Corporate Software Solutions – What’s the Right Lens?

by David Zusman Partner, GoPoint Ventures

There are many terms thrown out in the venture world like SaaS, workflow solutions, productivity tools, analytics suites, data orchestrations, and smart integrations. While often used interchangeably, whether correctly or incorrectly, some of these terms refer to a business model, some refer to product features, and some an expected result. It’s a venn diagram of labels and acronyms that has increasingly merged.

What’s clear though is that corporations have always had numerous dynamic workflows – some more automated, some more core or productive, some more outward facing, and some more inward facing. For these workflows, software remains a pervasive solution everywhere.

But software really just enables a series of steps in a business process, managing data along the way to better achieve business goals. The original mantra: Workflow automation would increase speed and accuracy, while eliminating critical errors. Much of the time it would replace mundane human activity with digital ones. The new mantra: Integrate multiple automated processes into existing corporate architecture to achieve higher-level insights and better human decision making. It’s a case of, “until I brought it all together, I didn’t know what I was missing.”

So what lens should an investor or a founder have when assessing the opportunity set for a particular software? Are all these new workflows, integrations, or analytics really useful? Are they a game changer? Or are some of them just a pile of tech on top of tech for the sake of it, fueled by a start-up funding bubble that has already begun to deflate?

Here are the five key factors that drive our scorecard when we evaluate a new venture in software:

Does the software solve a big enough problem for enough people/businesses that an automated solution is worth pursuing? Solving a problem for a few people or in niche areas and extrapolating to a larger population set can be dangerous. We often find that “product-oriented” founders do not research the true extent of the market opportunity before jumping into the deep end! Also, determining if the product is truly a “need to have” and not just a “nice to have” is critical.

Can the software reduce costs in a significant enough and quantifiably-proven manner? Simply put, the easier it is to quantify immediate cost saving, the easier it is to sell. Or does the software, through insights or automation, just reduce business tail risk? These impactful negative events are often caused by small or infrequent data errors. Reducing tail risk is a form of value that tends to be difficult to prove and requires a long-term horizon. The more nebulous the value proposition, the harder it is to make the sale.

Do the insights gained from the software increase linearly or logarithmically as more processes are automated and integrated? With optimal workflow solutions (especially with the inclusion of AI), there should be logarithmic improvements and compounding insights. This also assumes the software systems can manage, store, and protect all the data it takes in.

Does the software enable scaling elsewhere in the business? Does it remove a bottleneck that enables the business to grow faster? While the workflow that is being added may have a direct benefit (lower costs, insights), there may also be domino effects that allow for organizations to scale better. For example, is Slack just a chatbox or is it an enabling solution/platform helping organizations scale more effectively. How much value can a single workflow solution actually create?

Does the software automate mundane tasks and have the potential to improve morale and culture by doing so? Can it improve the customer experience or have a greater impact on the corporate brand or internal culture? One needs to carefully consider whether adoption of automated workflow solutions positively or negatively impact corporate culture and the customer. Often, a new software solution looks good on paper, but implementation hurdles and process integration are too disruptive. Adoptability considerations are often overlooked.

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