Financial Systems: The Good, The Bad, and The Ugly
Financial Systems: The Good, The Bad, and The Ugly
Let’s talk private equity portfolio companies and the financial systems they use.
Here’s the good: The overwhelming majority of private equity (PE) stakeholders understand the value of effective financial information systems within portfolio companies. Those systems not only support day-to-day operations, but they help capture and analyze the (often complex) data sets important to institutional owners.
Equally as important, the right financial information system (or combination of systems) can better facilitate management-sponsor dialogue. As a result, 64% of attendees at the most recent PEI Private Fund Compliance Forum said they plan to prioritize spend and direct resources toward process automation and overall systems improvement.
Here’s the bad: They need to, because those systems are not in very good shape. Forty-eight percent of attendees at that same event consider data management a significant operational challenge. And, according to the EY 2018 Global Private Equity Survey, more than 90% of PE-backed CFOs acknowledge their data systems “are not fully integrated across the organization.” What’s more, a full 75% reported absolutely no integration. That’s right: zero, zilch, nada.
Here’s the ugly: Even when there is acknowledgement of necessary system enhancement, and money put against that effort, that’s still no guarantee of improvement.
The dirty truth of financial systems implementations is most of the time, they fail, (or minimally, don’t function properly). That failure is the result of a confluence of issues, including the intimidating process of the system purchase, the complexity of its integration into existing tech infrastructure, and the time commitment required of those in the implementation’s orbit.
And we’re assuming the company invested adequately in the first place — which is, at least in the PE world, a bad assumption. Remember, PE is a time and numbers game. Though sponsors are well positioned to reap the benefits of systems that can calculate, analyze, and present financial data — the data they’re demanding from portfolio companies! — financial systems are a long-term investment. The steep price tag is, therefore, often at odds with the shorter-term investor game.
It needn’t be, however – because, as it relates to PE tech, pricier isn’t necessarily better. That doesn’t mean there’s an easy tech answer. The portfolio company landscape is wide and varied, and as a result, each company’s needs will be unique to them (and their industry, size, organizational structure, sponsor requests, etc).
So while there is no one-size-fits-all financial system for the PE-backed universe, there is a four-step roadmap portfolio company CFOs can employ to better align their needs to tech spend.
Step 1: Take the Tech Tour
Don’t allow for acronym intimidation. The very first step is to understand the broad technology categories in order to align to the need (and that need will likely be filled by a combination of systems layered together). Once category needs are determined, a second stage will be a deep dive into product choices and differentiators. We’ll focus here on presenting the differences between the former, but we know the Gartners and Forresters have ample roadmaps on the latter.
- Enterprise Resource Planning: Business process management software allows an organization to use a system of integrated applications to manage the business and automate many back-office functions. Examples include NetSuite, Oracle, SAP, and Intacct.
- Corporate Performance Management: Typically layered on top of an ERP system, CPMs focus on financial planning, budgeting, forecasting and analysis, with financial consolidation and reporting capabilities. Examples include Anaplan, Host Analytics, and Adaptive Planning.
- Business Intelligence: Takes data from both financial and operational systems to produce integrated dashboards and KPIs, often including dynamic visuals and interactive data. Examples Include Tableau, Microsoft BI, Qlik, and Hyperion.
- Configure Price Quote: Produces accurate and configured quotes (centralizing and providing real-time access to all product, pricing, and business rules), and supports forecasting and margin analysis. Examples include Apttus CPQ, Oracle CPQ, Salesforce CPQ, and Endeavor CPQ.
- Customer Relationship Management: Tracks and analyzes the lifecycle of customer relationship journeys. Examples include Salesforce, Pipe drive, Zoho, and Deltek.
- Human Capital Management: Unifies a wide range of HR functionality into a single system and source of data. Examples include Workday, Sage, Namely, and Paycor.
- Warehouse Management System: Optimizes warehouse and distribution center management; assists in inventory costing, placement, production, forecasting, and reporting. Examples include Fishbowl, NetSuite WMS, Oracle WMS, and Softeon.
Step 2: Do the Data Diligence
The key to this stage is understanding what the company data needs are, in order to align to value creation plans and to increase efficiency. Once those are clear, the current data gaps and analysis obstacles become more apparent. There’s also the critical, and complementary, task of designing an ideal future data/reporting state and purchasing to fit that need.
Here are some of the questions to ask during the second step:
- What are our overarching value creation objectives?
- How do the systems we’re evaluating help drive the company to meet long-term goals and growth plans? It will be important to determine if the value of the benefits outweigh the costs and complexities of implementation.
- Given those objectives, what is lacking to make our existing data meaningful? How high-level or low-level do we need to go? (Think of drill-down capabilities.)
- Who needs access to the data views (e.g., executives, managers, staff)? Each level will have differing priorities and result in different decision-making needs.
- How should information be distributed and consumed (e.g., recurring reports, dashboards, ad hoc?) Is automated scheduling important? Is there a large number of recipients? (Look at detail and cadence capabilities.)
Step 3: Scrutinize Support Sophistication
The best IT software in the world is useless unless you have a support system to run/trouble-shoot it, a finance owner to lean into it, and a management team willing to embrace it. The questions here require an accurate — and sometimes brutal — level of corporate self assessment:
- What is the availability of sufficient IT support and network capability? Do we have the expertise and ongoing bandwidth to handle a sophisticated and maintenance-intensive tool?
- Consider the source: If the IT tool benefits from real-time numbers, beyond static files, can we support the system enough such that investment in the expensive functionality makes sense?
- Do we have engaged owners on the finance team willing to work with, and advocate for, the tool?
- Will management evangelize for the new tech investment to be used as the single source of truth?
Step 4: Understand the Universe of Users
Ultimately, end user adoption is the final, and highest, hurdle determining the success or failure of implementation. Understanding the universe of users and building a user experience (UX) appropriate to that community, is a critical last step. Questions about user consumption include:
- Are potential adoptees a sophisticated group? If so, they can adapt to less-intuitive solutions. But an uninitiated group will require a more user-friendly (read: expensive) interface.
- How eager are potential users to use? If they’re all-in and awaiting implementation, interface bells and whistles may not be necessary. But, in a more corporate-led implementation, the user experience becomes paramount to acceptance and ultimate adoption — and that focus on UX will result in higher per-user costs.
And Now…Intelligent Implementation
Once the category and product variables have been solved for and purchasing decisions have been made, next comes the hard work of implementation. Here PE-backed companies should follow the golden rule that governs all tech investments: integrate intelligently. That, more than anything else, will be the key to avoiding the fail stats. Intelligent integration means the following:
- First Impressions Matter: Make the investment to integrate the right way, the first time around. Don’t pay a premium for a tool you’ll never use because it was never set up properly.
- Train, Train, Train (at every level): Make sure all users, at all levels, get the one-on-one training they need to use the tools in an optimal way, whether it is an executive accessing a daily KPI dashboard on their mobile device, or an accounting clerk pulling transactional detail for their month-end journal entry.
- Stay Current: Maintain software licenses and updates, train key users on significant changes, and keep up-to-date with the latest trends and offerings in BI technology. Don’t wait until your daily driver tool is too old for a simple trade-in and you have to start from scratch all over again.
Now that you understand the good and the bad of investing in PE tech tools and financial systems, you also understand the immense amount of time, research, assessment, and patience it takes to avoid the ugly.