Lack of talent slows implementation of analytics
The potential of modern analytics in finance is enormous, but many still struggle to move beyond descriptive analytics.
In the five-plus years since analytics first entered the business mainstream, many finance departments have developed capabilities to leverage data for driving better decision-making. Some have even become sophisticated practitioners, while others are on a very early stage. And so the gap remains wide.
While finance departments have plenty of motivation to address the analytics issues, a June 2016 Deloitte Dbriefs webcast attended by more than 3,000 finance professionals found that 34.9 percent indicated that they do not even know which forms of analytics their companies have adopted. Asked what may be holding back their analytics efforts, respondents most often cited people, followed by process, technology, data, and strategy.
Getting the right talent
With a better understanding of the five skill-sets needed to produce descriptive, prescriptive, and predictive insights, CFOs can then map those capabilities against current staff aptitudes and decide which ones can be met internally and which may have to be filled via hiring, partnering, or through third parties.
One way to begin is to simply poll finance staffers about their current analytics capabilities or relevant experience, and also gauge their interest in making analytics a larger part of their job responsibilities. Addressing the needed skills through training and development programs is also part of building out an analytics capability, and such efforts may benefit from the creation of rotational programs that give analysts exposure to the needs of tax, treasury, and other specialty areas, enabling them to develop their analytics capabilities to the fullest.
To elevate analytics to the next level, though, may require creating a dedicated analytics function within finance, led by a director of analytics or similar position, who serves as the orchestrator of the applicable skills, at least for the analytics projects that finance spearheads. This individual is typically a midlevel finance staffer who has accumulated some skills in data management and analysis. Some companies choose to embed their finance analytics group within the financial planning and analysis function, while others make it a separate group altogether. Regardless of the model chosen, companies tend to start small, with three to four people in the group and then expand as an established record leads to increased demand, both from within finance and from other business units.
Effectively organizing the analytics function as it expands, however, can present its own challenges.
Think of it as a continuum, with a dispersed model at one end in which many small analytics teams are dedicated to functional areas, including finance, and a centralized model at the other, in which a single analytics team addresses the needs of all areas of the business. In between, options include the creation of an analytics Center of Excellence and other hybrid models characterized by a mix of centralized and decentralized capabilities. Often, one of these hybrid models is a good place to start.
CFOs can also play an important role in propelling the use of analytics by taking a number of important steps, including:
- Setting a personal example by conspicuously using analytics to make important decisions.
- Dedicating a pool of funds to support analytics activities and projects.
- Talking frequently about the value of analytics and data-driven decision-making, both within finance and by advocating for the use of analytics across the organization.
- Working closely with analysts, regardless of where those analysts reside, by providing access to data, assessing problems and opportunities, and questioning the methods and assumptions behind the analysis.
- Developing a close working relationship with the chief information officer (CIO), because data governance and systems capabilities are critical to the effectiveness of analytics.