Building an Analytics Team for Your Organization, Part 1

Analytics can no longer be considered an optional capability for businesses that strive to be competitive in today’s environment. In working with organizations across a number of industries, one of the critical components of any successful program or initiative is driven by finding the right people to lead and participate in the program.

In this blog series, I will be discussing the various roles people play in an analytics program; people are always the most important asset of any organization, the life-blood of a company. While some of this information may be common knowledge for those well-versed in the analytics space and already operating an analytics program, the intent of this blog series is to provide guidance and information for those that are just beginning to explore the idea of developing an analytics program. I will be discussing topics such as: the organizational structure, roles, team or job family design, Skills/Knowledge/Ability (SKAs), recruiting and retaining analytical talent.

As with any initiative, there are countless approaches to setting up a program but regardless of the framework, people remain the common element. Below are two brief illustrations that highlight the roles people play within an analytics model. The first example, Table 1, highlights two types of organizations, one with a mature analytics platform and the other, an organization with an analytics platform in early stages of development. The second example is a brief introduction of the DELTA Model Framework with attention on the important role people play in an analytics program.

Table 1 ¹

The “DELTA Model Framework ² ” encompasses the five foundational elements of a successful analytics program:

• Data,
• Enterprise,
• Leadership,
• Targets, and
• Analysts

Below are some highlights supporting the “people” factor or the ‘L’ and ‘A’ in DELTA:

• Leadership: In general, analytics initiatives require participation from multiple departments or organizations within a company – IT, Business Partners, Analytics teams, etc. With resources and investments being made across multiple stakeholders, one central leader and leadership group or steering committee with clear governance processes is essential. According to the years of experience and research conducted by Thomas Davenport and Jeanne Greene Harris, leadership of an analytics program can determine success or failure. Their research is based on hundreds of organizations and a wide range of analytics initiatives. “If we had to choose a single factor to determine how analytical an organization will be, it would be leadership. If leaders get behind analytical initiatives, they are much more likely to bear fruit. Leaders have a strong influence on culture and can mobilize people, money, and time to help push for more analytical decision-making ³ .”

• Analysts: In addition to establishing the right leadership team enabled with clear governing authority, the right type, level and experienced individuals far outweigh choices regarding level of investment, vendor selection, tool selection, and scope. “Though computers and data drive analytical decision-making, they are not nearly as vital as people; we’ve never seen an analytically oriented firm without plenty of analytically oriented people. Finding, developing, managing, and deploying analysts – the people who make the day-to-day work of such organizations possible –is critical to a firm’s success ⁴ .” Recruitment and retention success have a direct impact to implementation success. It is far easier to recover from a planning error or weak architecture decision if you have seasoned professionals from IT, the business line and from the analytics discipline to apply proper insight and take action to course correct. It is also much more likely to make the correct strategic and solution architecture decision to begin with if the team is structured appropriately with the right types of resources and is all supported with proper management or senior executive-level backing.

Based on the central role of people within an analytics program, these individuals must be armed with clear governance, executive level sponsorship and access to training and resources. In my personal experience, I have found that the following steps are critical for developing an AOM or “Analytics Operating Model & Enablement” are:

• Secure Support and Sponsorship: First, you need a well-defined, clearly communicated organization chart with the blessing or approval of your sponsoring senior executive. Any major program with a vision, mission and charter, must be supported and driven from the top down with formal executive sponsorship and an executive leadership team (ELT) or steering committee.

• Clearly Define Roles and Responsibilities: Second, you need a job description for each role and complementary to role descriptions, a RACI chart. RACI means Responsible, Accountable, Contributor and Informed – and represented as such in a matrix or chart with the R- A- C- I- defined by each major function supported by the organization. For each team, a clear definition of RACI should be determined down to the level of team functions and roles.

• Planning is Key: Third, you need what I call an “Organizational Enablement” plan. Organizational Enablement is comprised of a training plan, communications plan, onboarding plan and infrastructure plan. Infrastructure should address a file share or folder storage tool, a physical library if applicable, seating chart and contact information. Fourth and finally, you need organizational work guidelines or a charter as well as a published business calendar in sync with the overall corporate or enterprise calendar (i.e., month-end close dates, release dates for key reports, earning calls, etc.).

A typical organizational design should include the following functions for AOM:

• Enterprise Analytics Development
• Technical Architecture Team
• Business/Functional Team
• Change Management Team
• Analytics Data Library Team

In the next blog post, we will further explore each organizational function, the individual teams, and the supporting role structures and role definitions.