Tapping into the tech startup ecosystem
The concept of businesses pursuing innovation through the tech startup ecosystem is not new. For years we have been seeing organizations get involved – many even setting up labs – at innovation hubs like Communitech, MaRS, Ryerson DMZ, Notman House, Volta, Invest Ottawa and many more across the country. The goal is to become closely connected to a great source of cutting-edge technology products (not to mention tech talent) and potentially even spot the next big disruption ahead of the competition.
From mentorship, to investment and/or acquisition, to using their products, there are many ways for businesses of any size to work with startups. Many organizations conduct experiments or proof of concepts as a way to try out new ideas and pave the way for larger adoption.
For startups and established companies, working together can be a challenge. Startups, by definition, are agile and move quickly while established companies, by definition, have lots of internal controls and processes that need to be in place for it to run at scale.
Nonetheless, we have found that with some focus, dedication and a little groundwork in place, traditional businesses and startups can indeed innovate together.
Recently, we have worked with several startups – primarily in the Artificial Intelligence (AI) space – to conduct experiments. Our goal is to create learning opportunities and proof points for both sides. If an experiment is successful, the solution may be considered for scaled deployment.
3 ways to reach win-win outcomes
1. Focus on the value proposition
While we often hear that innovation should start with a problem to solve, this is not always the case. Innovation is also about being open to new value propositions that you may not have thought of before. Take the time to think about creative ways that the solutions offered by startups may be applied. You may find surprising new ways to bring value to your company.
One example of this can be seen in the work we did with a startup called skritswap – which uses AI to translate complex documentation into simpler, more easily understood language. While this was not a problem we were actively looking to solve, one of our business stakeholders saw a great opportunity to apply this technology to improve the readability of some of our online documentation and enhance the client experience.
2. Think about minimum viable processes and scope
When experimenting with startups, think about the minimal viable set of procedures and controls that need to be followed. Given that the immediate intent is not to deploy at scale, there are ways to simplify contracting and approach security and risk reviews in a different manner. The trick is to carefully design the scope of the experiment in a way that meets the risk appetite of the company while being able to prove business value.
For example, when working with Hendrix.ai, a cloud-based AI meeting assistant, we limited the scope of the experiment to non-client-sensitive meetings which allowed us to conduct an initial proof point while meeting security requirements. In other situations, we have masked data or leveraged publicly available inputs.
3. Consider each other as partners who are “in it together”
Be sure to define joint success criteria upfront. Take the time to organize a proper kick-off meeting, define roles and responsibilities, and make sure you have the right people to participate in joint design sessions.
For example, a critical success factor in our work with MindBridge.ai, an AI for audit tool, was to include the right business analysts from the start and have the data scientists from both organizations working shoulder to shoulder to deliver meaningful insights from the data. We held a formal kick-off with executive sponsorship, ran regular status checkpoints as well as 2 full day joint design sessions. We ended with a formal executive summary of the insights generated during the experiment and identified key learnings for each party.
Well-run experiments are a win-win way for established companies and startups to learn from each other and drive adoption of technology innovation. Experiments take time and resources to plan and execute successfully. Not all experiments will result in the uptake of the solution and that’s ok. The key is to create a fair and flexible process where both parties gain from the experience and outcomes.