• Christina D. Warner

Leadership Edge with Richard Potter, co-founder and CEO, Peak

For my leadership series, I had the fantastic opportunity to sit down and interview Richard Potter, CEO of Peak. Richard founded Peak in 2015 and has overseen its growth from one of Manchester’s hottest tech companies to a leading enterprise AI provider with offices in London, Manchester, New York, Jaipur, and Pune. In 2019, Richard was recognized by Data IQ among its 100 data influencers for his work in shaping the early Decision Intelligence space.

Founded in Manchester in 2015 by Richard Potter, David Leitch, and Atul Sharma, Peak is on a mission to change how the world works. Peak’s Decision Intelligence platform provides businesses all over the globe with AI-powered solutions that drive commercial outcomes.

Connecting data sets from across an organization to provide predictive insight, the Peak platform directs fast and effective decision-making. It is used by leading brands, including Nike, Pepsico, KFC, Sika, and ASOS. In August 2021, Peak announced a $75m Series C funding round led by SoftBank’s Vision Fund II.


Web Summit

At a time of great uncertainty for many industries and the world itself, Web Summit gathers the founders and CEOs of technology companies, fast-growing startups, policymakers, and heads of state to ask a simple question: Where to next?

Politico has said we run “the world’s premier tech conference,” the Atlantic that Web Summit is “where the future goes to be born,” and the New York Times that we assemble “a grand conclave of the tech industry’s high priests.”

Web Summit also hosts events worldwide: Web Summit in Tokyo, Collision in Toronto, and RISE in Hong Kong.


Q&A

Can you please provide a brief introduction to yourself and your role within PEAK? What brought you to this specific career path?

I am one of three co-founders at Peak, and, as CEO, my role touches on every part of the business. It is an exhilarating time for Peak; we completed a successful Series C funding at the beginning of September and are opening offices in Pune, Mumbai, and New York. So lots to keep me busy!

I’ve always been interested in tech. I worked in investment banking for UBS, covering tech and semiconductor stocks throughout the 2008 crash, and later ran the product line for the high-growth semiconductor company Wolfson Microelectronics (now Cirrus Logic), supplying chips to Apple, Samsung, Amazon, and Sony. I moved to Cooper Software as their commercial director before founding Peak.

What is your blueprint to success? Can you share an example of how you have implemented this into your work at PEAK?

We established Peak with the vision of changing how the world works; half of that vision is to build a company people love to be a part of. I think that this ‘people-first approach has been our blueprint for success.

On a very basic level, Peak effectively solves problems. The team we need to do that successfully must have a diverse array of outlooks and experiences and come from a variety of backgrounds. Everyone’s role has to matter; they need to be trusted to do their job and empowered to do it and make a meaningful contribution every day. We are very rigorous in how we select people to join the business, and most of our selection process is geared around the company’s values and behaviors – smart, curious, responsible, open, and driven. That has meant that, as we scale and open new offices internationally, we’ve been able to maintain our unique culture.

But people first is about more than just how we engage with each other as Peakers. It’s also a framework that has shaped our external processes and platform. Our platform is user-friendly, our communications are straightforward, and we prioritize the customers we work with. Yes, we’re a tech company, but we never lose sight of the fact that we exist to deliver solutions for people.

What is/are your life philosophies? Are there any social causes that you are particularly passionate about?

I do fundamentally believe that AI has the potential to have a positive impact on the world; it can help to remove mundane tasks from our daily work to make it more exciting, fun and novel, freeing up time for creativity. It can help us meet sustainability targets at a societal level and tackle the biases that prevent so many groups from accessing resources.

I’m really proud that our platform is being leveraged by businesses to reduce supply chain waste, take trucks off the road, and improve agricultural sustainability, but there is one project that is particularly close to my heart since it impacts my local community in Manchester.

Throughout the lockdown, we ran fundraising events for Fareshare Greater Manchester (GM), a local charity that distributes surplus food from the food industry to charity partners who support vulnerable people. The experience pushed us to ask what more we could be doing. We’ve since partnered with Fareshare Greater Manchester to provide Decision Intelligence solutions that will help them work more efficiently with their volunteer resources.

Our UK team of over 70 data scientists will be doing a week-long hackathon in the coming weeks to build out a number of bespoke solutions, and seeing how passionately my team has worked with Fareshare GM to get this project off the ground, the creativity and the time they’ve dedicated to it has been inspiring in itself. It strengthens my belief that AI is and will continue to be a positive force for good in the world.

Are you working on any exciting new projects right now?

Probably one of our biggest and most exciting! We are going to be opening up our platform to technical teams besides our own. Historically, we have worked with our customers to build solutions. From January, those with AI capabilities will license the platform and make DI solutions independently for the first time.

This is a big step forward for our business and the sector as a whole, and it means that business users will be working on the same platform as data science and engineering teams for the first time, removing many of the challenges that face organizations when developing and deploying enterprise AI solutions.

What are your "3 Things I Wish Someone Told Me Before I Started" and why?

I don’t know if I have three! But I wish someone had told me to “move faster!”. Since starting Peak, we’ve not looked back, but I do sometimes wish we’d done it sooner and not spent so much time deliberating over it. Since we landed our seed round, the speed with which some things have happened has surprised me – how fast our customer base and brand grew in the UK, for example – but other things have been much slower to get off the ground. It takes time to build a great team and to grow and develop talent. It takes a long time to make a platform as capable and broad as Peak, too. I would love to have started earlier!

Do you have a life hack that’s always come in handy?

Not as such, I am not one to focus on ‘shortcuts’ and often derive a lot of fulfillment from taking a considered approach to many situations. Well, perhaps that’s it; I believe good things come to those who wait, work hard and seize the opportunity. Perhaps my hack is that I’ve made my impatience something I can enjoy… although I still wish I’d started Peak earlier!

What do you want the readers to know (any calls to action)?

We are expanding into the US and have a range of really exciting roles open for our New York office. If anyone thinks they’ve got what it takes to be a Peaker, we would love to hear from you. Our open roles are on our website.

You spoke on the topic of ​​Advancing AI with Decision Intelligence. What are the most surprising insights you’ve learned on this topic?

So many! I think the thing that continues to surprise me is how many businesses are investing significantly in getting their data AI-ready and building out technical teams without any real concept of what commercial objectives they need an AI strategy to achieve and deliver on.

Decision Intelligence (DI) as a category aims to address this. It is the commercial application of AI to aid decision-making, but the main differentiator of a DI solution is that it must deliver a tangible return before it can be classed as DI. One of the big challenges with AI is that only a minority of models are built to get deployed, so starting with an outcome in mind – as you have to with DI – is key to widespread enterprise AI adoption.


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