Access to very specialized, innovative data expertise is crucial these days. Enterprises of all sizes face increasing pressures from very nimble and efficient startups, changing market trends and global health challenges. Successful enterprises will need to do things better and faster than they ever did and adapt and innovate better than their competitors to succeed.
As a result, COEs are in more demand than ever, and the Analytics COE is leading the way. COEs are no longer a luxury afforded by very large F100 and F500 enterprises and are finding their way to medium and small companies, albeit, at a smaller scale.
Strategic enterprises are thus considering COEs and an increased focus on the management of their data assets as key competitive differentiators, so many organizations are taking COEs more seriously than ever.
In this first of three installments I will lay the foundation and definition for the Analytics COE, outline its key benefits, prerequisites for success, key drivers, and what COEs are not and should not provide.
References throughout the three installments span the last 3-5 years. The challenges and benefits of COEs have been consistently increasing over time.
The COE stands for Center of Excellence or Expertise. It is often referred to as the Center of Competency or COC. The Analytics COE is often called the Business Intelligence Center of Competency or BICC, or the Analytics Center of Excellence or ACE. Other notations may also include COEI (Center of Expertise and Innovation).
For the purposes of this discussion, I would like to use the name Center of Expertise and Innovation or COEI, since it best describes what it needs to be and what it will do. In my next entry in the series I will highlight the capabilities and advantages of a Data Management COEI.
There are many types of COEs. Here are just a few:
Focusing on the first 2-3 COEs in this list will provide your enterprise with tremendous, tangible value, value that increases drastically when the COEs leverage an integrated, mature set of Data Integration, Governance and Management tools that work seamlessly to support your enterprise analytics solutions.
The COEI is a centralized data & analytics organization meant to streamline all enterprise analytical efforts while standardizing analytics demands/requests and the way analytics are presented and consumed. It is staffed by a group of very senior, dedicated, intelligent and experienced business and data experts that are aligned with and serving multiple Lines of Business (LOBs) with their Analytics requirements, including:
This COEI aims to help multiple LOBs focus on their businesses’ reporting and analytics needs by producing the required analytics as well as enabling as many self-service facilities for these LOBs as possible – so that LOB staff can stop focusing on data wrangling (data massaging and cleaning) and more on producing analytics that drive business value.
According to Gartner, COEs exist to “concentrate existing expertise and resources in a discipline or capability to attain and sustain world-class performance and value.” These virtual or physical centers combine learning and oversight in a specific area, driving the organization to shift across multiple disciplines together.
The COEI will deliver multi-faceted, tangible, and intangible value to the enterprise, and is made up of a team of dedicated individuals outside of the LOBs or functional areas that it supports within the enterprise. The COEI usually leads the way in analytics innovation and in exploring and developing, adopting, and standardizing tools, techniques, and best practices.
This group operates across the enterprise and focuses on:
I am always asked what does not belong in an Analytics COEI and what should be included among the functions of the Analytics COEI. Clear distinctions must be made, and expectations must be set about what the COEI is and is not. In my next installment I will include more details around roles, responsibilities, and core Analytics COEI functions.
A center of excellence is not:
But it is the group that will be:
Companies always need to justify the implementation and role of the Analytics COEI, since building one will be both disruptive and constructive. These drivers are shared among most enterprises that are trying to become data driven and are often required to build a ROI study. Some of the main drivers behind establishing this COEI include:
When you are starting your COE, it is as important to think about what conditions need to be put in place for success, as well as evaluate any known success inhibitors and risks. Without considering all of these, the COE will struggle to gain traction.
Prerequisites to building an Analytics COEI include certain capabilities that need to be in place and have at least a level 2 maturity to ensure a successful implementation.
There are many proven benefits and huge advantages in implementing an Analysis COEI. After 1-2 years, the companies I have worked with cited great improvements of 3-6x in time to market and trust in the results that went from 10-25% up to 80-90%. They also mentioned that they have rationalized the tools used by IT and the LOBs by 30-55% while eliminating 70-80% of shadow IT staff. Finally, most enterprises reported increased capabilities to deliver complex AI, ML and statistical modeling and trending analysis/data mining that the enterprise was not even expecting.
And the experts agree:
Gartner shows that 95% of organizations that establish a Cloud COE will deliver measurable cloud transformational success through 2021. With a firm understanding of the definition and rationale behind the Analytics COEI under our belts, we will turn our attention in my next installment to discussing how to set up your COEI, including:
Radu Arslanian is a Sr. Principal Consultant in Informatica’s Advisory Services group, a team dedicated to helping our customers design and implement their data programs and strategies. He has more than 25 years of experience designing, architecting, and delivering Advisory and Strategy services focused on Data Strategy, Data Governance and Data Management and Quality programs.
Need help partnering with your business stakeholders to drive more value, build a roadmap, build a COE, or design your data strategy and data governance programs and processes? Contact Informatica’s Advisory Services group for an initial consultation.
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