In every deal, it's the details that count. That's why, when approaching any merger or acquisition (M&A), leveraging data to gain informed insights into a target's performance, customers, operations, or even its geographic traits can ensure buyers and sellers shake hands confidently.
Read on to learn about the key data analytics areas you should keep front and center to unlock value in your next deal or contact us if you'd like to discuss your related needs.
The true value of data during an M&A transaction lies in its ability to help dealmakers see beyond the obvious. Whether you’re on the sell-side or the buy-side, with timely and relevant data points on your side, all parties can drill down into the business at a granular level to identify the operational trends, connections, and unrealized opportunities that may have otherwise gone missed during due diligence. Conversely, the absence of accurate, timely, and actionable data can lead to missed opportunities and money being left on the table.
Consider the following 4 areas where data analytics can unlock valuable advantages in a deals' context:
1. Customer: How well do you know the business's customer base? What drives them? Is growth coming from price, volume, or both? And what other products might catch their attention? Collecting and analyzing customer data helps buyers quickly make those connections and pursue strategies that might add value; for example, knowing historical renewal trends, you can predict future revenue patterns and product upsell.
Without making the best use of customer information, you may also be hindering your ability to retain customers. This data can show why customers drop off, what incentivizes them to remain loyal, and where retention investments are best spent. In addition, by analyzing granular product basket data by customer, you can obtain a deal edge by uncovering hidden value through improving cross-sell.
2. Product and SKU rationalization: By digging down into individual contracts and transactions, you can pinpoint opportunities to improve your product, gross margin, and pricing. These insights can also help you rationalize SKUs and understand variability in costing. For example, maybe there's an opportunity to hedge inventory costs by making a bulk purchase at a different time of year when business is slower.
Ultimately, without taking a microscope to your product or service lines and looking in at a line-item level, you risk letting actionable insights fly under your radar.
3. Operational: Timely, relevant, and in-depth benchmarking data concerning functional areas of the business (e.g., procurement, research and development, human resources, logistics, etc.) will uncover risks and opportunities that may influence an organization's ongoing growth. Data may also unearth operational limitations that are best to know before the purchase. For example, using granular Purchase Order data to understand opportunities to rationalize procurement across different plants may come to light. Further investigation, however, might reveal a need for improved systems and tools to see it through. Operational data analytics should be tailored to each deal – every business has specific metrics and KPIs that should be assessed. For example, classroom utilization rates at a private college might indicate headroom to expand student enrolment.
4. Geographical: Factors such as a region’s socio-demographics, foot traffic volumes, transit connections, and even weather can play a role in a brick-and-mortar business's success. This is all data waiting to be collected and assessed, either from the target acquisition's files or public data sources. All combined, geographical data is useful for understanding why some locations may perform better than others and where adjustments to one's strategies may be needed. In addition, knowing deeply about where your customers come from, beyond a brick-and-mortar setting, such as online sales, allows you to find similar areas and expand your market. Learning this during diligence gives you a clear action plan post-close.
Thanks to ongoing advances in data analytics, today’s dealmakers can access these insights more efficiently, reliably, and at deal speed. For this reason, advanced industry data tools and expertise are our team’s go-to strategy for ensuring clients leave no money making (or saving) opportunity left off the negotiating table.
There’s always more to a story. Data analytics unearths the “quick wins,” long-term opportunities, or other value creation opportunities that can strengthen negotiations and add value to a deal. Whether analyzing operational data to surface untapped competitive advantages or applying a data lens to customers’ buying habits to reveal cross-sell opportunities, the use cases are many.
Sellers also benefit from data analytics in the deal. It enables companies to go to market with a fulsome view of their business's value and potential growth opportunities. This, in turn, empowers sell-side players to demand an equitable price for their business, while injecting more transparency and trust into a process where both traits are vital assets.
Even if companies don’t decide to sell, the insights extracted through data analytics can spotlight growth, improvements, and innovation opportunities. These will all position the business well for when (or if) selling becomes a consideration once again. After all, there’s no fixing what you can’t see.
My colleagues have written extensively about how building a strong data analytics foundation is essential to helping businesses grow, innovate, and adapt to the modern landscape. And from experience, I know the same applies to the M&A space. That is why we at KPMG in Canada wield industry-leading data tools, frameworks, and skills to help our clients gain an edge at the negotiating table.
