Thursday, January 11, 2018

Between Guardrails: How Organizations Handle Mission Contradictions

Digital Divide Data (DDD) is a commercial enterprise doing data-entry work for profit. It is also a social enterprise that trains Cambodians to obtain better jobs than the ones they do for DDD. Is that a contradiction? Maybe it is not fully contradictory but instead just a tension—one that many social enterprises handle because they need to sustain themselves commercially, not just do good work. We have long known that the dual purpose of social enterprise is seen as a contradiction internally and can lead to various problems and coping strategies, but we have not known much about the long-term effects.

Now we know more, thanks to an article in Administrative Science Quarterly by Wendy Smith and Marya Besharov. They followed DDD for more than ten years, seeing it as a great example of the effects of how such contradictions are dealt with over a long time. It is a great example both because DDD has coped with them well, while many other organizations break apart or fail, and because it has faced a particularly difficult tension between its commercial and social work, as the commercial work has slim margins and some of the social activities can undermine it seriously.

What do we learn from DDD? As you might expect, the answer to such contradictions has more than one part, but here I want to describe just one: guardrails. Establishing guardrails is a way to set up the organization that follows some old organization theory almost to the book, although the DDD founders may not have been aware of it. In a hybrid organization like DDD, whose commercial and social activities are both important, one of the many possible solutions is to make sure that the organization holds strong advocates of each one and is not set up to let one type of activity dominate. That setup results in a battle for dominance between these advocates and between the coalitions they can muster for support whenever a critical problem arises.

That sounds like a noisy and costly way to organize, and it is. But its key feature is that the battles arise whenever one coalition sees the organization as going too far in one direction and neglecting the other, and the battles help to pull it back to the center. As long as the organization can balance its activities, it is peaceful. That’s why competing advocates and coalitions function as guardrails – they keep the organization from going off track and favoring one mission over the other.

The reason this is important is that hiring advocates for contradictory positions without giving priority to one looks like a way to generate problems for the organization. There is not one overriding mission, there is not a clear organizational identity, it is not possible to predict when conflicts will start, and it is hard to predict how they will end. But all these frightful sources of noise help stabilize the organization and resolve the tension between its contradictory goals and activities.


Thursday, January 4, 2018

The Different Uses of Training: Training to Retain First-time Workers

Firms often train workers, and nearly always for very specific reasons. We are most familiar with how they teach specific skills for their equipment and procedures, including re-training people when these change. Whether we’ve taken such training ourselves or have worked with assistants or administrators who have done so, we understand that such training is important for both the organization and the worker: it should help the worker produce more valuable output (which they can share), and it is more valuable if the organization can retain the worker on the job longer after training.

But the reality is that many workers don’t stay on the job very long, either because they experience a lack of fit with the employer or they have difficulty meeting the organization’s expectations of them as an employee and continuing to manage their responsibilities outside of work. This is especially true for women entering the workforce for the first time whose domestic roles haven’t prepared them for work. It is also true for people with self-employment backgrounds such as families doing farming or craftwork. Such first-time workers are the focus of an article in Administrative Science Quarterly by Aruna Ranganathan, who studied women entering the workforce for the first time as employees of a garment factory in India. Many of these women didn’t last long on the job: about a third left within three months of hiring.

As expected, the employer provided training to help new workers get up to speed. But what was unusual is that the content of the training differed depending on the trainers’ experience, and the content made a big difference in attrition rates. Ranganathan found that less-experienced trainers in the factory focused on teaching the new employees assigned to them only job-specific skills, such as how to use a sewing machine. These trainers saw their goal as teaching the “equipment and procedures” knowledge I referred to before. More-experienced trainers taught job-specific skills and also provided more general work-readiness training that focused on skills related to self-presentation, interpersonal communication, work–life separation, and self-reliance.

Clearly this is a different form of training because it is a way of socializing the first-time women workers, helping them feel comfortable in their workplace, behave as expected, communicate well when needed, and work independently when needed. These activities are natural for many people who are socialized into workplaces early in life through exposure to an organization such as a university or a business. The women studied by Ranganathan came from rural villages, where such socialization is hard to get. Successful work-readiness training, which decreased the numbers of women quitting shortly after they were hired, was important both for the firm and the employees: re-hiring is costly for the firm, and leaving paid work as a result of lack of fit hurts these women’s income and further employment chances.

Socialization training was different from job-specific training because the trainers didn’t work from a checklist of skills to impart. Instead, the experienced trainers seemed to have a natural understanding of what the new workers could experience as problems; they taught new employees how to get to work on time in the morning, showed them where the bathroom was, and encouraged them to take breaks for drinks of water, for example. Without the benefit of a checklist of such seemingly simple (yet clearly important) skills to teach, less-experienced trainers didn’t teach them, perhaps because they didn’t understand the importance of such work-readiness skills.

