Millenials: an issue for Financial Analysis

The topic of Millenials / Gen “Y” is certainly hot. At a recent alumni presentation at the CPA firm where I once worked, an overflow crowd discussed the impact of this new group on HR practices and policies. As the father of children now entering the workplace, this strikes close to home. But what about the impact on Finance? At the BBRT conference, we had an interesting discussion of the impact of Millenials / Gen “Y” on Finance. Our BBRT discussion centered on the way in which information needs to be presented in organizations. With increasing electronic delivery, organizations are demanding more visual presentation of results, and “instantaneous” information. In the Facebook age, data, insights and ideas flow freely and quickly. Bad data can enter the conversation as easily as a bad rumor, enabled by “corporate facebook” tools such as Yammer. And, we fear, analysts are quicker to look at the surface instead of pursuing deep analysis and simulation – a situation aided and enabled by new visual tools.

This strikes close to home again as we put the finishing touches on the second generation of reporting capabilities in our own ABC tool, rapidABC. It is easy to develop sexy, visually compelling charts to show relative profitability improvement opportunities. Yet, it is difficult to create a generic capability for data exploration and deep analysis – for example, by identifying underlying causes in all circumstances. As developers and consultants, we know generically where profit improvement may come from – for example, the “profit cliff” chart that always shows 80 – 150% of profits coming from 20% of customers, or a heat map that highlights the most and least profitable product/customer combinations. But then going further to understand all the underlying factors – relative activity intensity for example – requires the combination of solid data structured in a systematic way, good tools for data exploration and analysis (both of which we have developed) – combined with experience, training and persistency on the part of the analysts. Good analysts must identify hypotheses, explore, validate and discuss prior to reaching and publishing their findings.

This is the skill that “Gen-X”ers must pass on to the next, so that they can put their superior technical skills to work in an effective way.