is precisely the starting point for developing and implementing their data strategy. Tragically.
After all, it would be ideal to finally carry out data analyses that also refer to the individual departments. Not just having to read columns of bare figures, but having visualizations that the specialist employees can use straight away. Not to experience frustrated IT that constantly has to process tickets for additional functions instead of being at the heart of the data management organization.
As highly professional and technologically sophisticated down to the last pixel as data analyses can be, they are simply not valuable without a business context. Without both parties on board, a data management strategy cannot work and the analyses produced cannot be used to create value.
Data management with a business context through trust and interdisciplinarity
Traditionally, this is still the case in the companies concerned: IT has data sovereignty, reacts to requirements and transmits these back in its own interpretation. This often results in habits such as reports that always look the same, a lack of interactivity and little room for interpretation. As there is only a narrow communication channel between the departments, specialist departments submit requests for modifications that are collected by IT, which has to work through them successively or reject them due to tool limits. Here again, IT takes on a very reactive role. Data silos and dividing lines dominate data analysis. This makes it rigid and inefficient.
In most cases, the decision is made at management level: the frustrated employees must finally work together. The first step is to clarify who the departments can turn to in terms of data management and data strategy. Structures and transparency must be created here. Fixed contact persons on both sides who know business and IT, clear processes and regular agreements are established so that interdisciplinary teams can be formed.
Data specialists from IT should not be perceived as bored reporting tinkerers, nor should business managers leave at the first key figure. Instead, mutual trust and open-mindedness should exist and be further encouraged.
As an interdisciplinary team, they first sound out who exactly needs the data analyses, what they are to be used for and what they are intended to achieve. This "start with why" approach is helpful for communicating effectively and identifying needs quickly.
An internal central data team represents an increase in interdisciplinarity. It acts as an internal service provider that takes care of communication with the specialist departments and their requirements and translates them into data analyses. They are also often the bridge between specialist departments and the "traditional" IT department.
Optimizing discovery for successful data management
Data can only be placed in an overall corporate context through continuous exchange. During value-adding data discovery, the specialist departments are involved right from the start. They add their departmental knowledge and requirements to the data expertise. Which data records are recorded when, where and how? How do they need to be put into context? If the machine is producing, what data does it store and why? If the marketing department is planning a campaign, what data does it purchase externally? If the web analytics tool tracks user data, what can it be used for? This data needs to be explored and contextualized to provide results and insights.
To achieve this, the data silo of closed IT systems must also be broken open. If access is restricted or interfaces are missing, this makes handling data almost impossible and does not inspire confidence. For employees to be able to work with data more autonomously and on their own responsibility, they must first be allowed to use it.
Columns of figures and uninformative reports only become targeted reports, forecasts and decision-making aids when the teams' trust in each other and in the data is strengthened. This has a major impact on value creation. After all, data analyses can then be incorporated into processes in order to make well-founded decisions based on measured data.
"Data driven" down to the last team member
Including the business is a key component of a data-driven corporate culture. The creation of such a culture is a process that begins with the accessibility of data and ends with the supportive involvement in important departmental or company decisions. Ideally, data forms the basis for all company decisions in a natural, motivating and ambitious way.
The lack of collaboration and data silos in particular mean that there is little trust in the data and its use. A so-called "data-driven culture" is either not practiced at all or only inadequately. This would significantly help to recognize data management as a normal and valuable part of work. By educating and integrating every single team member throughout the company, an awareness of data and its importance can be created. Open discussions, recognizing needs and taking them seriously as well as exciting, interactive dashboards strengthen motivation - both on the part of IT and in the specialist departments.
"A data culture depends on everyone's trust in data. This trust can only be established and maintained through access, the development of expertise and the demonstration of value creation."
Till Aufderheide / Managing Consultant / taod Consulting
If team members are inspired by data, the actual added value from dealing with it is greatly increased. Ultimately, faster and better decisions, company-wide transparency and even cost savings can be achieved - in other words, professional data management.
Our recommendation is therefore: IT and the specialist departments should be brought together and fixed contact persons should be appointed for focus topics. Alternatively, a central data team can be established directly to take care of the data strategy and shape it proactively. In both cases, the IT and business strategies are brought together in a meaningful and sustainable way.