We rarely think of training as having such general goals to help employees feel ready to work. We rarely think of socialization as happening through training rather than through workers interacting formally. We rarely study how developing nations modernize through having people who were earlier engaged in farming or housework taking on the role of paid employees. Ranganathan’s research is eye-opening because it is right in the middle of so many important and neglected topics.



Tuesday, December 26, 2017

Teams at Work and Lives at Stake: How to Handle Fast-Paced Complexity

There is a lot of research on how teams make disasters happen, and the answer is clear: teams use cues to make sense of the situation, and disasters happen when sensemaking differs from reality. That’s useful to know, but we would also like to know how it can be prevented. We know that expertise and experience do not help. Experienced commercial pilots, space shuttle subcontractor engineers, chemical plant operators, and fighter pilots have all been studied and found to do faulty sensemaking.  The examples I just gave have led to a total of 4,000 confirmed deaths and more than 10,000 likely deaths.

Finally, an article in Administrative Science Quarterly by Marlys Christianson has some answers. She studied how medical teams went through an emergency room training procedure – treating a young asthma patient with increasing breathing failure – in a simulation designed to invite incorrect sensemaking in the beginning, so they would need to recover later. Fortunately, in simulations the patients are not real, because one quarter of them would have died. Even among the teams that managed to identify and correct the problem (replacing a piece of broken equipment), the speed of doing so varied a lot, so thanks to this research we now know a lot more about how sensemaking can recover.

Teams are in organizations for doing work, not for solving puzzles.  Whenever a situation involves a puzzle that needs to be solved, such as faulty sensemaking that needs to be corrected, the regular work done by the team takes effort and attention away from the correction. This means that cues that may look obvious to someone outside the team are not at all clear to team members who are focused on the regular work and who do this work premised on their sensemaking. In an emergency room, the team will look for cues to how the patient is doing, but they spend much of their time treating the patient. Treating and observing clues are related, but they compete for time.

This means that emergency room teams can solve puzzles only if they manage two trajectories at once – the regular treatment and the interpretation of cues from the patient’s condition. The interpretation trajectory is how sensemaking is updated, and it is complex because it moves from noticing cues that suggest something is wrong, to interpreting them to indicate what the problem is, to acting to check the interpretation. Usually the actions involve changing the treatment, so treatment and interpretation need to be in sync. The trajectory management can fail in multiple places. For example, the treatment takes too much time so cues are not interpreted, or the treatment is based on current sensemaking so changing it to check interpretation does not make sense.

The emergency room teams had a sensemaking problem because the simulation was designed to involve treatment equipment that did not work correctly, so the usual sensemaking (“our equipment works, so all problems can be found in the patient”) was faulty. Similar sensemaking problems are found in many places. In the Black Hawk shooting incident, the fighter pilots saw helicopters without correct friend–foe identification signals and concluded they would be hostile because friendlies signal who they are. Any cues they could see were drowned out by the tasks of flying the aircraft low in mountainous terrain, keeping alert for possible threats, and going through a modified foe identification and engagement procedure while communicating with each other.

Trajectory management can easily fail, with tragic consequences. Now that we know more about the differences between teams that succeed and teams that fail, we may be able to work to make teamwork more reliable, especially when lives are at stake.



On a personal note, I’ve experienced the benefits of the sort of updated sensemaking described in the article.  When I was in the emergency room after an accident, the team scanned me to look for internal bleeding based on their experience of how body folding from being hit by a car while riding a motorcycle can break blood vessels. They found none. The cue of falling blood pressure after closing the external wounds made them re-scan over a broader range, and they found the broken vessel and fixed it. I am alive, thanks to the team’s updated sensemaking.

Wednesday, December 20, 2017

A Paradox of Innovation: Those Who Do It May Be Ignored

We are supposed to like innovations. They drive the world forward, with effects that range from the pleasant (like the camera on your phone) to the vital (like portable ultrasound in developing nations). In fact, many of the heroes in business are known because of their innovations. A classic example is Steve Jobs launching the multi-function iPhone, which relied on knowledge of music storage and playoff, as well as internet connectivity, that previously had not been part of mobile phone technology. This is one of the two classical stories on how to innovate: combine existing knowledge in new ways, or create completely new knowledge.

The only problem with the iPhone story is that it makes us think the world rewards innovation and that firms doing it get Apple-like fame and fortunes. That happens to be the exception. A research paper by Matt Theeke, Francisco Polidoro, and James Fredrickson in Administrative Science Quarterly has shown that firms using new kinds of knowledge for making innovations face a surprising form of risk: they may end up getting ignored.

