How Quality of Earnings Can Drive Value To Your Manufacturing Enterprise

By Jerry Dentinger & Ryan McCaslin

Dealmaking in the manufacturing industry is poised to accelerate in 2017, buoyed by investor optimism around proposed pro-growth economic policies. Despite the modest slowdown in volume last year, multiples and valuations stayed high going into 2017. Therefore, buyers remain laser-focused on understanding a target’s profitability model to justify the expensive prices they are paying. The due diligence process continues to be critical to making informed investment decisions and capturing value after closing.

As part of the due diligence process, buyers typically seek out a detailed analysis of a target’s Quality of Earnings (QofE). QofE analyses aren’t new, but attention continues to grow around Big Data and how to navigate the exponential increase in volume and variety of structured and unstructured data in a due diligence process. This development has added a new layer of complexity—demanding a near-forensic level of detail, further increasing the burden on sellers and raising buyers’ appetite for information. For small and mid-sized manufacturers, where QofE processes often start immediately after receiving a Letter of Intent (LOI), introducing another layer of unexpected complexity can add serious anxiety to the sale process.

The proliferation of data, however, is also a major opportunity for both buyers and sellers to analyze and glean meaningful insights and thus gain important leverage during negotiations. For sellers, QofE analysis proactively identifies new areas to create value. For buyers, it helps confirm or challenge value to justify the investment or re-trade the deal.

Increasingly, manufacturers are proactively using data analytics tools to identify new areas where value can be created and proven. No longer viewed as a burden, the QofE process is enabling sellers to take more objective looks at their business and operations prior to sale. It’s crucial to understand where your business generates value well before bringing a buyer into the picture. Data analytics has proven to be an extremely important means to identify, create and hold value for companies going through a sale.

How is Big Data changing the QofE process?

QofE is not simply an accounting function—it also helps a buyer understand how and where a business makes its profits. Buyers request QofE analysis to be performed on targets to help them confirm value and identify areas where they can begin to drive returns post-close. The process requires sellers to disclose a significant amount of company data to allow buyers to drill into profitability by customer, product, SKU, geography, distribution channel and a variety of other metrics to understand where value is generated. Sellers are not always comfortable sharing such sensitive information with potential buyers. This friction has increased with the introduction of data analytics.

Historically, sellers have responded to QofE requests by providing as little information as possible. Today, they provide significant confidential information, most of which is delivered in electronic form with multiple large data extracts from their operating systems. QofE teams analyze these data sets manually through sophisticated spreadsheet modeling. All of this is done under tight time frames and often requires significant effort to reconcile and ensure completeness of the information. Most sellers have never provided or analyzed this volume of data—much less in an electronic form—until entering a sale. This can result in a slow start to the QofE process, delays and sometimes cost overruns if sellers are not prepared.

In the manufacturing industry, embedded sensor technology, wireless connectivity and mobile technologies have given companies access to unprecedented levels of data, enabling more sophisticated reporting and metrics. However, combing through these disparate data sets to create actionable information poses a significant challenge for mid-sized manufacturers unless they use data analytics software that links to their ERP systems. Even then, companies may still struggle to design management reporting that combines operating data with the financial information to meet the rigors of a QofE analysis. Today, few manufacturing companies are able to implement a comprehensive, cost-effective data analytics approach.

But that is changing.

With a variety of Big Data tools available, companies can now obtain greater visibility into key financial variables and their relationships, identify gaps and evaluate business opportunities in significantly less time. For both buyers and sellers, leveraging data analytics in conjunction with a QofE process provides valuable insights into where value is created or exposes whether value is sustainable or if it truly exists.

Manufacturers face unique QofE challenges

QofE analyses can be more challenging for manufacturers than other industries. Why?

  • Production volume: Many manufacturers, particularly in sectors like fabricated metals, plastics and components, operate in high-production-volume environments with thin product margins. Analytics and reporting are both critical and challenging because of product costing, hundreds of bills of materials and the sheer number of SKUs. However, this level of complexity presents a significant opportunity to pinpoint value drivers across product lines, channels, geographies and individual customers.
  • Difficulty understanding costs: Manufacturers are proficient at tracking direct costs of production and distribution for specific products, but complications arise when accounting for indirect costs, overhead and allocations of variances, particularly if there is strong seasonality to revenues or volatility in the supply chain or marketplace. Errors can occur in standard costing and overhead allocation methods that affect fully absorbed product costs and thus raise questions about whether a SKU, product family or entire customer relationship is actually profitable. Further challenges arise when companies operate with multiple business lines. Successfully implementing data analytics here generates visibility and adds significant value.
  • Inventory and working capital: Manufacturers typically operate with high inventory levels and overall working capital. In a deal, buyers and sellers negotiate a working capital target or “peg” that will be delivered at closing based on an agreed-upon methodology and historical performance. Data analytics is starting to play a critical role in setting pegs by, for instance, proactively identifying inventory obsolescence issues down to the SKU level. These tools are facilitating stronger negotiating positions for their users.

A proactive approach to QofE adds value

Regardless of whether you’re considering an immediate sale or looking to increase value through process improvements, these three proactive practices will improve your readiness for the eventual, extremely thorough QofE process.

  • Mind the GAAP gap. Keeping your books on Generally Accepted Accounting Principles (GAAP) and as current as possible is prudent if you are considering a sale. Many companies update their ledgers quarterly or even once a year, whether audited or not, and many keep certain accounts on a cash basis. In QofE, you need the historical bookend of a trailing 12-month period on accrual basis, and scopes are usually no less than two full years, often three. Monthly GAAP-based financials and corresponding monthly metrics are key.
  • Be proactive and understand the QofE process. Get ahead of the curve and anticipate the demands you will face in the sale process. A QofE is industry standard, and most third-party debt and equity providers require it. Too often sellers aren’t aware of QofE requirements until they have an LOI, and regardless of whether it is a proprietary sale process or a broad auction, due diligence is extremely detail-oriented, with no topic left off the table. Technology-enabled tools are making the exercise more complex, not less—but they’re also necessary to the process. Thus, QofE preparedness should start no later than 90 days before hiring an advisor.
  • Look in the mirror. The sooner QofE disciplines are introduced, the sooner value creation can begin for selling shareholders. Sellers should consider “reverse due diligence” one or two years before starting a sale process so they can identify and capitalize on process improvement opportunities to increase long-term value, identify lower versus higher profit operations, and generate a higher purchase price. Today, however, sell-side QofE typically begins when the seller hires an advisor, who shortly thereafter assists the company in the selection of an accounting firm. Better late than never, a seller-initiated QofE at the time of sale will be instrumental to holding value during the sale process. Holding value and certainty to close are the two biggest reasons why sell-side QofE has become a necessary part of a seller’s process in the U.S. market—despite being part of the European M&A landscape for decades. Sell-side QofE pays for itself many times over, whether started at the time of sale or years earlier.

Understanding the methodologies behind a QofE analysis, and then approaching it as a best practice—rather than as an accounting function or “check the box” requirement for due diligence—can help sellers maximize value upon exit. Incorporating data analytics solidifies the understanding where value is created and where to drive the business after sale. Sophisticated buyers are already looking to the future on how to drive value in their targets long before they submit an LOI. Sellers who understand that perspective and prepare for diligence accordingly will facilitate greater success for themselves and all parties in the transaction.


This article originally appeared in BDO USA, LLP’s “Manufacturing Output” newsletter (Winter 2017). Copyright © 2017 BDO USA, LLP. All rights reserved.

CATEGORIES: Manufacturing & Distribution
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