Finance leaders should assess how new talent could strengthen financial and
nonfinancial decision making through advanced analytics. Specifically, finance leaders
who are using advanced analytics should consider three new roles in the finance
function: data specialists, data engineers and product managers. Each new role
targets a persistent problem in finance analytics.
Digital technologies are enabling organizations to create new businesses, optimize
processes and transform existing business models. Advanced analytics is quickly
becoming the de facto modus operandi of digital business initiatives as new
ways to generate, integrate and analyze data emerge. Finance leaders should
therefore explore how advanced analytics could support finance’s organizational and
performance goals. But this requires a new talent approach; advanced analytics work
requires different skills compared to other finance work.
Advanced analytics in finance is the examination of data using
sophisticated techniques — such as multivariate regression
analysis, simulation, data mining and machine learning — to
complement traditional accounting and financial analysis.
The Talent Solution: Data Specialists
Finance leaders can make progress today by hiring data specialists to experiment
with the many advanced analytics methodologies available. For example, a finance
leader could ask a data specialist to understand how current customer purchase and
collection policies influence profitability in a specific segment and what changes are
most likely to increase profitability. Investigating this question quantitatively would
require no more than basic statistical knowledge (such as how to estimate and shape
different types of probability distributions) and basic analytics functions (such as
running an Excel-based simulation or applying a regression analysis in a decision tree).