TLDR;
- AI is suddenly able to master many of your business processes.
- How well your company manage your staff's strategic and problem solving capabilities is becoming critical.
- Knowledge, not information, is fast becoming your most valuable asset as human staff focus on solution design and exception management.
- Managing that knowledge will fast become a major focus of boards and executive teams as they avoid the rigidity of legacy business management solutions.
With AI now able to make decisions for us, we don't need knowledge any more, right? Or people for that matter, right? Right?
In a recent HBR article, Thomas H. Davenport, Matthias Holweg, and Dan Jeavons discuss the important question of how artificial intelligence (AI) is helping companies redesign their processes.Business scholars and consultants have been encouraging organisations to better deal with change and volatility for decades now. Hauschild, Licht, and Stein captured this well “In today’s changing economy, the key to faster, cheaper, and better is to bring the full force of a company’s knowledge to bear on the effort. Knowledge, not land, labor, and capital, is now the lifeblood of a corporation.”
Attempts to move away from scientific management and more toward Peter Drucker's Knowledge Economy have been undermined by many leaders clutching to traditional linear forms of control such as Five-year strategic plans and simple, quantitative metrics and KPIs. Drucker knew this and spoke often about the self protecting nature of power structures. Some companies have gone out of business as a result; either slowly over decades like Kodak or suddenly during the recent pandemic. However, many persist, including in the government arena where competition and profitability pressures don't have the same import.
Suddenly, a potentially larger fluctuation is on our doorstep, and it's set to impact every sector, both private and public. The snowball of Artificial Intelligence. I say suddenly, but of course this has been coming in for decades now. However a few things have changed recently as outlined by Bruce Boyes in his recent RealKM article and the uptake of these new tools has been explosive despite various warnings and examples of cyber-security failures.
Focusing on the future of management
I am interested, not so much in the details and possibilities of tools like chatGPT as I am in how the nature of our management structures will change as trust increases in these AI bots, and automation, design, authoring and analysis get handed over.
For years, companies have rolled out ERPs, CRMs, Workflow and Risk Management tools in order to build and reinforce the organisations ability to deliver the HOW of their business and secure their key value propositions. But until now, much of that focus has been on the manufacturing and service delivery capability. That is where these tools are aimed. As Davenport puts it, "The technologies enabling reengineering in the 90s were primarily transactional and communications-based. They enabled efficient data capture and transfer within and across organizations. AI, on the other hand, enables better, faster, and more automated decisions."
So now AI-based automation will transform these primarily human "HOW" tasks:
- Software will literally write itself, but who carefully defines the problem it needs to solve?
- Reports will appear at a command, but what exactly are we trying to analyse and understand?
- News articles will be magically written seconds after an event has occurred, but what are the larger strategic implications of publishing that information and if it gets it wrong then will you suffer the same fate as the Silicon Valley Bank just did?
- With process work the nexus of control is on monitoring and compliance - you know people are doing a good job because the process is good and you know it is being followed. Think procurement, risk audits, health and safety, etc.
- But with knowledge work, the capability is based on critical thinking, creativity, advanced problem solving, and many, if not most of these are not repetitive, not measurable against a simple benchmark. So how then do you manage the corporate capability for this?
- Finally, with knowledge work, the focus moves from outputs to outcomes. Something a little harder to both define and measure with numbers on a dashboard.
So how does Knowledge Management help?
The most important contribution management needs to make in the 21st century is similarly to increase the productivity of knowledge work and knowledge workers.”
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