August 14, 2017 John Tough 0Comment

With the digitization of traditional industry, software solutions are increasing their focus on the energy and industrial verticals. At the Invenergy Future Fund we are seeing many pitches a week for companies seeking capital to grow their business. As part of our diligence, we like to sit in on a few sales calls – usually to prospective customers that we introduce. Through those calls, we have seen three common mistakes that start-ups make while pitching traditional industrial firms. We list them below to serve as a guide of pitfalls to avoid:   

1) Buzzword blockers: Many sales decks pitching the operations, maintenance and security divisions of traditional industries read the same… some newly formed version of technology (MACHINE LEARNING! ARTIFICIAL INTELLIGENCE!) could dramatically improve business results. The problem is that these buzzwords talk about your company’s solution, and not the customer’s problem. The customer does not necessarily care how the problem is solved, just that the results will improve. To paraphrase a statement I recently heard from an energy executive: “what makes this solution better than the 20 other AI software companies I have been pitched this year?” As a growing start-up you are better served cutting the jargon and delving straight to results and focusing on how you will get to a proof of concept within the customer’s desired timeframe. Remember, your technology is merely a tactic to serve the customer. The real product is the problem you are solving for the customer.

2) Hubris hurts: Energy and industrial firms have been solving maintenance, throughput and security problems for decades. Yes, the technology environment is changing. But within these Fortune 500 companies there are seasoned executives who have developed impressive IT and software systems based on an accumulation of historical technologies that manage billions in assets. No new technology solution is going to completely rip & replace existing software. Start-ups that expect to dramatically replace existing software architectures and make generalizations about weakness of existing solutions simply have not done their homework. Respect the reasons that current solutions are in place by identifying existing strengths and demonstrating new, complementary capabilities. The professionals who made those architecture decisions were operating with then-existing resources and are likely still somewhere in the organization.

3) Deliberate (business) development: In-the-ground or under construction assets have detailed, expected lifetime performance metrics based on the technology and environment for when the asset was implemented. Given those strict performance expectations, a large company will only trial a new, unproven technology on a select number of assets whereby the test will not materially impact overall results. It takes time for the prospective company to identify those sites for your software and it takes time to encourage the internal P&L owner to take on the potential risk. Bake that “discovery period” and longer sales cycle into your revenue projections. The beauty to this structure is that if the software does work as expected, then the concrete data enables implementation across the rest of the asset fleet within a surprisingly abbreviated timeline. As a result, the longer sales cycles of the energy & industrial world can actually be a feature, not a bug of the purchasing decision.

We hope you find these insights helpful. If you are a software company targeting the Industrial IoT segment looking to scale your business, please reach out as we would love to share thoughts, make some introductions and help further optimize the industry.