Strategy. Innovation. Brand.

Strategy

Innovating The Innovations

It's a mashup!

It’s a mashup!

Mashup thinking is an excellent way to develop new ideas and products. Rather than thinking outside the box (always difficult), you select ideas from multiple boxes and mash them together. Sometimes, nothing special happens. Sometimes, you get a genius idea.

Let’s mash up self-driving vehicles and drones to see what we get. First, let’s look at the current paradigms:

Self-driving vehicles (SDVs) include cars and trucks equipped with special sensors that can use existing public roadways to navigate autonomously to a given destination. The vehicles navigate a two-dimensional surface and should be able to get humans or packages from Point A to Point B more safely than human-driven vehicles. Individuals may not buy SDVs the way we have traditionally bought cars and trucks. We may simply call them when needed. Though the technology is rapidly improving, the legal and ethical systems still require a great deal of work.

Drones navigate three-dimensional space and are not autonomous. Rather, specially trained pilots fly them remotely. (They are often referred to as Remotely Piloted Aircraft or RPAs). They military uses drones for several missions, including surveillance, intelligence gathering, and to attack ground targets. To date, we haven’t heard of drones attacking airborne targets, but it’s certainly possible. Increasingly, businesses are considering drones for package delivery. The general paradigm is that a small drone will pick up a package from a warehouse (perhaps an airborne warehouse) and deliver it to a home or office or to troops in the field.

So, what do we get if we mash up self-driving vehicles and drones?

The first idea that comes to mind is an autonomous drone. Navigating 3D space is actually simpler than navigating 2D space – you can fly over or under an approaching object. (As a result, train traffic controllers have a more difficult job than air traffic controllers). Why would we want self-flying drones? Conceivably they would be more efficient, less costly, and safer than the human-driven equivalents. They also have a lot more space to operate in and don’t require a lot of asphalt.

We could also change the paradigm for what drones carry. Today, we think of them as carrying packages. Why not people, just like SDVs? It shouldn’t be terribly hard to design a drone that could comfortably carry a couple from their house to the theater and back. We’ll be able to whip out our smart phones, call Uber or Lyft, and have a drone pick us up. (I hope Lyft has trademarked the term Air Lyft).

What else? How about combining self-flying drones with self-driving vehicles? Today’s paradigm for drone deliveries is that an individual drone goes to a warehouse, picks up a package, and delivers it to an individual address. Even if the warehouse is airborne and mobile, that’s horribly inefficient. Instead, let’s try this: a self-driving truck picks up hundreds of packages to be delivered along a given route. The truck also has dozens of drones on it. As the truck passes near an address, a drone picks up the right package, and flies it to the doorstep. We could only do this, of course, if drones are autonomous. The task is too complicated for a human operator.

I could go on … but let’s also investigate the knock-on effects. If what I’ve described comes to pass, what else will happen? Here are some challenges that will probably come up:

  • If drones can carry people as well as packages, we’ll need fewer roadways. What will we do with obsolete roads? We’ll probably need fewer airports, too. What will we do with them?
  • If people no longer buy personal vehicles but call transportation on demand:
    • We’ll need far fewer parking lots. How can cities use the space to revitalize themselves?
    • Automobile companies will implode. How do we retrain automobile executives and workers?
    • We’ll burn far less fossil fuel. This will be good for the environment but bad for, say, oil companies and oil workers. How do we share the burden?
  • If combined vehicles – drones and SDVs – deliver packages, millions of warehouse workers and drivers will lose their jobs. Again, how do we share the burden?
  • If autonomous drones can attack airborne targets, do we really need expensive, human-piloted fighter jets?

These are intriguing predictions as well as troublesome challenges. But the thought process for generating these ideas is quite simple – you simply mash up good ideas from multiple boxes. You, too, can predict the future.

Us Versus Them

"The school bus broke down!"

“The school bus broke down!”

How easy is it for an us-versus-them situation to arise? How often do we define our group as different from – and therefore better than – another group? The short answers: It’s surprisingly easy and it happens all the time.

In my professional life, I often saw us-versus-them attitudes arise between headquarters and the field. Staffers at head-quarters thought they were in a good position to direct field activities. People in the field thought the folks at headquarters just didn’t have a clue about the real world.

