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CHAPTER III - Building the New Workspace

Beyond education, the physical work environment significantly contributes to how workers learn and apply their skills effectively. All organizations have workspaces built into them. For many, this design is an afterthought, an accident of an office space built on top of an organizational chart. The workplace of the future needs to be more intentional.

“How,” asks John Seely Brown of Deloitte’s Center for the Edge, “are we going to craft spaces for things to happen, whether it be organizational spaces, physical spaces, cognitive spaces or emotional spaces?” If the two parts of the future of organizations are learning and working, then the question is how to design a context that is supportive of both?

In higher learning processes, transdisciplinary and continuous, workers solve new problems every day. Teams vary according to the problem. This is not an arrangement that can be solved with a revolutionary office plan. It is going to be solved with a revolutionary way of thinking.

Inquiry-First Architecture and Solution-Centered Workspaces
Today, the best organizations are set up to learn from exceptions. No case is ever the same, and problems are too complex to apply standard approaches. Playing “best practices” is, at best, playing the odds. Organizations may arrive at an acceptable answer, but not at a great one, and certainly not an inventive one. Improvisation will be necessary — but that does not mean making it up as they go along.

In the future of work, organizations will not be starting with a process, they will be starting with a question. “Inquiry-first thinking” lets an organization start with a problem that needs to be solved, and then work back to discover the kind of knowledge and process that will find the solution. This is a creative process, a shining example of higher order learning, and it is not something that machines may ever master. The challenge comes in creating a work environment that supports that framing. It requires systems, it requires new physical, organizational and social structures. These structures can be flexible —and indeed must be.

Given today’s pace of change, workers every day face the unexpected. Processes no longer work, and the workers that get ahead are the ones that are able to interpret exceptions in an almost subconscious way. This is the essence of transdisciplinary learning. This approach requires an embrace of ambiguity, and the patience to wait for results. Inquiryled learning is not the most time-efficient way to tackle a problem, even if it is the most effective.

John Hagel, Co-Chairman of Deloitte’s Center for the Edge, expressed frustration with some of the companies that he talks to. “When I talk to executives about learning, almost inevitably the conversation quickly gets to sharing existing knowledge,” he says. They talk about courses and learning on the job, making micro-courses available in the work environment, about finding a lecture or lesson that will bring employees up to speed. Hagel suggests that the most valuable learning goal is the creation of new knowledge. Because we live in a business world where there are more and more exceptions and less and less routine, the companies and the institutions that are going to thrive are those that figure out how to help people create new knowledge continually. This is about more than listening to lectures and being able to do a Google search for a question.

At Amazon, according to Senior Vice President of Human Resources Beth Galetti, the process begins by identifying the problem, and then working backwards. “The learning comes when there’s a lot of specificity in the problem and there’s clarity in what success would look like,” she says. Broad problems are challenging because too many people get involved, and a lot of time is wasted, and there is typically a loss of focus. Giving people very specific problems allows them to experiment quickly to test the outcomes.

That does not mean that big problems cannot be solved. Peter Fasolo of Johnson & Johnson, speaks of the company’s “process for creating process.” It begins with a big question; chief scientific officer puts a figurative bull’s eye out on the table that says, “Lung cancer, HIV vaccines —how do we solve this?” That question creates an ecosystem around itself and gathers up all of the knowledge that sits inside of Johnson & Johnson. Importantly, the engaged workers are told to be agnostic to which department —or even outside organizations —the solution comes from.

Michael Arena, Chief Talent Officer of General Motors, has done a lot of thinking about this as well. “Once you’ve discovered that we’ve got to bring something new into the world, all of a sudden I want a different set of social arrangements. I want lots of people who really are great engineers in the room to iterate and experiment and bring it to life. So for me, these workscapes change depending on the intent and the challenge at hand.” There might be times where a company will want to lock into a system in order to scale quickly and distribute value across an organization, but the initial architecture must begin with the inquiry.

