Accidental Business Complexity

I have spent years watching once-thriving organizations get swallowed up by a creeping threat - “business complexity.” At first, it arrives so quietly that few notice. A new system is introduced to simplify sales lead management, another to handle people org chart, and then a third one to manage HR. Little by little, these tools overlap, data definitions diverge, and whole days get wasted chasing the same information in different silos. Many executives don’t notice the damage until they realize product launches are delayed, or crucial opportunities have been missed.

In his book Software Wasteland, Dave McComb warns that the sheer volume of software and data in most companies can become an albatross, slowing them down more than it speeds them up. This is not a phenomenon confined to tech-heavy giants. Startups with just a handful of tools eventually discover that the intricacies of merging different systems, data sets, and teams turn once-agile processes into tangled knots. Some leaders describe it as the cost of doing business or evidence of “growth.” However, ignoring the real toll that complexity takes only allows it to expand further and quietly erode productivity from within.

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Complexity as the Byproduct of Growth

Nobody sets out to create a labyrinth.

After all, most new software or workflow is introduced with the best of intentions. A marketing group might say, “We need a specialized analytics platform to track user engagement in real time,” while another team implements an AI-based churn predictor, and yet another spins up a separate BI tool to measure operational KPIs. These moves all sound logical, until a few months down the line, you have three dashboards each claiming to measure user retention, but with varying definitions or time windows. Now everyone is wondering, Which numbers are correct? Is the AI tool referencing the same data warehouse as the BI platform, or is it pulling metrics from a local log file? By the time you sort out which dataset is the true source, that initial goal of visibility has dissolved into confusion and extra work. 

The truth is that complexity sneaks up on every organization with any degree of scale or ambition. That’s not the real tragedy. The tragedy is when leaders don’t realize it needs active management, much like a garden that becomes choked with weeds if left untended.

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The Hidden Toll

I’ve seen teams spend hours reconciling contradictory spreadsheets or scrambling to find the most current version of a file. Top managers, lacking a single accurate view of their metrics, end up making decisions based on guesswork. Over time, employees become resigned to the chaos, and “That’s just how we do things here” becomes the unofficial company motto.

Then, there’s the intangible drag on innovation. Any new product or feature must vavigate through a bureaucratic swamp of unknown interdependencies. When someone proposes a new integration, the immediate response is often, “We can’t do that until we understand how it might break everything else.” Momentum grinds to a halt, and the organization wonders why faster-moving competitors keep outpacing them.

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Accepting Complexity but Managing It

The central paradox of business complexity is that it’s often born of growth and ambition. A small company with a single product has a simpler environment but also fewer opportunities for expansion. Successful organizations inevitably accumulate more systems, data streams, and specialized processes. Yet, it doesn’t have to devolve into mayhem.

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A Practical Approach to Taming Complexity

Yes, complexity is unavoidable, but it’s also manageable. Here are some practical actions to help:

1. Conduct a “Systems Census”
   
   • What It Entails: Create an inventory of all major software systems, data sources, and critical workflows. Capture their purpose, data owners, and how they connect to (or depend on) one another.
   • Why It Helps: Much like counting everything in a messy warehouse, this exercise reveals duplications, silos, and hidden dependencies so you can address them systematically.
2. Identify Systems of Record
   
   • What It Entails: Decide which applications (or data stores) own specific data domains (customers, products, financials, etc.) so everyone knows where the authoritative version of a data point lives.
   • Why It Helps: Without a declared “source of truth,” conflicting information can proliferate and undermine decision-making. Clear ownership also improves accountability.
3. Standardize and Align Key Definitions
   
   • What It Entails: Agree on shared terminology for critical elements such as “customer,” “order,” “invoice,” or “product.” Document these definitions and ensure all teams adhere to them.
   • Why It Helps: A universal language prevents the same metric from being interpreted differently by different teams. It also simplifies data integrations and reporting.
4. Automate Where Possible
   
   • What It Entails: For repetitive tasks like syncing data between systems, generating reports, or monitoring health checks, use scripts or workflows instead of manual intervention.
   • Why It Helps: Automation reduces errors, saves time, and ensures consistent results. It also frees people to focus on more strategic, value-added tasks rather than fighting fires.
5. Enforce Incremental Governance
   
   • What It Entails: Establish guiding principles, like naming conventions, data retention policies, and version control procedures, and improve them over time, rather than attempting one massive overhaul.
   • Why It Helps: A culture of small, continuous improvements avoids the paralysis that can come with a “big-bang” transformation. Tackle one pain point at a time to build momentum and trust.
6. Measure the Impact
   
   • What It Entails: Track metrics that matter, such as time-to-decision, product launch velocity, or reduction in duplicated records. Regularly review if these are improving as changes roll out.

Why It Helps: Demonstrating tangible results motivates teams to stay disciplined, and provides an early warning if something isn’t working as planned.

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The Ongoing Effort

It’s more like a continuous gardening effort: you keep pulling out weeds (inefficiencies, duplications, broken integrations) so the healthiest plants (core processes, strategic innovations) can flourish. The upside is profound. Teams with less internal friction deliver on projects faster and executives can pivot more confidently as they trust the data they see.

Certainly, it takes work to maintain a clean, coherent system of systems. But as any gardener will tell you, the alternative is not an option if you want to survive in a dynamic, fast-moving market. And, in my own experience, taking small, consistent steps starts to yield tangible improvements faster than you might expect. Because at the end of the day, complexity is not the real enemy: neglect is.

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