In today's competitive landscape, data-driven decision making is critical to the success of every business.
Working capital management, entering or exiting markets, or managing supply chains are just a few examples of strategic decisions that should be guided by data insights. In the middle market (broadly defined here as companies between $50M to $2B in annual revenue), a unique set of circumstances has made making data-driven decisions particularly challenging.
What challenges do middle market companies face?
The middle market is a significant segment of the U.S. economy, contributing roughly one third of U.S. private sector GDP. Many of these companies start as family-owned businesses, growing steadily and operating on average for 30 to 50 years. As they mature, some attract interest from private equity firms looking to help with scaling operations.
Due to their age, origin, and size, middle market companies often build their operations on antiquated ERP systems and operate with scattered data and manual processes. Even when companies use newer operational systems, they often struggle with data silos and operational inefficiencies due to growth and rapid acquisitions, which all come with their own unique systems that need to be consolidated. These issues present difficulties painting an accurate picture of the health of these businesses and in turn obstruct data-driven decision making. For example, a company looking to secure financing for strategic growth would struggle to attract investors without accurate, consolidated financial data. A company managing working capital difficulties cannot make informed decisions without detailed information on receivables and payables.
Acknowledging these challenges is especially important given that middle market companies face competition both from larger enterprises and digital native startups. Large enterprises face similar issues but are often well-funded and can procure the tools, talent, and resources to address this. In contrast, startups are lean and cloud native, often using modern tools from day one, enabling them to innovate and pivot quickly. This creates a “competitive squeeze” for companies in the middle market – they face the unique challenge of needing to maintain an existing business model (keeping current customers happy) while competing with limited resources and antiquated systems.
How has the technological landscape changed?
The modern data stack is an ecosystem of cloud-based SaaS tools for ingesting, transforming, cleaning and analyzing data, emerging in response to the problems that businesses faced dealing with old, slow, and expensive systems. Advances in cloud storage and computing provided businesses with access to new tools for achieving business objectives in ways that are affordable, fast, and scalable. Historically, the benefits of these technologies were reserved for large enterprises with wide budgets or for venture capital-backed startups. Constrained by leaner budgets and limited technical capacity, the middle market has traditionally been slower to adopt these innovations. In recent years, advancements in technology and the emergence of cost-effective SaaS tools have data-driven decision making more accessible to the middle market. A few notable examples of these changes include:
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Predictable and affordable pricingIntegrating data systems into one source of truth traditionally required a heavy upfront investment into hardware and servers. An even larger investment was then required to scale as your data grew, leaving this an expensive endeavor for middle market companies to successfully achieve. Modern cloud-based platforms have lowered this barrier to entry, with significantly cheaper pricing models that can adapt to how businesses use their data. These tools allow you to avoid upfront costs and pay-as-you-go to get started quickly in integrating disparate data systems in a cost-effective manner. |
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Scalability and flexibility through modularityContrary to the perception that recognizing value requires procurement of dozens of new tools, businesses can save on procurement by choosing only the most relevant tools for their business. Most modern data stack tools are modular, meaning individual tools complement feature sets of other tools in the stack. This allows companies to “mix and match” tools for their exact needs. They do not need to go “all in” on any set of tools, and can realize value without vendor lock-in. |
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Lower overhead for implementing and maintaining toolsPreviously, implementing and maintaining technology tools required specialized knowledge, requiring full teams of engineers, which can be a substantial labor cost on top of platform costs. New SaaS tools have automated and simplified data ingestion and transformation, making these once-costly processes accessible to smaller, less technical teams. This means middle market companies can leverage leaner teams and minimize the need for specialized engineering talent. |
These advancements have transformed the competitive landscape, making analytics and automation that was once out of reach for the middle market now cost-effective and accessible to even small and medium-sized companies. These companies now have an unprecedented opportunity to leverage their data assets to create opportunities across their operations.
How can middle market companies make data driven decisions?
At MERU, we assess the challenges our clients are facing and partner with them to implement solutions that leverage the modern data stack to transform their business. For a retail company, our team addressed unreliable financials caused by fragmented data across dozens of ERP systems. We consolidated this information into a detailed and accurate financial model, providing clear visibility into profitability, cash flow, and liquidity. This consolidated financial model allowed executives to make informed decisions to manage working capital and secure additional financing from investors.
“Having these dashboards earlier would have saved years of my life.”
- Head of FP&A, Luxury Retailer
For a construction company that rapidly grew through multiple acquisitions, we integrated data across all of their ERP systems to provide a real-time view of project and customer profitability. This single source of truth was leveraged to greatly streamline data gathering and analysis during the company’s sales process, allowing for a successful exit.
These are just a few examples of digital transformation in the middle market. Each business faces unique challenges, but all of them can use technology in new ways to drive better and more informed decisions.
Our expertise at MERU is specifically focused on the challenges that middle market companies face. We work with companies across industries and at all phases in their analytics maturity. If you are looking to drive better decisions, streamline operations, or improve financial visibility, learn more about our services here.
Authored by: Jan Aquino, Principal Solutions Architect
The author wishes to thank Audrey Gompf, Sam Stein, Jacob Gordon, Drew Kaplan, Peter Lee, and Vadim Grakhovskiy for their contributions to this article.