Managers and employees spend much of their time in discussions, but too often conversations bog down in an endless series of unproductive meetings in which the usual suspects cover the same ground without making progress. Frustration mounts as participants “spin their wheels” or “talk in circles.” This frustration often occurs when managers lead the wrong kinds of discussions at the wrong time in the wrong way.
My last post introduced the agility loop as a simple framework to helm managers and employees structure and lead discussions in a more effective manner. The first step in structuring and leading discussions through the agility loop consists of deciding which discussion to have when, who should be involved, and how to lead these conversations. The following questions can help managers improve their discussions.
1. What are we talking about? This simple question often surfaces a disturbing lack of focus about the objective of a discussion. Discussions, particularly those that take place in large groups, often derail when participants pursue multiple strands simultaneously and end up talking past one another. To focus their brainstorming discussions, the design firm IDEO enforces a rule that a team can only discuss one idea at a time.
2. Are the right people in the room? Conversations often fail before they begin, when team leaders fail to bring
How can managers build organizational agility in turbulent markets? My recent posts have discussed how fighter pilots, software engineers, entrepreneurs, scientists, and venture capitalists achieve agility by proceeding into the future through a series of iterative loops. It is easy to envision a fighter pilot going through a series of iterative loops of observing the situation, orienting himself, deciding what to do, acting, and then repeating the cycle over again. Leaders in large organizations must coordinate complex activities across diverse units where people have different world-views, values, time-frames and priorities.
The complexities of achieving agility in large, complex organizations raises a series of thorny questions: How can a managers from different functions and geographies develop a shared understanding of a situation is in flux? Given uncertain outcomes, how can they decide which initiatives to pursue and which to kill? How can they prevent priorities from proliferating? How can they agree on what to stop doing? How can they execute against objectives that shift as new information comes to light? How can they make mid-course corrections in light of new information?
To understand how to enhance agility in large, complex organizations it helps to go back to basics, and remember that management, at its heart, consists of getting things done through discussions with other
Entrepreneurs and managers can consciously design experiments to surface flaws in their business plan and spur revision. An entrepreneurial experiment, as I use the term, is a test designed to reduce uncertainty critical to success before committing additional resources. Common examples include customer research, prototypes, regional service, and beta customers. Based on the results of these experiments, entrepreneurs may decide to cut their losses, revise their working hypothesis and run another experiment, or harvest the value they have created. Below are some examples.
- Identify the deal killers. Every plan includes countless assumptions. Rather than worrying about all of them, an entrepreneur should identify potential deal killers, variables that could prove fatal. Deal killers vary: In commercial real estate development, title disputes or environmental liabilities could scotch a deal, while a software start-up faces a deal-killer if a deep-pocketed rival has a valid claim on the underlying intellectual property. Deal killers are often discernible early on, and managers and entrepreneurs should try to surface these critical source of uncertainty early. New deal killers may appear as the venture proceeds, while others prove tractable.
- Know what you are betting on. In turbulent markets, multiple variables influence the an opportunity’s
Entrepreneurs can pursue an opportunity much as scientists pursue knowledge–by following a disciplined process of identifying an anomaly in the market, formulating a plan to fill the gap, testing their plan in the real world, and revising their assumptions in light of new information. Menlo Park based ONSET Ventures, a venture capital firm focused on fledgling start-ups, has codified a set of practices that increase the odds that entrepreneurs formulate, test, and revise their working hypothesis in a disciplined fashion.
Since its founding in 1984, ONSET has backed over 100 early stage start-ups, 80% of which have gone on to receive subsequent rounds of financing, a much higher success rate than the average for investments in raw start-ups. When they co-founded ONSET in 1984, Terry Opdendyk and David Kelley (who also founded IDEO) conducted a systematic study of 300 seed stage ventures, with an eye to understanding the factors that influenced their ultimate success or failure. They found that a few factors accounted for most of the variation between successful and failed start-ups, and codified these findings into a set of principles for incubating new ventures.
- Simplify the working hypothesis. When selecting potential investments, ONSET partners use a set of
My last post described Karl Popper’s cycle that explains how scientists spot anomalies in existing theory, formulate a working hypothesis, submit it to rigorous testing, then revisit their hypothesis in light of new information. Entrepreneurs, it turns out, can exploit opportunities much like scientists pursue knowledge, by spotting a gap in the market, formulating a business plan to fill that gap, and then running experiments in the market, and revise their plan in light of new information.
- Notice a gap in the market. In the first step, the entrepreneur or manager notices an anomaly in the market that may point to a potential opportunity. Typical anomalies include a product that shouldn’t sell but do or customers using a product in an unexpected way. Consider Noodles & Company, a chain of
In the early Twentieth Century, most people viewed scientific hypotheses as theories that had not yet been proven. The philosopher of science Karl Raimund Popper flipped this view on its head, and argued that any theory-even one as well–established as Newtonian physics–was simply a hypothesis that had not yet been disproved.
Popper viewed science as a Darwinian struggle for survival between competing theories. Every theory is an imperfect representation of reality and vies for preeminence by surviving experimental scrutiny in the real world. Rigorous testing weeds out weaker theories, leaving only the strong to survive. Eventually, further experiments expose the flaws of the survivors, and yet stronger theories replace them as well. Science, for Popper, was a permanent battle for survival.
The engine that drives scientific progress, in Popper’s view, was an unending cycle that iterated between spotting an anomaly, formulating a working hypothesis, and submitting that theory to empirical and logical scrutiny to identify defects, steps elaborated below.
- Notice an anomaly. The cycle begins when a scientist bypasses a theory’s strong points to search out its