Headquarters and the field are typically separated by many factors, including geography, planning horizons, rank, age, academic experience, and tenure. Each side has plenty of reasons to feel different from – and superior to – the other side. But how many reasons does it take to generate us-versus-them attitudes?

In the early 1970s, the social psychologist Henri Tajfel tried to work out the minimum requirements for one group to discriminate against another group. It turns out that it doesn’t take much. People who are separated into groups based on their shirt color develop us-versus-them attitudes. People who are separated based on the flip of a coin do the same. Tajfel’s minimal group paradigm is quite simple: The minimum requirement to create us-versus-them attitudes is the existence of two groups.

Us-versus-them attitudes are completely natural. They arise without provocation. There’s no conspiracy. All we need is two groups. I sometimes hear managers say, “Let’s not develop us-versus-them attitudes here.” But that’s completely unnatural. Something about our human nature requires us to develop such attitudes when two groups exist. It can’t not happen.

We can’t avoid us-versus-them attitudes but we can dissolve them. We can’t stop them from starting but we can stop them once they have started.

The pioneering research on this was the Robbers Cave Experiment conducted in 1954. Muzafer and Carolyn Sherif, professors at the University of Oklahoma, selected two dozen 12-year-old boys from suburban Oklahoma City and sent them off to summer camp at Robbers Cave State Park. The boys were quite similar in terms of ethnicity and socioeconomic status. None of the boys knew each other at the beginning of the experiment.

The boys were randomly divided into two groups and housed in different areas of the campground. Initially, the groups didn’t know of each other’s existence. They discovered each other only when they began to compete for camp resources, like playing fields or dining halls. Once they discovered each other, they quickly named their groups: Rattlers and Eagles.

So far, the boys’ behavior was entirely predictable. The research question was: How do you change such behavior to reduce us-versus-them attitudes?

The researchers first measured the impact of mere contact. The researchers thought that by getting the boys to mingle – in dining halls or on camp buses, for example – they could overcome negative attitudes and build relationships. The finding: mere contact did not change attitudes for the better. Indeed, when contact was coupled with competition for resources, it increased friction rather than reducing it.

The researchers then moved on to superordinate goals. The two groups had to cooperate to achieve a goal that neither group could achieve on its own. For example, the researchers arranged for the camp bus to “break down”. They also arranged for the water supply to go dry. Rattlers and Eagles had to work together to fix the problems. The finding: cooperation on a larger goal reduced friction and the two groups began to integrate. Rattlers and Eagles actually started to like each other.

The research that the Sherifs started has now grown into a domain known as realistic conflict theory or RCT. The theory suggests that groups will develop resentful attitudes towards other groups, especially when they compete for resources in a zero-sum situation. According to Wikipedia, RCT suggests that “…positive relations can only be restored if superordinate goals are in place.”

The moral of the story is simple: you can’t prevent us-versus-them attitudes but you can fix them. Just find a problem that requires cooperation and collaboration.

 

 

Managing The Matrix

Task: Assemble the best team.

Task: Assemble the best team.

One of my largest clients is re-engineering its organization to focus on functions rather than geographies. It’s a classic move from top-down management to matrix management. I think it’s very much the right thing to do but it’s making some of the managers nervous. How does one shift from managing a team to managing a matrix?

I went through a similar transition at Lawson, the last major software company that I worked for. We transitioned from geographies – Sweden, Western USA, Australia/New Zealand – to global teams that focused on vertical markets like healthcare, food and beverage, and fashion. We focused on industries rather than geographies and became expert advisors to our customers.

And what did I learn about managing in a matrix? Here are the key ideas that stood out for me.

Connectors succeed – in a geographic organization, a manager gets to know her team and learns how to accentuate their strengths and minimize their weaknesses. Team members are often physically close to each other. There’s no need to connect them; they’re already connected. In a matrix, the ability to connect people is the most important single skill. People who are natural connectors are often the best matrix managers.

Diplomacy counts – diplomacy is a useful skill for any manager. It’s especially important in a matrix. In a top-down organization, a manager could simply give orders without much tact or diplomacy. Not so in a matrix. A matrix manager is forever building teams – one team to address Issue X, and another to address Issue Y. A matrix manager is always recruiting and needs a positive attitude, good diplomatic skills, and a good understanding of what motivates people.

