To be successful, startups need to know how to fail early and fail fast, work with prototypes, engage in a lot of testing and a rapid iterative cycle of planning, doing, testing, assessing/learning and planning again. They need to be agile. They need to make decisions very quickly about a myriad of issues.
In that sense, they can benefit from knowledge management if they adopt practices that will support improved decision making based on rapid organizational learning. You don't conduct After-Action-Reviews or their equivalent every year, you incorporate an element of "pausing to learn" in every weekly core staff meeting and you make it a practice that gets disseminate as the organization expands so that it becomes part of the organizational culture.
In addition, startups are, by definition, small and immature organizations. They may lack organizational structures and governance because as long as they are small, they can get away with having very little formal structure. That may be exactly what is needed at that early stage of organizational development, but if they look ahead and think in terms of increasing maturity, they will want to pay attention to the inevitable emergence of organizational silos and preemptively set up information and knowledge structures and governance to ensure continuous knowledge sharing across the organization as it grows and evolves. Creating teams and giving them autonomy to go do what they do best is great but they will tend to go off and reinvent the wheel if they are allowed to, resulting in a multiplicity of tools, duplication of resources, proliferation of intranets and overlapping discussion forums, none of which will be integrated within a global vision of where the organization's knowledge resides and who to leverage it for the organization's benefit.
For something more substantive to read, see Piera Centobelli, Roberto Cerchione, and Emilio Esposito, "Knowledge Management in Startups: Systemic Literature Review and Future Research Agenda," Sustainability 2017, 9, 361.
Friday, January 19, 2018
Saturday, January 13, 2018
Learning More and/or Better
The following string of thoughts comes out of recent readings and meetings. As always, more questions to ask than answers to provide.
We can think about learning in two dimensions, quantitative and qualitative. Learning MORE is quantitative. Learning BETTER is qualitative.
I am inclined to think (or hypothesize) that learning MORE is a very incremental process whereas learning BETTER is potentially an exponential process. I don't really want to use the word "exponential" here and I certainly don't want to use the word "transformational". What I mean is that learning BETTER, addressing the qualitative dimension of learning is potentially more impactful than learning MORE.
It's the difference between the idea of continuous learning, which is simply about learning more over time, and the idea of learning HOW to learn, which is about becoming a better learner.
This manifests itself currently for me in terms of something as simple as reading. The number of books I will read this year is somewhat irrelevant. I am much more interested in developing, nurturing my capacity to engage in deep reading and deeper learning. There is some tension there because I could benefit from reading more broadly, which might translate into more books. The compromise might be scanning more books from a broad spectrum of disciplines but reading deeply a smaller subset of those books.
Reading now: Humility Is the New Smart: Rethinking Human Excellence in the Smart Machine Age, by Edward D. Hess and Katherine Ludwig.
We can think about learning in two dimensions, quantitative and qualitative. Learning MORE is quantitative. Learning BETTER is qualitative.
I am inclined to think (or hypothesize) that learning MORE is a very incremental process whereas learning BETTER is potentially an exponential process. I don't really want to use the word "exponential" here and I certainly don't want to use the word "transformational". What I mean is that learning BETTER, addressing the qualitative dimension of learning is potentially more impactful than learning MORE.
It's the difference between the idea of continuous learning, which is simply about learning more over time, and the idea of learning HOW to learn, which is about becoming a better learner.
This manifests itself currently for me in terms of something as simple as reading. The number of books I will read this year is somewhat irrelevant. I am much more interested in developing, nurturing my capacity to engage in deep reading and deeper learning. There is some tension there because I could benefit from reading more broadly, which might translate into more books. The compromise might be scanning more books from a broad spectrum of disciplines but reading deeply a smaller subset of those books.
Reading now: Humility Is the New Smart: Rethinking Human Excellence in the Smart Machine Age, by Edward D. Hess and Katherine Ludwig.
Wednesday, January 03, 2018
Why We Need Contrarians
I don't make New Year's resolutions. I have a variety of reasons for not doing it, but at least one of them is that I like being a contrarian. When the crowd is doing something just because everyone in the crowd seems to be doing it, I resist.
More seriously, and in a professional context, being aware of the fact that each time I write publically about monitoring and evaluation (M&E), I run the risk of never getting hired to do M&E work, simply because of my skepticism and at times contrarian opinions. And yes, these are opinions. I don't claim to be correct while everyone else is wrong. I just wish people would stop and think rather than follow the crowd. Admitedly, following the crowd is much easier. You get pushed by its forward motion, going downhill like the little grey people in the picture above. When going in the other direction, not only are you going uphill but you have to fight your way through a crowd of opposing views.
Today, I will point to research that may support at least some aspects of my thinking and validate my conviction that we need contrarians. Not surprisingly, it has to do with a cognitive bias, the resulting fallacy.
I first encountered this fallacy through a simple case study run by NASA and developed in collaboration with academics researching decision-making. The case study describes a mission that was ultimately successful but was considered a near-miss. In other words, it benefited from a certain amount of luck and it could have been a complete failure. The learning objective of this case study is that people draw conclusions about decisions made based on the outcome. The mission succeeded, therefore the decisions must have been good. People studying decision-making and focusing on the resulting fallacy say, "not so fast." You cannot say much about the quality of a decision based solely on the outcome.
What does the resulting fallacy have to do with being a contrarian you ask. It points to the need for more in-depth analysis of cause and effect and the thinking behind our decisions. We need more contrarians who are ready to raise their hand and say "not so fast."
Why be a contrarian? Someone has to. When 99% of the people in a particular industry or discipline are jumping on a bandwagon, I like to be the one standing back and watching. It's not that I don't ever jump on bandwagons. I do. There are some bandwagons however where I get tickled and I go, "wait a minute... something is fishy. I don't know what it is yet but I'm not getting on that one."
I like poking and prodding when I see the bandwagon passing by. Being a contrarian doesn't make me right. I can make me useful. There's always a role for a devil's advocate, a skeptic who will force others to articulate their positions and assumptions.
This is also related to the importance of allowing dissenting opinions in organizations, but that's a topic for another post perhaps.
Resources
"Do you have a contrarian on your team?", Insights by Stanford Business, November 13, 2015, by Elizabeth MacBride.
"The Resulting Fallacy is Ruining Your Decisions," by Stuart Firestein, December 7, 2017.
"Understanding Near-Misses at NASA," ASK OCE, August 17, 2006, Vol. 1, Issue No. 12.
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