There is one comparison that has always surprised me. The one between the manufacturing industry and the so-called knowledge industry in terms of continuous improvement of delivery methods.
Indeed if some people like to call manufacturing the old world (in your opinion where computers and smartphones come from) it has always been able to question the way it produces, and constantly improve its production flows.
Conversely, the world of “knowledge workers,” a broad term that covers a large number of disparate professions whose common feature is to produce nothing tangible, seems to have been wading in the muddle since almost the dawn of time. What I mean by this is that it seems to refuse any scientific or structured approaches to work. Worse, it struggles to question the way it works to deliver.
In fact the organization was structured, not work and production.
You can’t compare offices and factories
The comparison stops there because one cannot compare offices and factories.
First of all because if the factory will always remain the place of production of the ones most of the others can work most of the time from where they want.
Secondly, because in manufacturing, human beings are less and less present in the production process and many productivity gains have been achieved precisely by replacing them with machines. Conversely, in the other case, the knowledge worker is the machine. He is in any case the means of production. The more complicated the task becomes, the less adding people helps to produce more or faster. A highly skilled person will always do more or faster than 10 moderately skilled. I am not even talking about making people work together when the subject is not about adding individual production capacities but about achieving a result that can only be achieved together. When the essence of the work is to be creative or to solve problems (or both at the same time) “brain power” usually requires more quality when “man power” requires quantity.
Also because one manages tangible flows and the other intangible flows. When it comes to visualizing and quantifying this changes everything. Take a walk in a factory and you will easily see whether things are working or not: a machine at a standstill, too much stock here or there, an idle worker. And you will also be able to understand “easily” how one starts from a sum of materials and products to arrive at the final product. The process or at least the scheduling of tasks will always be the same and intangible. Take a walk in an office and it’s the other way around. Everyone may look busy but not produce anything. A person who does nothing and looks at the ceiling may be in the process of finding a major solution. We’re in a production workflow that can reconfigure itself in an ad hoc way all the time (right or wrong, for good or bad reasons). No stock or visible work in progress. And as for knowing which flow follows the information, how it is processed, by whom, in order to arrive at a final result? Almost unpredictable a priori and untraceable a posteriori.
Finally, because the question of the value produced and production costs arises. In manufacturing, all costs are theoretically known in advance as well as the selling price. In “knowledge” the costs are a function of the number of people and time. It is not always known how many people will be involved at the beginning of the process or how long it will take. Sometimes, even at the end, we don’t even know how to determine it afterwards. You can pilot and observe, but the art of forecasting is much more difficult.
And if you look hard enough, you can still find a ton of arguments in this direction.
It’s not a matter of individual productivity.
Before going any further, the debate needs to be clarified. What interests me here is not the question of individual productivity. It is part of the equation, but it is not everything. Peter Drucker has long identified the causes of good or bad productivity in knowledge work and there is not much more to add.
This is true if one person is solely responsible for a whole. But when several people are working at the same time or in sequence, it no longer makes sense. What interests me here is:
- The end-to-end production process: from “input”, whatever it is, to “output”, whatever it is
- Of course the respect of deadlines and budgets as well as the achievement of the expected level of quality (no matter how it is measured).
- The fluidity of the flow as a whole
- The fluidity of the employee’s work (points of friction, useless tasks with no added value). In short, the employee experience in the production flow.
We all know that having a lot of individually productive people doesn’t mean that the team is productive and that you get something at the end of the day.
In addition, when work involves several people or teams, the employee is not fully responsible for his or her productivity or contribution to the production activity.
- He has no control over how tasks are sequenced (when they are sequenced).
- He has no control over the schedule (when there is one).
- He has no control over the content of each step.
- He has no control over what is done upstream and downstream.
- He doesn’t always control his own time (he can work on different projects, his manager can give him tasks that have nothing to do with that particular job).
- He has no control over the control and coordination interfaces (meetings, reporting, decisions).
In this context one can still micro-manage and put pressure on each person one by one, but I don’t think that this solves the problem.
Who is questioning the way in which the work of knowledge workers is organized?
