Work is solving problems
The lessons from Google
There is a mental framework that is used when dealing with work, and another distinct mental framework regarding learning. But what if we could talk about work the same way we talk about problem-based learning?
What would this kind of work look like and what kind of managing and organizing would support it?
There may be a triggering event that needs to be seen and understood. The goal is then to define the problem together with the customer. The task is not to sell (a solution that may have worked earlier), but to learn, to understand the unique context. What is different now? What is new? What is special here?
Following this line of thinking, the principles of new work could be:
Problem-based work is interaction and exploration both when it comes to defining the problem and when seeking a solution.
The exploration is performed most efficiently through transparency and a network process of distributing the cognitive load of the case.
People don’t perform job roles or tasks. People participate. You as a manager don’t delegate, you invite! Work is engagement and interaction between interdependent people.
People from the whole community/network should have a chance to contribute through voluntary self-organization and at the same time, not sequentially. You design for participation. As many people as possible with applicable and relevant skills should have a chance to connect and contribute.
The industrial process was long, sequential and divided. The problem-based work process is short, distributed/parallel and interactive. The process follows three entrepreneurial phases: defining the problem, creating a solution, scaling up the solution.
The contributions and comments that are received should integrate into a modular solution that can be iterated. The solution has to create value for the customer and equally income for the producer.
All contributions never prove to be valuable or relevant for the customer. This is seen as just one of the opportunities to scale up learning. Relevance is defined as problem solving that customers would be willing to pay for.
Software tools develop from industrial ERP (enterprice resource planning) to post-industrial AI (artificial intelligence) and VR/MR (virtual and mixed reality). Users are going to pay for computing resources as they need them, rather than having to own computing systems
The industrial process wanted to scale up the supply side. The problem-based process wants to scale up the demand side.
Understanding transaction costs has to be combined with a thorough understanding of network effects when utilizing the platforms of work.
Work is about cognitive and social presence. You don’t need to be present in a factory or in an office, but you need to be present to other people.
Virtual reality is soon going to create the same eye-to-eye experience we are used to in physical spaces. And you can be present in many places at the same time.
The lessons from Google
Eugene Garfield founded the Institute for Scientific Information in 1960. His pioneering work was in citation indexing. This allows a researcher to identify which articles have been cited most frequently by others and who has cited them. Garfield’s studies demonstrated that the number of linked items, i.e. the number of papers, together with the frequency of their citation, meaning how many scientists link to the paper, can be used as a measure of success in the scientific community.
Links on the Web are also citations, or votes, as the founders of Google realized. The whole Internet is a densely interconnected network of situational references. It is no different from the practice of academic publishing and citation indexing.
The observation of Larry Page and Sergey Brin seems commonplace today, but it was a huge social innovation and a total breakthrough at the time Google started on September 7, 1998. But what Google did was essentially building on the work of Eugene Garfield.
At that time, contextual relevance was measured through counting the number of other sites linking to a web site, as well as the number of sites linking to those (linking) sites.
What Google has since proved is that people’s individual actions, if those actions are performed in a transparent way, and if those actions can be linked, are capable of organizing and managing previously chaotic and unmanageable tasks.
Totally new ecosystems for work and learning can now be created because of these findings. Work can be solving (contextual) problems and learning can be asking and answering questions.
The quality of both work and learning depend on asking the right questions and linking with the most relevant nodes in the network!
Problem-based, cooperative work is best expressed organizationally through emergent, responsive communities. The mainstream business approach is still predictive grouping and an ex ante organizational structure. It is typically a process organization designed and controlled by the expert/manager. This is based on the presuppositions that we know (1) all the linkages that are needed beforehand, and (2) what the right sequential order in acting is. Neither of these beliefs is correct any more.
The variables of creative work have increased beyond systemic models of process design.
The Google insight is that organizing can be responsive and that the contextual relevance of even large numbers of answers/contributions can be measured and prioritized. By relying on the uncoordinated actions of millions of people instead of experts/managers to classify content on the net, Google in effect democratized scientific citation indexing.
To be able to manage the increasingly complex new business ecosystems, the same kind of democratization needs to take place in the corporate world. Although many people don’t agree with this, I see platforms/platform cooperatives as an important step towards democratization and the new economies of learning and scope.
The transparency of actions is the corporate equivalent of publishing academic articles. Responsive linking, rather than organizational charts, then acts as a measure of relevance and a guarantee of quality.
This has served the academic community. It made Sergey and Larry billionaires. Now is the time to do the same in the corporate world. The Google lesson is that the more work is based on responsive processes of relating and the more organizing is an ongoing process in time, the more value can be created because contextual solutions are, by default, more valuable than mass solutions!
Yesterday you needed access to corporate data and corporate tools to be able to work. Today you need access to customers and their problems to work. The Internet was the original platform. Today the Internet is still about democracy: easy access, decentralization of power and freedom to act.
The Internet is the best architecture for the open and loosely coupled work systems of the future. When it comes to work the Internet hasn’t really started yet
In a way, we need to move back in time to the original Internet when it comes to understanding platforms, but also fast forward to the future when it comes to AI.
Digital intelligence is crucially needed to help us find and create the answers, but human beings in interaction are needed to define the problems and ask the questions–also in the future.
To be human is to be social!