A good manager can build all-star teams – let’s say I wanted to sell Lawson software to the Swedish fashion house, Filippa K. With the right diplomatic and connecting skills, I could assemble an all-star team to sell the account. My team might include a design expert from New Zealand, a cut-and-sew expert from New York, and a retail expert from Stockholm. I pull them together and focus them intently on the task of selling to Filippa K. Once they sell the account, the team dissolves and the team members reassemble — perhaps with other teammates – to focus on a different project. The good news is that a matrix manager gets to work with all-stars all the time. The not-so-bad news is that a successful matrix manager needs to continually assemble and re-assemble teams in ever-changing patterns.

Talent spotting becomes more important– in a geographic organization, employees do multiple things in a designated area. They become jacks-of-all-trades. In a matrix organization, employees are much more likely to specialize in a given function. They can master the skill. The successful matrix manager knows how to spot the most talented employees and recruit them to her (temporary) team.

Flexibility and adaptability count – flexibility is the strongest point of matrix organization. Managers can quickly assemble and re-assemble teams based on changing needs. This only works if managers are equally flexible. Managers must be fluid; they can’t stay attached to a permanent structure. There is no permanent structure.

Managers must work effectively with each other – in a matrix, an employee often has more than one manager on a given project. For instance, that retail expert from Stockholm would report to me temporarily while working on the Filippa K account. At the same time, she would also report to the overall head of the retail team, who might be located in Melbourne. It can get confusing and roles need to be clearly defined. At the same time, managers need to work effectively with their peers cross the matrix. If I have a beef with the manager in Melbourne, things will go downhill quickly. Again, diplomacy and good communication are key ingredients for success.

The matrix changes the culture – in geographic organizations, teams may easily fall into competition with each other. I would have no incentive to lend my retail expert to another geography. That would only crimp my chances of making my number. A matrix, on the other hand, emphasizes cooperation. If a manager doesn’t make her all-stars available, she doesn’t get access to other all-stars. Sharing becomes more important than competing.

Ultimately, good managers have nothing to be afraid of in a matrix organization. Even in traditional top-down organizations, good managers are likely to be effective communicators and motivators with good diplomatic skills. Those are the same skills that are required to succeed in a matrix.

Another Reason For Female Executives

Which gender norms should we adopt?

Which gender norms should we adopt?

Want to get stuff done? You may need to compromise occasionally. Who’s better at that? Who do you think?

A recent study in the Journal Of Consumer Research (abstract here; pdf here) suggests that men working with men tend not to compromise. By contrast, men working with women or women working with women are more likely to find the middle ground.

The article, by Hristina Nikolova and Cait Lamberton – professors at Boston College and the University of Pittsburgh respectively — focuses on consumer behavior and is probably most relevant to marketing strategists. But I wonder if it doesn’t have much broader implications as well.

The study revolves around the compromise effect, which is well understood in marketing circles. Let’s say that you want to buy a car and you have two decision criteria: efficiency and prestige. Car X is clearly better on efficiency and OK on prestige. Car Y is clearly better on prestige and OK on efficiency. Car Y is also more expensive than Car X.

Which one do you buy? It’s a tough choice. So the salesperson introduces the even more expensive Car Z, which is even better on prestige than Car Y. Now Car Y is the compromise choice – it’s OK on efficiency and pretty good on prestige. With three choices available, Car Y is not the top of the line on either criterion but it’s acceptable on both criteria. The compromise effect suggests that you’ll buy Car Y.

The compromise effect has been demonstrated in any number of studies. Indeed, it’s why restaurants often add a very high-priced item to their menus. The item probably doesn’t sell very often but it makes everything else look more reasonable.

But what if you’re making the decision with another person? This hasn’t been studied before and Nikolova and Lamberton focus their attention on decisions made by two people acting together (also known as dyads). The authors looked at three different dyads:

  • Male/male
  • Female/male
  • Female/female

Under five different conditions, Nikolova and Lamberton found essentially the same results. First, the compromise effect seems to work “normally” with female/female and female/male dyads. Second, the compromise effect has much less impact on male/male dyads. Such dyads tend to move toward one of the extremes – either Car X or Car Z in our example.