Big problems, notes Steven Spear, Principal of HVE, LLC and Senior Lecturer at Massachusetts Institute of Technology (MIT), are solved with little steps. A quintessential example is Neil Armstrong stepping onto the moon and calling it a “giant leap.” Spears continues:

If you really want to dig into it, there was never a giant leap, it was just millions of small steps. Neil Armstrong was not on the first Apollo mission, he was on the eleventh, and Apollo was not the first space program, it was the third, behind Mercury and Gemini. And the big accomplishment of Mercury was getting nowhere near the moon; they just sent someone up and returned him safely to the earth from very, very low altitude. But in solving that one problem, it gave a stable platform onto which the next problem could be revealed and then solved, and that allowed for the revelation of the next one and the next one.

Hierarchical structures must also change in solution-centered workplaces. In today’s world, notes John Seely Brown, “All of us are always newbies.” Each of us has to be willing to pick up new skills all the time. That can mean an upending of the traditional mentorship role, with well-established employees learning from much younger coworkers on some subjects, and more traditional mentorship happening on others. “Both groups have tremendous things to tell the other,” he says. “Wisdom can go both ways.”

Another org-chart issue concerns the direction that information can be shared. Esther Dyson, Executive Founder of Wellville, points out that all workscapes need to have a way to share information not just between employees, but with management. The exceptions that lead to insights are typically going to happen lower down in the organization, where workers are dealing with more specific cases. If they are left to solving problems themselves but not sharing that knowledge up the chain, then the organization as a whole will not learn much at all.

To gain that knowledge in the first place, companies must give employees permission to gain knowledge. Or, put more directly, they must give the permission to fail. At SAP, according to Global Vice President for the Future of Work Guenter Pecht, it is accepted that creating new knowledge is mainly done by human beings experimenting and failing. “If failure is seen as something bad,” he says, “you won’t create.”

The Problems of Existing Corporate Culture
The list of things that are problematic about modern corporate structure is long. Beginning at the top, shareholders demand high quarterly returns rather than long-term company health. Then comes the Chief Executive Officers and Board Directors who are also often incentivized by share price. Whether it is in service of higher stock prices or simply a relic of industrial culture, however, there is one major problem baked into most corporate structures that will create havoc: the idea of scalable efficiency.

Scalable efficiency —the idea of reducing costs through standardizing outputs and processes and streamlining routine tasks —works, and has worked for centuries, to produce large numbers of standardized products/services. But it works incrementally, and the more costs are cut, the harder the next increment is to achieve. The models needed to harness for the future —creating cultures in which workers embrace solving problems and identifying opportunities —are about making exponential gains rather than incremental ones. In addition, producing large quantities of standardized products is less desirable as customer needs and expectations become more specific to their own context and also change more rapidly.

Hagel’s research through Deloitte has him talking with CEO’s around the world. “In the privacy of their offices,” he says, “when we talk about future of work, there are two questions —‘How quickly can I automate? How many jobs can I eliminate?’ It’s all about cost reduction.” While noting that there are some exceptions, he says, “Particularly for the large traditional companies, the way work is defined today is a set of routine tasks tightly specified. You have a process manual that goes into infinite detail about each task and how it needs to be done. It needs to be done the same way everywhere, standardized and tightly integrated. Well, frankly, if that’s what work is, machines do that so much better than we human beings can.”

Further complicating matters, almost every department of almost every organization is still captured by an annual budgeting cycle, no matter the long-term goals. “By the time they’ve seeded [an idea] and got it out there and it’s time to spend really big bucks to actually build it, most of it dies,” says William Coleman of the Carlyle Group. He notes that it is much easier for large companies, especially in the tech sector, to grow by acquisition than by developing new, groundbreaking products.

In any given organization, the drive for scalable efficiency will crush the drive for innovation. Corporations act like living beings, in that any novel structure is perceived as a threat. Workers in the system who offer advice based on old models —even if they are trying to helpful —end up acting like antibodies, shutting down the creative process.

