To Maximize Your Exit Value, Get a Grip on Your Data

Data analysis can identify potential issues, demonstrate growth drivers, and shed light on profit drivers.
Mark BremerDecember 17, 2015
To Maximize Your Exit Value, Get a Grip on Your Data

As CFO, preparing a company for sale and maximizing exit value can be a critical part of your role. For private equity-owned businesses, such preparation often begins years in advance of a sale, but it can create value even if the company isn’t ultimately sold.

If the decision to sell is made, shareholders can realize far greater value if the company is well-prepared; if the decision not to sell is made, you’re still likely to have created a more profitable asset.

Drive Business Strategy and Growth

Drive Business Strategy and Growth

Learn how NetSuite Financial Management allows you to quickly and easily model what-if scenarios and generate reports.

Mark Bremer

Mark Bremer

Among the most valuable preparations for exit is maximizing the use of company data. While most CFOs have command of financial and accounting data, integrating insights from sales/CRM, customer transaction-level, and operations data creates additional value.

Data analysis can drive understanding of the business, proactively identify potential issues, demonstrate growth drivers and future growth runway, and understand current and future profit drivers. The value created is significant, and CFOs with command of the insights embedded in company data, integrated across sources, are more valuable leaders and better partners to sellers and buyers alike.

In our experience, we have seen many common obstacles to unlocking the value in company data. One is that the data exists but can’t be processed, viewed, or understood at an overall level because of siloing.

Another is data in legacy systems that cannot link with data in newer software and systems. For example, many companies have invested in new CRM systems that have complete sales and sales funnel data, but it cannot be effectively linked to accounting, revenue, and operations data. The data mismatch can be exacerbated by the naturally optimistic growth outlook of sales, compared with the more reserved outlook of finance/accounting, and operations data that usually is isolated from both the sales and accounting data. The numbers don’t usually sync, which limits the insight that can be generated and can call into question the credibility of all the numbers.

A typical solution to this problem is, “We’ll be able to do all of this syncing after we install our new [ERP/data warehouse/CRM system], which will be ready in 18 months.” That will be too late, and it typically won’t play out in a way that you expect anyway. More immediate insight must be developed, efficiently and quickly.

The good news is that these obstacles can be overcome without major installation of new systems or a lengthy process. One way is to invest in an integrated view of the data, and to do so outside of the current systems. A typical starting point is to link all data at the customer level, cleaning and reconciling the information in a way that provides the ability to roll up to an organization-level view and to drill down to detailed customer and product/service-level views.

Again, this does not mean installing new systems. Instead, bring all the data outside legacy systems and link and conduct analysis using the most appropriate tools, like SQL and database tools, or SAS or other analytics tools. Conduct the analysis in discrete chunks, each with a valuable output on its own and each building on the next.

Here are some tips that will increase your chances of being successful:

  • First, start with the end in mind and answer the question, “what are the final results or what is the outcome that I need?”
  • Second, think nimble, fast, and phased, not all-encompassing and slow. Analyze small data sets to identify pockets of opportunity.
  • Third, when looking at these sets, start with high-value chunks like churn/attrition analysis, the complete value of customer and granular growth drivers, and runway analysis.
  • Fourth, invest in the right people or outside help. There is probably someone on the team already who has database experience.
  • Fifth, repeat this process to build and create more value. This can be done monthly, quarterly, or as appropriate. In order to stay efficient, build templates to make future analysis that much easier.
  • In summary, most companies have a wealth of data that can be tapped quickly for valuable insight and a higher value exit. To demonstrate to colleagues the productivity of analysis, CFOs should begin with limited analysis goals to identify pockets of opportunity. Then, use those gains to reinvest in more analysis, creating a cycle to make better-informed business decisions around profitability, marketing spend, sales-force allocation, and more.

While each company’s situation is different, taking these actions can help a CFO better position a company for an exit and maximize its value. And for the CFO, this process creates personal influence and power, as well as a gratifying command of the foundational details of the business.

Mark Bremer is president of Stax, a global strategy consultancy serving private equity firms and corporations across a broad range of industries.