Strategies to Set Up and Scale Analytics CoE
The economic and market dynamics over the past decade has taught us one thing – ‘business efficiency’.
Be it in pushing cost efficiencies, growth strategies, market expansion plans, or improving decision-making, businesses are seeking avenues to increase their efficiencies continuously. Today, one way, or perhaps the ‘only’ way, to increase business efficiency is by making data-driven decisions. This need, along with the growing volume of data, is pushing organizations to set up analytics and business intelligence Centre of Excellence (CoE). It helps enterprises access insights on customers, services, products, markets, etc. and help them proactively adjust their strategies according to the shifts in the market forces.
But why do I need an Analytics Center of Excellence? Isn’t having an in-house analytics team enough?
Why you need an Analytics Center of Excellence?
Let’s begin by understanding the purpose of a CoE. The CoE is a cross-organizational body that is responsible for a specific function (primarily information management). Its main purpose is to identify, develop, and establish cross-functional processes and harness the expertise and knowledge of resources to provide tangible business benefits.
A CoE is a channel leveraging which project managers, customers, line managers, etc. can fulfill and improve business initiatives and their outcomes. The CoE, most importantly, is also an updated knowledge repository that continuously generates and refreshes knowledge, skills, practices, and competencies and serves to guide those working in that business domain.
So, when should you set up an Analytics CoE?
Some of the key reasons to establish an Analytics CoE could include:
- Increased adoption of analytics at an organizational level
- Need to accelerate go-to-market
- Improve collaboration between business and IT
- Make analytics accessible to all business departments
- Standardize analytics tools across the organization for increased adoption
- Discover ways to transform operations, products, markets and eradicate operational redundancies and obstacles
Strategies for setting up an Analytics CoE
Define the roles and responsibilities
The right set of people will make all the difference to your CoE. This becomes a Catch-22 situation as in the face of global analytical talent shortage, this is perhaps the hardest piece of the puzzle. You need data experts such as data engineers, data scientists, data architects.
You need to create a data custodian. This custodian can be in-house or a third-party team and has access to all the data sources of the organization. This team will support all needs for data mining, data assimilation, and reporting.
Along with the data experts, your Analytics CoE should also include business experts to align the organizational business strategy and all aspects of the business to improve efficiencies and drive profitability.
Choose the right platform
Choosing the right platform for your CoE is of importance if you want to drive usage and increase the use of data in decision-making processes.
Adopt an easy to use, intuitive, comprehensive platform that allows business users to play with data, examine patterns, reveal hidden insights without necessarily needing the help of data scientists. The platform should automatically implement the right models to the right data to help business users gain the insights they need to achieve their desired business outcomes.
The platform should also give you access to rich visualizations and powerful interactions to provide an elevated user experience. It should also have a pre-built set of Linguistic, Statistical, NLP, and Machine Learning techniques to Model & Structure textual data for analysis, visualization, and collaboration.
Focus on governance
As the volume of data increases, so does the focus on data governance. Given that no CoE has unlimited funds and resources, it is imperative to set the right priorities and control the costs. For this having a good governance framework is essential.
When establishing this framework, it is also crucial to ensure that the Analytics CoE fits in with the existing Business Intelligence and information governance framework.
Along with this, the CoE also has to have big data governance policies in place, ensure the security of data, have robust access management strategies, and also have the right privacy controls. When setting up a CoE, it is imperative to remember that data is a key asset. Thus, having governance focus helps from not only the legislative standpoint but also a security standpoint.
Deploy as a service-radar
The Analytics CoE should also be able to deploy as a service. By enabling deployment as a shared service across business units, the Analytics CoE can democratize data use by making data-driven decisions accessible. This model also helps in improving and optimizing infrastructure and resource utilization and rationalization.
When setting up the Analytics CoE, it makes sense to educate the users and explain that the CoE is not just an algorithm factory. It is also not just a team of product specialists. It is a place where technical and business teams come together. Here, tools, technologies, methodologies, and techniques are applied to data to gain the efficiency that today’s business organizations need and help all employees become citizen data scientists.