Inefficient at the speed of light

While process mining started years ago as a mainly data-driven exercise, its stated goal is to be knowledge-driven. Given KM's multidisciplinary scope, we can play a major role in achieving that goal. Any process, no matter how simple, has the potential to reach across an entire business ecosystem, including all stakeholders. This seems like a perfect match for collaborative workflow, AI/ML, knowledge graphs, human sensemaking, and many of the other arrows in our KM quiver.

The rise and potential fall of the citizen developer

The citizen developer movement was heralded as a revolution. Like most revolutions, things have sometimes gone differently than planned. The logic is sound, empowering those who know the business best to build the tools and systems needed to do their job. Ah, if only things were that simple …

The third place of knowledge management

The third place I alluded to goes far beyond mechanistic KM or curated knowledge and takes us into the actual world of tacit knowledge. Here, knowledge comes from and often remains as personal experience, impressions, and intuition; it's undocumented and often hidden and elusive.

Should we go back to paper-based KM?

The sheer volume of largely useless data we have accumulated across the years severely limits the ability of AI to work well, and it comes at a heavy environmental and financial cost.

AI technologies upending traditional KM

If we are not careful and proactive about it, the concept and importance of knowledge itself may soon become blurred or lost.

Return on … Infrastructure???

As our physical and IT infrastructure continues to grow in size, complexity, and vulnerability, people and the knowledge they possess will play an ever-increasing role.

The undiscovered country

Capturing and sharing what you already know is good; and with today's data and text analytics tools, it has become much easier than when we'd first begun this journey.

The human capability to under-or overestimate

Yet maybe the most glaring example of underestimating humans we encounter in our work is in the world of AI. It's partly the term "intelligence" in AI that misleads so many, as AI is not intelligent in the same way that humans are intelligent. Though powerful, AI ultimately matches patterns it has learned, and even the smartest of AI systems is limited in how many patterns it can match and make sense of.

Finding the weakest link

Though traditional and often reluctant to change, the supply chain sector is now reassessing its lack of embrace of technology and, significantly, rethinking long-established processes.

Dispatches from the edge

Edge-of-chaos decisioning means being continually informed on the critical elements needed to make better, faster decisions.

The way of the scenario

The Delphi technique has become less effective in recent years, especially in crisis situations in which conditions, assumptions, and other variables are changing faster than the group is able to respond.

From robots to digital workers

As more firms use the term "digital workers" in place of bots, a spotlight is being shone on the role, importance, and increasing controversy surrounding enterprise automation.

Making the jump to hyperdrive

The new, all-digital workforce will be made from a combination of AI, machine learning, computer vision, naturallanguage understanding, robotics, and more.

The big opportunity for knowledge management

It may well be stating the obvious but we will not be returning to the old ways of working, even though some of us, myself included (as it turns out, I am in the minority), would like to.

How we innovate matters

Just as nobody was fooled by the arguments used to justify offshoring and outsourcing business processes, they should also not be misled by the furious energy behind automation, be it in the form of RPA or even AI.

Decentralized knowledge management

Decentralization, though a boon to technology vendors, poses a unique set of challenges and risks for information and knowledge managers to grapple with.

Thinking about KM differently

Moving to a push rather than a pull mentality simply means that we now have the technology to tag, manage, and interpret information automatically and near instantly—automatically pushing the right information to the right person (or application) at the right time.

Thinking beyond the status quo

The technologies exist today to achieve almost any corporate or departmental goal. What is lacking is the nerve to think big and think beyond the status quo—to break barriers, to collaborate, and to share.

Building the enterprise of the future: If not now, when ?

It should be plainly clear that we need knowledge management now more than ever. You can be sure that the COVID-19 crisis won't be the last crisis to come our way. And the next one might be even more severe because our supporting systems have taken some serious hits.

Deep project management

Given the increased negative media exposure that comes from project failure, organizations need more tightly integrated, intelligent project management systems, in addition to people who have the requisite skills. This need will grow as systems continue to become more complex and timelines more tightly compressed.