In case you missed it, we covered a lot of ground on growing your business through machine learning and artificial intelligence with Niko Pipaloff, CEO and Founder of Hybrid Intelligence.
Every organization has data coming in from all fronts. Some is captured and analyzed, but much of it is sitting there on servers and in spreadsheets waiting for the patterns it holds to be uncovered. See how your business can be poised for greater success when you incorporate innovation and experimentation as part of your growth strategy.
Here's what we learned:
- Use an innovation lab as a strategy to plant a seed to embrace the pursuit of new technologies while removing the friction and barriers that can impede real digital transformation in a company.
- Give your innovation strategies C-suite level sponsorship to advocate and protect this mission critical component to your organization’s future viability.
- Any company that is sitting on a lot of data can look to machine learning as a tool. And think beyond the spreadsheet. Any data you have recorded (ex: audio logs from call centers) can use AI to find hidden patterns in the data.
- To start, focus on problems you know you have good historical data to feed it. Quality of data is the greatest limiting factor to machine learning.
- You have to be comfortable with trying things that are going to fail. Don’t determine the success of the lab on the first project. View it as an investment strategy: Use ROI on a portfolio basis over the long term and dedicate resources unique to the lab, including talent and infrastructure.
- Dedicate staff to your innovation strategies. You can start small and recruit – the only requirement is to bring in people passionate about technology and willing to put in the extra time it takes to get up to speed on the skillset.
- Create a clear line that this is not IT. Innovative pursuits should be technologically separate from the company, so the team can try things quickly and even “break” things while the company’s website and other assets are left unharmed. It’s like the Mirror Dimension in Dr. Strange where the real world is unaffected by whatever exercise you’re running.
- Keep the innovation team focused on what’s next. When a project appears to be bearing fruit and you’re ready to apply it to the organization, there should be a handoff from the innovation team to an implementation team (could be IT, could be an outside provider) who brings it to life within the company’s working environment.
- It’s more art than science and a process of discovery. The first model is often messy, but with continuous, rapid iteration an innovation lab can see if the exercise can bear any fruit.
- There are no shortcuts but you can run more algorithms simultaneously to get to the answer more quickly.