Centralize your Excellence!
This is the 3rd article in a series of 5 publications on organizations’ Data Analytics strategy. The series, called ‘Moving beyond point solutions and pilots in Data Analytics’ addresses five challenges. These are challenges that organizations most experience when they want to upgrade their Data Analytics from point solutions to strategic, data driven and coherent governed activities.
Many organizations are exploring the value of business analytics and data science. The typical initial approach is to focus on specific use cases and test those for their added-value and feasibility. This suits very well when there is a wide variety of potential use cases and it is not immediately clear if there is a relevant connection. It also combines flawlessly with the Agile method to provide early, initial proof of the potential value of a use case.
This case-by-case approach also has an unwanted side-effect. This is that the use cases and the teams that work on them that are spread throughout the organization generally approach the use cases in an isolated manner and involve only the expertise and tooling already known to them. Also, possible learnings only loop back to the same small circle of people. This article explains how to overcome these challenges.
What challenges are to be faced?
So, what do you do when business analytics grows into a strategic competence to your organization? A competence that is needed in the long-run to create sustainable competitive advantage? This poses specific challenges to the organization. For example, how to leverage lessons learned and standardize the best-in-class approach? How to prioritize across the board and put focus on the most promising use cases? How to build up and secure the needed competences? And last but not least, how to govern this rising new field of expertise within the organization?
From successful companies, we learn that 3 decisions are a necessity to leverage the full potential of business analytics and data science in an organization.
- Get Business Management committed
A solid and far reaching mandate by executive leadership from both business and IT is key to be successful in addressing use cases throughout the organization. As different departments have different priorities, it’s necessary to operate on a level in the organization where priorities can be reviewed in line with the corporate strategy. Typically, the commitment is given by a Board member and operational governance is implemented at a delegated level.
- Define roles and responsibilities of departments working with your Center of Excellence
As business is dynamic, so is its data. To manage these dynamics, a best-in-class governance model for managing data and analytics, will enable the organization to swiftly and cost-effectively explore opportunities and adopt successful learnings. The model must introduce clear roles and responsibilities that enable teams to standardize their approach and adopt the same way of working across the Board. A standardized governance model also ensures that departments will cover all aspects of, and ensure, continuity in the expertise that is needed to work with the data. Finally, it must enable the boost and alignment of data standards and models.
- Center expertise, boost all departments
Business analytics and data science ask for a broad range of competences. Across the traditional IT and business departments specific skills and awareness are needed to enable a truly data driven operation. It needs central coordination to create awareness, built up expertise and focus your effort at the most promising areas. Without central coordination, the wide variety of use cases will continue as local solutions, which do not live up to their potential to deliver sustainable competitive advantage.
If you target to receive the full value that Business Analytics and Data Science can add to your organization, you need the right level of commitment, a standardized governance model and a center of excellence that boosts the process. Start centralizing today!
The research for this article, which is a series of 5 with the collective title 'Moving beyond point solutions and pilots in Data Analytics', has been done by my team at Atos Consulting. So the thought of the gentle courtesy goes out to Tom Konings, David van Steen, Marcel van de Pol and Carline Nauta.