Tag Archives: experimentation

Guinness beer, “absorptive capacity,” and innovation

August 8, 2015 By in exploration, idea landscapes, teams Tags: , , , , ,

In its everyday sense, to absorb something refers to our ability to take it in or soak it up or learn it well. But how do organizations absorb new knowledge or skills?

In Innovating Minds (p. 183), we explore what has been called the “absorptive capacity” of an organization. Absorptive capacity refers to:

“the ways in which teams and organizations evaluate, receive, and integrate new ‘external knowledge.’ [It] depends on their dynamic ability to recognize the value of new external information, assimilate it, and apply it. This capacity of an organization to productively absorb new information . . . applies not only to concepts but also to skills and meta-skills or ‘skills of skills,’ such as learning to learn. Appreciating the potential value of new information is something that may not come easily or automatically and needs to be fostered.”

So what’s this all got to do with Guinness beer and innovation?

Let’s travel back in time—to October 1899—in Dublin Ireland. The Guinness Brewery has just hired the young William Gosset, fresh out of New College, Oxford. Gosset’s stellar academic performance in math and chemistry has brought him to the attention of the company and he is recruited as a junior brewer. He will be joining four other recent recruits—all selected to spearhead a newly launched “scientific” approach to brewing.

Gossett soon is confronted with the very practical problem of what to make of the results of their many experiments with samples of malt and hops and plots of barley. Because of financial and other constraints, all of their experiments are based on very small sample sizes. It’s difficult to reach firm conclusions with such small samples because the numbers bounce around so much from one sample to the next.

He begins to see that standard practices won’t work and writes an internal company report suggesting a way forward. The report is well received.

But he and the company’s leadership realize that they need greater expertise and exposure to the very latest statistical methodology—that is only available outside the company. With this in mind, the company grants Gosset a one-year leave to go to England to study at University College London (UCL) with the pioneering statistician Karl Pearson.

Once at UCL, and working collaboratively with Pearson, Gosset recognizes that his small sample problems will require their own unique approach. This heralds the development of foundational insights that allow sound inferences to be drawn even from small sample sizes and a publication leading to what is now known as Student’s t-test. (If you have ever encountered this statistical test to compare two means, “Student” is a pseudonym adopted by William Gosset—see below.)

The fact that the company directly encouraged Gosset to leave Dublin to acquire deeper knowledge underscores that the organization understood the value of purposefully “absorbing” new knowledge and meta-skills into their idea landscapes. The company realized it needed to reach beyond its considerable internal expertise to draw on the insights and novel methods of others—extending its absorptive capacity.

Gosset_paper_1908

—> For further background see:

Phillip J. Boland (2011). William Sealy Gosset — An Inspiring ‘Student’,’ Proceedings of the 58th World Statistical Congress (Session STS028), pages 2650-2655.

Cycling Change

July 11, 2015 By in exploration, goals, making and finding Tags: , , , , ,

According to a recent article in The Guardian, more than one-quarter of trips in the Netherlands are made by bicycle (this rises to 38% in Amsterdam) versus only 2% in the UK. Yet, this wasn’t always so in Holland, especially in the 1970s—how did such a change come about?

As we read the article, we learn that the change was driven and carried by both bottom up and top down factors. Parents in neighborhoods were galvanized into action by the large number of child injuries and deaths caused by the influx, increasing dominance, and unquestioned prerogative of car traffic. The introduction of car-free Sundays in Amsterdam (a form of experiential variation) concretely reminded residents of what it had been like before the reign of the car.

Some obstacles to promoting the use of bicycles on city streets were not as unbudgeable as expected (e.g., even early on there was police receptivity and cooperation). External events and circumstances also played along, including steeply rising gas prices during the 1970s energy crisis. There was, too, a prescient recognition of the cumulative adverse health effects of air pollution from automobiles.

City-wide experimentation yielded new insights and provided crucial data. A pioneer city in the Netherlands tested the idea of a single bike route coursing through the city. Disappointing results from this approach prompted another city to successfully explore a more varied and networked multiple set of bike paths.