New Models for New Thinking
There are many different models for how one might redesign the workplace for exponential learning. Most of them, perhaps unsurprisingly, are built around avoidance of “the core” —the place where existing corporate culture is strongest. The core is an entity motivated by self-preservation. It is also where power resides and where grand decisions are made. It is risk-averse, preferring the stability of incremental gains to the risks of exponential ones. Exponential learning, then, must happen on the edges, in more agile groups.

There must be bridges back to the core. These bridges are the most important part of the model. They must protect the edge groups from the antibodies of the core, but at the same time, must be able to communicate novel learning back to the core for the benefit of the organization. These bridges are not structures, they are people. The role they fill will be one of the most important in the future of work.

According to Michael Arena, Chief Talent Officer at General Motors, these bridge people will have to be more coaches than leaders. They will have to be sense makers. “They connect all the different power points, but they are translators, and they protect those agile pockets.” They will be people who have earned the highest firm equity, and who are powerful enough to be listened to, and comfortable enough to sacrifice their authority —or risk becoming just another “helper.”

The catch-22 is obvious here. The core must cede power to bridge workers, in effect willing itself to be subverted. Furthermore, in pursuit of creating agile teams that rebuild processes in the name of innovation, a company must create a system for developing teams. Ad-hoc teams are wonderful, if they have been granted time and permission to form, though their very ad-hoc nature may create issues of trust.

Today, when a company creates special-purpose teams, they are mostly pulled from existing talent. Someone in the core senses a problem and immediately makes a call to “put our best people on it.” But creating edge teams from workers who are trusted by the core almost guarantees that some of the core’s antibodies will start an attack. Michael Arena instead suggests the need to start an era of “teams over talent.”

This model acknowledges that the “best people” are in such demand that they may not stay with an organization for long. So instead of forming ad-hoc teams, organizations might instead start and empower team constructs, viewing teams rather than individuals as the basic unit of innovation. Teams maintain their agility and speed, but will not be as vulnerable to the loss of individual human capital. In other words, if one person quits, all is not lost.

Taking it one step further, companies can begin to view the organization-worker model as one of access rather than ownership. In this model, a corporation acts as more of talent broker than a place with employees on lifetime lock-down. Different teams can be brought in to solve different problems.

In many ways, this circles back to the issue of technology. We view machines as talent for the things they are particularly good at, and do not think for a moment about turning them on and off as needed. For human workers, we do not have a system that enables this without adding chaos into actual human lives. Today, corporations unitize on-balance sheet and off-balance sheet talent, people working as full- and part-time employees, and contractors, gig workers and crowd workers, and it is a hard system to optimize, especially for workers.

Pointedly, the solution is not the expansion of the gig economy; a society in which everyone works for themselves cannot create an advanced economy, which requires cooperation. But it is possible that smaller, scalable, employee-owned companies can fill the role of these edge teams. This is something like the Hollywood model, in which specialized production teams move from studio to studio on a project basis.

Alexi Robichaux, Co-founder and Chief Executive Officer of BetterUp, takes that model one step further, suggesting that we may be underestimating the creative potential of technology. “The corporation came about in the 17th century because it was what technology enabled in terms of organizing human beings in a unified structure to gain the greatest leverage. But if we’re thinking about technology today, it’s hard for me not to think that there may be a view of the world where companies are just brands and sets of values built around how they treat their customer and how they treat their employee.”

Through the use of technology, organizations may be able to create working teams that subscribe to a company for some undefined time. “We’d see radical efficiency, but we’d also see the increase of individual agency and choice, because if I don’t like how Brand X treats me, I don’t like how they treat my customer, me and my team can defect and go over to Brand B.” It is a dream of a radically empowered employee, which could be a nightmare to some corporations. Considering the directions in which technology is advancing, and with 4 billion people working on a hyper-connected planet, the very laws of economics that allowed large corporations to thrive might tear them down.

 
 
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