Why would this be? The authors suggest that it has to do with gender norms coupled with the act of being observed. They write, “Normative beliefs about women’s behavior suggest that women should be balanced, compassionate, conciliatory, accommodating, and willing to compromise….” Male gender norms, on the other hand require, “…men in social situations to be maximizers, assertive, dominant, active, and self-confident; their decisions should show leadership, … high levels of commitment … and decisiveness….”

For both genders, being observed influences the degree to which an individual adheres to the gender norms. If you know you’re being observed – and/or that you will need to defend your choice later – you’re more likely to behave according to your gender norm. Interestingly, men working with women tend to adopt more of the female gender norms.

Nikolova and Lamberton focus exclusively on consumer choice but I wonder if the same dynamic doesn’t apply in many other decision-making situations as well. Men may be willing to compromise but they don’t want to be seen as compromisers. If you need to compromise to get something done, it helps to add a woman into the mix.

Indeed, I was struck by the fact that the same day I discovered the Nikolova-Lamberton article, I also read about Tim Huelskamp, a Republican congressman from western Kansas. According to the New York Times, Huelskamp is a “hardline conservative member of the Freedom Caucus” who “quickly earned a reputation for frustrating Republican leaders…” after he was elected in 2010. Yesterday, a more moderate challenger defeated Huelskamp in the Republican primary. As one voter noted, ““I don’t mind [Huelskamp’s] independent voice, but you’ve got to figure out how to work with people.” Perhaps the good people of Kansas should elect a woman to replace him.

Jevons Paradox and The Future of Employment

My new teaching assistant.

My new teaching assistant.

Four years ago, I wrote a somewhat pessimistic article about Jevons paradox. A 19th-century British economist, William Jevons, noted that as energy-efficient innovations are developed and deployed, energy consumption goes up rather than down. The reason: as energy grows cheaper, we use more of it. We find more and more places to apply energy-consuming devices.

Three years ago, I wrote a somewhat pessimistic article about the future of employment. I argued that smart machines would either: 1) augment knowledge workers, making them much more productive, or; 2) replace knowledge workers altogether. Either way, we would need far fewer knowledge workers.

What if you combine these two rather pessimistic ideas? Oddly enough, the result is a rather optimistic idea.

Here’s an example drawn a recent issue of The Economist. The process of discovery is often invoked in legal disputes between companies or between companies and government agencies. Each side has the right to inspect the other side’s documents, including e-mails, correspondence, web content, and so on. In complex cases, each side may need to inspect massive numbers of documents to decide which documents are germane and which are not. The actual inspecting and sorting has traditionally been done by highly trained paralegals – lots of them.

As you can imagine, the process is time-consuming and error-prone. It’s also fairly easy to automate through deep learning. Artificial neural networks (ANNs) can study the examples of which documents are germane and which are not and learn how to distinguish between the two. Just turn suitably trained ANNs loose on boxes and boxes of documents and you’ll have them sorted in no time, with fewer errors than humans would make.

In other words, artificial neural networks can do a better job than humans at lower cost and in less time. So this should be bad news for paralegal employment, right? The number of paralegals must be plummeting, correct? Actually no. The Economist tells us that paralegal employment has actually risen since ANNs were first deployed for discovery processes.

Why would that be? Jevons paradox. The use of ANNs has dramatically lowered the obstacles to using the discovery process. Hence, the discovery process is used in many more situations. Each discovery process uses fewer paralegals but there are many more discovery processes. The net effect is greater – not lesser – demand for paralegals.

I think of this as good news. As the cost of a useful process drops, the process itself – spam filtering, document editing, image identification, quality control, etc. – can be deployed to many more activities. That’s useful in and of itself. It also drives employment. As costs drops, demand rises. We deploy the process more widely. Each human is more productive but more humans are ultimately required because the process is far more widespread.

As a teacher, this concept makes me rather optimistic. Artificial intelligence can augment my skills, make me more productive, and help me reach more students. But that doesn’t mean that we’ll need fewer teachers. Rather, it means that we can educate many, many more students. That’s a good thing – for both students and teachers.

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