Every year, IT World Canada (ITWC) invites a select group of 30 CIOs for a two and one-half-day retreat.  It’s a time for in-depth conversations in a relaxed setting and a chance to reflect on the challenges and opportunities that we face as a community. The discussions are generously sponsored by Cogeco Peer 1, but are fuelled by a series of panels and presentations.

Each year, I come away with several issues to reflect on. Here’s my list from this year.

AI – Great expectations and much work to do

AI is the hottest thing around, riding high on the hype curve. But what does that really mean to us as technology leaders in our companies? Our first session on AI left me with several ideas to chew on. When we looked at the peak of interest in AI, presenter Stephen Piron, co-founder of Dessa, a Toronto based AI company, showed us a graph of the market capitalization of Nvidia stock. Nvidia chips are essential to AI applications, so the stock is a good gauge for interest in AI in the larger world. Given the chart’s peaks and valleys, Piron asked: “Doesn’t this look a lot like the dot-com bubble?”

And truth be told, it does. But those of us who lived through the boom and bust of the dot-com era know that the downfall was more than marketing hype gone awry. The reality is the dot-com bubble occurred, in part, because the technology and businesses of the day could not deliver the promises they were making or the services that customers were demanding.  It took a long time between the promise and delivery. Those that existed for short-term gain and over-hyped their abilities crashed.

But those who focused on real value, steadily built their capabilities, followed real customer demand and were willing to reinvent the way they did business prospered in the long term. Their first attempts were clumsy, but in the long term, they prevailed.

To underscore the point, I offered up the example of a dot-com business where the company relied heavily on manual processes that bridged technology gaps and lost money year after year competing with large established companies. That company kept working, refining its processes and technology and refusing to give up. Today it’s a model for how a company can operate in the digital age and even sell its computing power to other businesses. That company? Amazon.

When we look at AI from this point of view, what can we learn? The current tools and our current abilities will not measure up to the hype. There is a great amount of infrastructure work that we need to do. What we can do now will not measure up and, in retrospect, it will appear clumsy. But if we look at it as inevitable and if, instead of waiting, we take our first stumbling steps, and focus on the value to the customer, we can accomplish great things.

Use Cases – Focus on the benefits and not the technology

It’s a lesson that we all should have learned, but have we really learned it well? Our discussions quite rightly looked at how we do things. To be fair, that’s our job. But do we spend enough time looking not at how we do things, but what our goals are? That’s where the concept of the agile use case is so valuable.

The Agile Manifesto charged us to think in new ways. It encouraged us to think aspirationally. Instead, many of us continue to discuss agile as if it was a method or a formula.

For years, I have been repeating the mantra that the real agile question is not about “what” but about “why.” My interpretation of agile is based on a statement that I call the “agile question.” The answer to the agile question comes in this form. “I need this so I can do this.” What they want to do, or why they want to do it, is the most important thing.

While this isn’t a new truth, it came home to me in a number of presentations and discussions.

Karma among CIOs

Who would have thought that a CIO retreat would lead to a discussion of karma? But as I listened to presenters and participants in discussions, it became apparent that a lot of successes in technology came from people who had help from their community. One of the participants talked about getting help and advice from Kevin Peesker, now the President of Microsoft Canada. In a former role, Kevin didn’t have an offering to help someone, but he did refer them to Cogeco Peer 1. That referral helped build a partnership that led to a successful cloud offering.

For those who hear success stories as marketing hype, I know all the people involved and the story and it is a real success story. But that’s not the point. The point is,  and I heard it a number of times, that much of our success depends on people who will take time to point us in the right direction, open doors, share their knowledge, their successes and their challenges.  It comes from peers who care enough to give you feedback or support when you need it.

Governance in the era of data 

The dreaded “g” word. How many of us would rather watch paint dry than go to a discussion about governance? Perhaps it’s because we still have a model of governance mired in powerpoint presentations, endless discussions and reports, ticking boxes, or never-ending steering committees. It’s not why we got into technology, but it’s a price we pay for success.

Yet in the era of cloud and digital transformation, I was struck by how important it is to make governance a reality. It matters, whether it is the data governance necessary to make AI work in real-time or the marketing governance that Teknion CIO John Comacchio detailed in his presentation about dealing with data.

The ROI of a digital asset  

If we really want to truly find the value in our data, we have to be able to express the value of a digital asset. Although one person talked about it in terms of a balance sheet, I don’t think we need it to be that formal in terms of valuation.

Every presentation and discussion came back to the same point. Moving forward is hard work. It involves taking chances. It involves making mistakes, learning and not giving up.

The model I had in my mind came from our first presenter on AI who talked about use case development as an algorithm. In each of the company’s AI workshops, participants would identify 30 to 40 use cases which had the potential to deliver value quickly. They boiled those down to about 10 that they would really investigate. From the 10 use cases, they would find four pilots where they would really look at the feasibility. And from those four, they would find one that might have the potential to fully merit the type of development that would offer the potential investment to take this idea to a real “production” reality. Forty to one. Sounds like a lot of work and it also sounds like the real world.

How can we invest the time, the energy and the corporate resources to sift through 40 ideas to come up with just one which we really bet on? How can we spread that type of thinking throughout our enterprise?

We need to be able to see, if not the value, at least the value potential in each of our data assets. That’s what will drive the pursuit of digital transformation, of building the infrastructure and processes that will deliver value.

Final thoughts

As more details of the summit are posted on our websites and shared in our newsletters, I’m sure there will be more nuggets brought forward. In the coming weeks as I am reading, watching videos and listening to podcasts to expand on these themes for a final Summit Report, I would love to hear thoughts on the path ahead from you, the reader, whether you attended the Summit or not.

As always, you can reach me at  jlove@itwc.ca or on Twitter @CIOJimLove



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