The details of this research help us see exactly what happens. All kinds of firms want stock brokerage firms to issue analyst reports on them, because that means investors will pay attention to them, which helps them gain financing. This is especially important for firms that rely on innovations, because making innovations means paying money now to get money later, which is exactly what financing is used for. In fact, there are entire industries that are so dependent on innovations that analyst reports are essential. Theeke, Polidoro, and Fredrickson studied medical devices, which is a good example of an innovation-driven industry. Brokerage firms covering that industry need to understand research and knowledge use, because otherwise they cannot estimate future profits well.

So what is the problem?  Well, the brokerage firms have expertise in the conventional use of knowledge, which means that use of new knowledge – innovative use of knowledge – is something they understand less well. As a result, firms incorporating new knowledge are more likely to be ignored, as brokerages drop them from their coverage. The newer the knowledge is, and the more expertise the brokerage firm has in covering other firms in the industry using conventional knowledge, the worse the situation is. Just as expertise makes some firms rigid in their knowledge use, it makes brokerage firms rigid in their knowledge valuation.

So our tales of heroic unconventional innovators are good examples of exceptions, because business rewards convention. Does that mean it is better to follow convention and just make minor improvements? Not really, because easier access to financing is very different from more successful product launches. It just means that firms planning to use new knowledge in making innovations should check their bank accounts first, because they may have to pay the cost themselves.

Friday, December 15, 2017

Open Innovation and Closed Minds: Why NASA Used Open Innovation Sometimes but Not Always

Open innovation is heralded as a way to advance technology and product innovation quickly and cheaply. It is modeled on the open source software movement, which is based on computer programmers donating their time to build software components, check their own work, check others’ work, and correct mistakes. Among the famous software suites made through open source, Linux is a computer operating system that is used in everything from cellular phones to web servers, and is often involved when you are retrieving and reading blog posts like this one. Open innovation extends this model to innovations outside computer programming by organizations posting problems that anyone interested can help solve.


The idea is to use volunteer efforts to get innovations for free (almost a Dire Straits lyric), which sounds like a good deal. Unfortunately, this has proven difficult for many organizations, and research in Administrative Science Quarterly by Hila Lifshitz-Assaf has found out why. Her careful study looks at an open innovation initiative in a very innovative high-tech organization: NASA. In 2009, NASA tried an open innovation experiment that led to some speedy, inexpensive, and impressive solutions. But its relationship with open innovation since then has been inconsistent, with some NASA professionals using it to great success and some not. Why the difference?

In a word, the difference is identity. Innovations are typically done by highly educated people who are trained to follow careful processes specific to their organization and to their scientific and technological specialization. These people have a professional identity built around their unique skills as problem solvers for the organization. For people with such an identity, what does it feel like to have amateurs solve problems instead of them? Open innovation draws much of its strength from individuals who may lack formal education, don’t follow the predefined process, and aren’t even employees of the organization. Naturally there is an inherent conflict between the insiders and the open innovation use of outsiders, and some insiders are tempted to seal the organization off from the outside sources of innovations.

Why did some parts of NASA embrace open innovation? Again the answer is identity. Those who could redefine their professional identity to be a solution seeker, not a problem solver, became adept users of open innovation. For a solution seeker, the existence of a solution is what matters – not who made it, and not how it was made. It is a completely different way of thinking of oneself and of solving problems.

The division between problem solvers and solution seekers resulted in NASA professionals adopting various approaches to the open innovation initiatives advocated by their leadership. Problem solvers maintained boundaries, either explicitly or through the pretense of openness but actual closure. That way they could maintain their focus on their individual efforts and internal innovations. Solution seekers looked for outside solutions, sometimes simply embracing externally developed solutions, and sometimes adapting external solutions so that the final solution became a mixture of outside and inside effort. Problem solvers may hold tight to their identity, but open innovation is sure to continue gaining ground. “Get your innovations for nothing, get your praise for free” is an appealing tune.  

Lifshitz-Assaf, Hila.2017. "Dismantling Knowledge Boundaries at NASA: The Critical Role of Professional Identity in Open Innovation." Administrative Science Quarterly, Forthcoming.

Thursday, December 7, 2017

Minimally Invasive Investment: How Ventures Interact with Investment Partners

Of the many kinds of new businesses that are created every year, researchers and policy makers have been most interested in the ones that pursue innovative technologies and market opportunities. They are the ones with the greatest impact on the world, and much effort has gone into studying what makes them innovative. But let’s take a broader view on this question. What if firms around them also affect their innovation – specifically their investment partners, firms that supply them with money and expect returns from their innovations? The answer would be especially interesting if different investment partners had different effects. And as it turns out, they do.

