Thinking beyond the status quo
AI is still a hot topic in the world of information management and KM. AI is hard to understand; it is complex and highly technical ... but then again, so is cloud computing. Few beyond the most technical genuinely understand the complexities of virtualization or containerization. Similarly, with AI, few outside of the data science world know the difference between a Random Forest and a Hidden Markov Model. But they should not have to; what they should know is how and why they should use these technologies. Unfortunately, few people today know the answers to these questions.
Adding to this is the fact that major technological shifts such as AI and cloud computing are followed by small-time thinking. The change to the cloud, for example, was driven in large part by the simple desire to reduce on-premise costs. The adoption of AI is driven by the need to speed up and automate current manual or suboptimal processes. That’s OK, but when something new comes along, it lets us reflect and reimagine what is possible, going beyond merely refining or adding more efficiency to what we already do.
In the past couple of months, our research has centered around supply chain, oil and gas, intelligent process automation, and enterprise search. I have talked to a lot of people and studied many companies and technologies. I will do more of the same over the coming months, but I suspect I will see much of the same things I have already found:
♦ That technology vendors are waiting for customers to take the lead
♦ That the focus will remain on fixing the present, rather than reimagining the future
To put it another way, everyone is waiting for someone else to take the initiative, even though we stand amid the most dramatic disruption in generations and we all know things will not go back to normal. We now like to refer to the “new normal,” but what does that new normal consist of? How can we make the most of the future? I would like to believe the tech sector can do better than posit that we will all undertake more Zoom calls and remote working.
Take, for example, the oil and gas sector. I started my career working on the Shell Kittiwake platform in 1990 (which is still in operation today). A once progressive industry has fallen behind the times, with production out of line with demand. From an information management perspective, it is one of the most siloed of siloed industries around. The supply chain, from upstream through downstream, lacks insight and information. There are significant problems to resolve, particularly at a time when oil prices are fluctuating wildly. But a careful examination of the sector shows blinkered thinking and a lack of vision. The same can be said for other supply chain industries. Transformation is needed. The tools exist to make that transformation, but it is proving hard to get past the seemingly complex use of new technologies as short-term Band-Aids to long-term problems.
But how do you think long-term, innovate, and transform? First, you need to have a vision; you need to set ambitious goals. Forget technology and dream. Once you have a clear idea of what you want to achieve, you need to take multiple steps backward to figure out what you need to do and in what order to achieve those goals. But if you don’t think big in the first place, you never pull yourself out of the weeds. The technologies exist today to achieve almost any corporate or departmental goal. Any ambitious overhaul, whether of citizen services or supply chains, will encounter cultural challenges. KM is an essential discipline that helps us develop a culture of sharing, learning, changing, and improving. KM is critical to any significant change, but in our tech-driven society, the focus is all too often on the technology itself, with a mindset that stays focused on fixing the small things and ignoring bigger problems.
Now more than ever, knowledge managers need to embrace and understand the capabilities and limitations of technologies such as cloud, AI, blockchain, robotic process automation, and 5G. What isn’t required is a code-level understanding of the mechanics of these technologies, but rather an understanding of how they can enable us to achieve our goals. If we work hand-in-hand with our organizations and build shared cultures of positive change, we can find a way forward together.