Even once new bicycle paths and infrastructure for cyclists were successfully implemented, change called for other changes—how to find spaces to park so many bicycles, the need for wider lanes to accommodate the increased number of cyclists, etc.

Change takes many forms. Sometimes we edge forward, sometimes we leap forward and at other times we need to step back. As we observe in Innovating Minds (page 171), “Change in organizations [and society] may concurrently arise from multiple sources, ranging from the planned to the emergent and from the internally to the externally driven: ‘In most organizations, transformations will occur through a variety of logics.’ ”

—> The quotation on the many logics of change is found on page 67 of: Orlikowski, W. J. (1996). Improvising organizational transformation over time: A situated change perspective. Information Systems Research, 7, 63–92.

Creativity friendly environments: Two examples

September 19, 2014 By in idea landscapes, making and finding, teams Tags: , , , , , , , , 1 Comment

What makes for a “creativity friendly” environment?

There is no single “one size fits all” answer… but here are some broader themes to think about. Let’s look at two recent examples through the lens of our iCASA framework.

(1) Shared learning and experimentation space

A very large Chinese factory that produced mobile phones had a massive open floor plan where the workers on the production lines and the supervisors were continually and readily seen. What would happen to production speed and quality if some of the lines were surrounded by a privacy curtain?

A field study with four production lines randomly chosen to be surrounded by such a curtain for several months found that the curtain increased improvisation, encouraged “productive deviance,” and led to higher productivity and quality. The comparative increase in team privacy afforded by the curtain allowed temporary, smaller issues to be solved locally through line-level learning and it promoted collective team knowledge.

Observations by embedded student researchers on the curtain-surrounded lines revealed that the workers actively switched roles to learn multiple tasks and enable team cross-support, fluid adaptation, experimentation, and learning.

The innovations that were observed “were a mix of preexisting and new ideas: some of these were ideas that were just waiting for an opportunity at experimentation, while others reflected novel learning on the line through the increased levels of experimentation the curtain enabled.’’ (Bernstein, 2012, p. 202)

The curtain allowed the line to collaborate and discuss new ideas and to iteratively test and try process improvements, arriving at successful prototypes before sharing them outside of their local idea landscape. It formed a “scrutiny-reduced” supportive making-and-finding environment where the workers and the line managers could adaptively and contextually experiment with an increased degree of autonomy.

—> For the research study, see Ethan S. Bernstein, The transparency paradox: A role for privacy in organizational learning and operational control, Administrative Science Quarterly, 57, 181–216. Also, see Bernstein’s, “The transparency trap”

(2) Cross-pollination at IKEA

IKEA’s product catalogs feature multi-color contemporary images of home furnishings in various natural looking settings. The company, though, was looking to move from its longstanding tradition of studio photography of its products to computer-generated images. Transitioning to computer-generated imagery would greatly reduce logistical and environmental costs because the many products would no longer need to be flown in and configured on site. Instead of physically creating multiple culturally specific settings, for example a typical Japanese kitchen, a German kitchen, and an American kitchen, computer-generated imagery would make such reconfigurations much simpler. But how could IKEA make this transition in a creativity-friendly way, while preserving catalog image quality and empowering employees throughout the change process?

The solution was simple and incisively creative: They started small scale, and then scaled up. After initial experimentation and demonstration of the feasibility of the computer-generated imagery process, all of IKEA’s studio photographers were required to learn to use the 3D computer generated process and vice versa. This in-depth cross-training extended the skills and understanding of both groups, and led to an increase in quality, with computer-generated images that were essentially indistinguishable from conventional photographs. There was a synergistic meeting of the two approaches to image making, and a fuller appreciation of the goals, aspirations, and constraints that each uniquely faced. The merging of techniques expanded and deepened everyone’s individual and shared idea landscapes and mental models. There was learning and unlearning at the same time.

—> For more background on the IKEA process, see: Kirsty Parkin, “Building 3D with IKEA”