An article in Administrative Science Quarterly by Emily Cox Pahnke, Riitta Katila, and Kathleen Eisenhardt shows how this happens. The important difference is how each organization doing investment has people trained in specific ways, and adhering to specific norms, as a result of their recruitment and career histories. For innovative ventures, venture capital (VC) firms are special because they invest in potential – in firms that could easily fail, and usually do, but have very significant profits when they succeed. VCs are different from sources of corporate venture capital (CVC), which are investment arms of corporations. They are special because they invest in fit to the corporate strategy – firms that develop products and technologies that match so well that they can become integrated into the corporation or at least use its resources well. Then there is the third kind of special investor—government agencies. They are special because they are interested in science and technology with significant societal impact.

Pahnke, Katila, and Eisenhardt looked at what happened to ventures after receiving funding from each of these sources by examining a specific high-technology industry—medical device firms developing products for minimally invasive surgery. The results were clear. The commercially oriented VC investors were good at exactly that. Their firms launched more products after the investment but did not get more patents approved after the investment. The strategically oriented CVC partners were not good at anything that could be measured independently of their strategy. No more patents were approved, and no more products were launched. That does not mean they weren’t good investors, because they could well have selected and improved the strategic fit of their firms. The government was not good at product development, having no effect there, and appeared to harm patenting, with a reduction in patents after entering the investment. That seems bad—but it is actually unclear, because government may be interested exactly in the type of scientific development that is useful for society but hard to turn into patents that give commercial benefit.

So what is going on here? We can tell that one type of investment partner – VCs – has clear and measurable goals and is good at accomplishing them. For CVC and governments, it is harder to tell. Either they are not doing well, or their goals are not exactly what we can measure. Looks like an interesting topic for further research, because each of these investment partners places big bets on our future.

Pahnke, Emily Cox, Riitta Katila, and Kathleen M Eisenhardt.2015. "Who takes you to the dance? How partners’ institutional logics influence innovation in young firms." Administrative Science Quarterly 60(4):596-633.

Friday, December 1, 2017

When Nanotechnology Shrank: How Communities Police the Boundaries of Their Field

It is ironic that I should write a post on how communities of science police the boundaries of their field shortly after writing a blog post on how nations hurt themselves by policing their boundaries. But a paper in Administrative Science Quarterly by Stine Grodal has exactly that theme and some important conclusions. Plus, it is about nanotechnology, something we have heard about and think will shape the future of the world but don’t understand well.

In fact, what I just wrote echoes the start of the nanotechnology field. It was a term coined and advocated by futurists, it was and still is claimed to be a source of advances in science, technology, and business that will change individual lives and society, and it has been redefined many times. The redefinitions of the field are important because they are partly a consequence of these futurists and others with an interest in the term, especially the government, grappling with the question of how best to define the boundaries of the nanotechnology field so that it attracts the right kind of support from others and makes the kind of advances that are desired.

Nanotechnology became a very successful field, in part because of government intervention in the traditional way: giving out money to those engaged in research on nanotechnology. The other source of success was interest in nanotechnology companies from venture capitalists, who expressed their interest the same way: they provided money. This initiated an identity crisis because it soon became clear to the futurists that there were many in the world with little interest in their vision but significant interest in money and other resources that were becoming available, and they had the ability to fit their activities into the loosely defined field of nanotechnology. After all, entrepreneurs are well known for creativity in the pursuit of funding, and scientists are (this is less well known) extremely creative in the pursuit of funding.

The result was a backlash. The creators of the field, the futurists, looked at all the newcomers and their flexible definitions of nanotech, and thought they were changing the meaning of the term and were pursuing different futures than the one originally envisioned. Government officials saw a flood of funding applications and realized that the topics were too spread out to provide any kind of consistency unless the funding agency enforced it. Government interest in nanotechnology started with the futurists’ initiatives, so officials could ask the futurists for help in making a stricter definition of the field. The futurists were pleased to help, given that the field was losing clarity and they were losing funding as competition increased. Interestingly, even some interlopers such as scientists and entrepreneurs started rethinking the meaning of nanotech, seeing it as too trendy a term and not well enough connected to their work.

Nanotech started out as a word with a clear symbolic vision and few adherents. Money was added, and it became unclear and populated with many newcomers, members of peripheral communities. This makes sense. The next step is the surprise, because everyone in the field started looking around and seeing a need to sort things out. The founders and funders of the vision stayed, and the newcomers started leaving. That’s how nanotech shrank, and it could well be how many other fields expand and contract over time.