The Challenges of Growth

Central theses of this article:

• Companies face different challenges as they grow
• Organizational size impacts the workflow and coordination needs of logical divisions
• The size of your company is central to planning your technology investment strategy

More Money, More Problems

As companies grow, the complexity of their operations increases, requiring strategic investments in technology to maintain efficiency and competitiveness. In knowledge-driven industries like insurance, scaling places greater demands on data management, decision-making systems, and workflow coordination. Investors and shareholders drive businesses to expand, seeking the advantages that come with scale. However, as organizations grow, their technology needs evolve, requiring more sophisticated information processing tools and platforms to support increasingly complex workflows and larger organizational structures.

In this article, I examine the specific challenges businesses face at different stages of growth and how these challenges shape technology investment decisions.

At Patterson Consulting, we classify businesses in our internal database as 1 of 4 size categories:

• Small: 1-99 employees
• Core Mid-Market: 100-499 employees
• Upper Mid-Market: 500-4999 employees
• Enterprise: 5000+ employees

The priorities of a business naturally evolve with its size and stage of development. Smaller, younger businesses are laser-focused on speed—completing tasks quickly to meet immediate customer needs and establish a foothold in their market. At this stage, coordination is less of a concern due to smaller team sizes and simpler operations. However, as businesses grow into core or upper mid-market entities, the emphasis shifts. Larger organizations prioritize coordination, as managing a bigger workforce requires streamlined communication and processes to maintain efficiency.

Growth Inflection Points

As a company scales during periods of success, it naturally expands its operations and systems to reach its initial growth plateau, typically with fewer than 150 employees. At this stage, businesses often implement multiple solutions to address immediate needs, though these systems may not be fully integrated. However, to advance to the next level, companies must address key challenges, including improving coordination beyond the 150-employee threshold, enhancing data integration, consolidating redundant systems, and increasing automation to drive productivity. Successfully overcoming these growing pains enables companies to unlock economies of scale and sustain long-term competitive advantage.

In the following sections I break out the above company size categories and briefly explain how their organizational needs drive their technology investment strategies.

Small Business (1-99 Employees)

These companies typically are buying technology tactically as the need arises, and as it makes sense. Smaller companies tend to buy tools that work together as a suite and do not require a large IT organization to configure and support. Microsoft has been popular in this space, with entry-level databases (Access, SQL Server), the standard in spreadsheets (Excel), and the biggest business intelligence tool in the world (PowerBI).

Core Mid-Market Business (100-499 Employees)

Early-stage growth often relies on a patchwork of purpose‑built tools that help a company sprint to its first performance plateau—typically reached with fewer than 150 employees—but this ad‑hoc architecture soon becomes a brake on further scale. As the organization expands, leadership must shift from merely adding point solutions toward orchestrating them: rationalizing overlapping systems, integrating fragmented data flows, and automating routine workflows. By tightening cross‑functional coordination and establishing a unified information backbone, the firm can eliminate productivity drag, unlock true economies of scale, and create the operational leverage required for sustained competitive advantage.

Breaking through the latent 150‑employee ceiling demands a deliberate shift from opportunistic tool‑sprawl to disciplined scale engineering: leadership must replace loosely coupled point solutions with an integrated data and process backbone, streamline redundant platforms into unified systems of record, and embed automation wherever human hand‑offs add latency or error. This coordinated modernization not only improves cross‑functional visibility and decision speed but also unlocks hard economies of scale—turning incremental headcount into exponential productivity and fortifying the company’s long‑term competitive moat.

Upper Mid-Market Business (500-4999 Employees)

Upper Mid-Market companies have been through the integration challenges one or more times, and have a generally integrated platform. They are likely to have multiple platforms that map to specific divisions as they have become logical separate companies inside the larger organization.

Enterprise (5000+ Employees)

The large scale enterprise companies act as multiple separate companies similar to Upper Mid-Market companies, yet will have "one of everything" in terms of tooling and platform initiatives. Their IT budgets stretch up into the billions of dollars per year and the class of investments they make into technologies is large, as large as the mid-to-late investment rounds of a private company.

Framing Your Technology Investment

Most CTOs will see their organization in one of the size buckets above. Once you have your bucket, it is on a solid starting place to start framing your company's current investment, future functional requirements, and information processing goals.

Start with Company Size

As illustrated in the scenario above, just adding systems to your existing platform will eventually produce technical debt issues that have to be addressed. This manifests in 3 ways:

• Internal and External Data Integration issues (e.g., "can't synchronize data between external partners and internal systems for tasks such as 'billing')
• Lack of centralized place to aggregate data into usable information
• Lack of information architecture to produce usable information for the line of business

Most of the technology decisions made by a small to medium sized company are less strategic and more tactical — a team experienced some short-term information processing pain, and someone on the team made a battlefield decision to "make things work". This technology strategy works for a while, but there tends to be inflection points in data strategies and data platform architectures along the size segments mentioned above.

If we baseline our technology investment stategy against how similar sized companies are evolving their information processing platforms, we have some starting points for types of technologies that will work for the size of your organization. It also gives us an idea of what type of vendors we would want to begin a dialog with for platform evaluations.

With that being said, let's now bring these ideas into focus for what specific things to consider per organization size segment.

Three Key Areas of Your Technology Strategy

Many "modern data stack" diagrams will have lots of boxes that become needlessly confusing. A simple starting place at any size segment is:

1. Data Integration (how to get data into your platform)
2. Core Data Platform (where to store and process the data into information)
3. Information Architecture (how to organize the data in a way the line of business can use it)

If we have those 3 things in some minimal fashion, our line of business can process information and capture revenue (or other goals). Now, there can be a lot more to a data strategy or a technology investment strategy, but those 3 points get us started. I'll build out a larger information processing strategy from that baseline.

Segmenting the Information Economy