Why hypotheses beat goals – Jeanne Ross

Jeanne Ross, Director & Principal Research Scientist at the MIT Sloan School's CISR

Jeanne Ross, Director & Principal Research Scientist at the MIT Sloan School’s CISR

From MIT Sloan Management Review 

Not long ago, it became fashionable to embrace failure as a sign of a company’s willingness to take risks. This trend lost favor as executives recognized that what they wanted was learning, not necessarily failure. Every failure can be attributed to a raft of missteps, and many failures do not automatically contribute to future success.

Certainly, if companies want to aggressively pursue learning, they must accept that failures will happen. But the practice of simply setting goals and then being nonchalant if they fail is inadequate.

Instead, companies should focus organizational energy on hypothesis generation and testing. Hypotheses force individuals to articulate in advance why they believe a given course of action will succeed. A failure then exposes an incorrect hypothesis — which can more reliably convert into organizational learning.

What Exactly Is a Hypothesis?

When my son was in second grade, his teacher regularly introduced topics by asking students to state some initial assumptions. For example, she introduced a unit on whales by asking: How big is a blue whale? The students all knew blue whales were big, but how big? Guesses ranged from the size of the classroom to the size of two elephants to the length of all the students in class lined up in a row. Students then set out to measure the classroom and the length of the row they formed, and they looked up the size of an elephant. They compared their results with the measurements of the whale and learned how close their estimates were.

Note that in this example, there is much more going on than just learning the size of a whale. Students were learning to recognize assumptions, make intelligent guesses based on those assumptions, determine how to test the accuracy of their guesses, and then assess the results.

This is the essence of hypothesis generation. A hypothesis emerges from a set of underlying assumptions. It is an articulation of how those assumptions are expected to play out in a given context. In short, a hypothesis is an intelligent, articulated guess that is the basis for taking action and assessing outcomes.

Hypothesis generation in companies becomes powerful if people are forced to articulate and justify their assumptions. It makes the path from hypothesis to expected outcomes clear enough that, should the anticipated outcomes fail to materialize, people will agree that the hypothesis was faulty.

Building a culture of effective hypothesizing can lead to more thoughtful actions and a better understanding of outcomes. Not only will failures be more likely to lead to future successes, but successes will foster future successes.

Why Is Hypothesis Generation Important?

Digital technologies are creating new business opportunities, but as I’ve noted in earlier columns, companies must experiment to learn both what is possible and what customers want. Most companies are relying on empowered, agile teams to conduct these experiments. That’s because teams can rapidly hypothesize, test, and learn.

Hypothesis generation contrasts starkly with more traditional management approaches designed for process optimization. Process optimization involves telling employees both what to do and how to do it. Process optimization is fine for stable business processes that have been standardized for consistency. (Standardized processes can usually be automated, specifically because they are stable.) Increasingly, however, companies need their people to steer efforts that involve uncertainty and change. That’s when organizational learning and hypothesis generation are particularly important.

Shifting to a culture that encourages empowered teams to hypothesize isn’t easy. Established hierarchies have developed managers accustomed to directing employees on how to accomplish their objectives. Those managers invariably rose to power by being the smartest person in the room. Such managers can struggle with the requirements for leading empowered teams. They may recognize the need to hold teams accountable for outcomes rather than specific tasks, but they may not be clear about how to guide team efforts.

Read the full post at MIT Sloan Management Review.

Jeanne W. Ross conducts academic research that targets the challenges of senior level executives at CISR’s nearly 100 global sponsor companies.

Is your organization ready for total digitization? — Peter Weill and Stephanie Woerner

Peter Weill and Stephanie Woerner (Image credit: Harvard Business Review)

From Harvard Business Review

What do the following items have in common: credit cards and streaming or recorded music, robots for production, CAD systems, telephone networks, digital games, computers in products like cars and vacuum cleaners, sensors, and video consoles used in remote mining? Answer: They are all digital and connectable.

This is the world of total digitization: a multitude of digital devices and sensors creating streams of data, as well as any number of digital services and products for both internal and external use, distributed throughout the enterprise, and sometimes, but not always, connected. As the drive toward increased digitization continues, enterprises have to get a handle on this total digitization — and corporate CIOs have to step up to the challenge.

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