There is a limit to what Drucker tells us about the management of knowledge workers. Yes, they are in the best position to manage their own work, but this only concerns their individual work. The more people are involved in an activity, the more important it is to set a framework and organize (I can already hear the remarks…self-organization is a form of organization and it requires a rigorous framework).
Whenever I have had to work on improving the work of a team or the functioning of an activity, I begin by asking myself the following questions:
- What do people do (their role, their contribution, all their tasks related or not to this activity)?
- How does each role interact and coordinate with the others?
- What are the known steps/tasks between the input (something needs to be done) and the output (it is done)?
- How is all this coordinated and measured?
- How is this formalized?
- How is it managed?
- Are there discrepancies between the way things are supposed to happen and the way they actually happen? What are they? Where are they? How big are they? What are their causes? How often do they occur?
- What are the friction points? (What prevents people from doing their job as well as they could?)
Questions to which, when I ask them, I get only vague answers. “There are things to do, it happens, we don’t always know how, but it happens and that’s the main thing”.
So for sure, when you don’t know what people are doing or how things are going, you’re not going to improve much.
When you are in “project mode” there is still a minimum of formalism and sometimes a lot (or even too much) of structure. But it can be a big blur when you get into the details of the tasks. But for the “daily work” whose routine side should not make us forget that it is not without inefficiency we are in the most complete informal world.
Just because you don’t see a problem doesn’t mean you have to pretend it doesn’t exist.
Disinterest? Fatalism ? Probably a bit of both. The reason? Again I think the “invisible” nature of work flows has a lot to do with it. It’s not easy to be aware of what you can’t see. And when you’re aware of it, it’s a very good reason for pretending that it doesn’t exist.
For example :
There is a real issue with information overload that slows down workflows. What do we do except talk about it?
We all know that organizational design influences a network’s ability to collaborate. For more than 10 years I spent most of my time coaching companies on collaboration-related topics. How many have tried to audit their organization to find out what was blocking them instead of looking at it only in terms of each individual’s willingness / ability to collaborate? None at all? How many thought that technology was not the solution to everything? Many. How many transformed their organizations accordingly? None.
• Who cares about where the bottlenecks are in the workflow? No one, and since a mailbox that overflows or a todo list that fills up faster than it empties doesn’t make a mess in an office, no one cares until the day an employee burns out.
• Who cares that the few who do care do so at the expense….of the performance of others? This is generally the case for support functions that like to improve their efficiency by shifting part of their workload to the operational staff! Or when two teams have to collaborate and each one tries to shift a maximum of load to the other?
• Who cares about the tunnel effects suffered by employees and customers? Can you imagine, when you’ve ordered your new smartphone, being told “we’ve started production but we don’t know when it will be finished or at what cost?
• Who worries about the disconnect that increasingly exists between the field that is moving at the speed of the market, of the client, which in some professions has been converted to agile and operates on a daily or weekly basis, and the managerial strata that operate over increasingly longer time horizons as one moves up the hierarchy?
• Where are continuous improvement approaches in the knowledge industry?
Here again one could draw up an indictment as long as an encyclopedia.
No one can deny that there is a problem or at least things to be improved, but I don’t see much happening in a structured and organized way, let alone on a large scale.
Blame the system, not the individual
The knowledge worker is not the forgotten one in operational excellence approaches. At least not as an individual. The literature is abundant on his characteristics, how to manage him or not, what makes him productive etc.
On the other hand, by dint of considering him as an autonomous entity, owner of his own means of production and capable of self-management, it has been forgotten that he is also a member of a whole, of a system, from which he cannot be dissociated because his performance depends on the functioning of the system in question.
A lot of work was done on the steering, control and coordination structures, but not at all on the “production system”. For yes, even if the term seems to come from another world, the knowledge worker “produces”.
And for the time being, the system has no one to take care of it. There are solutions, more or less adapted, perfect or not, my purpose today is not to judge them, that will come in time. Once again, inspired by the industrial world, they have not or hardly passed through the office door. For good or bad reasons.
If we stick to a basic definition that would say that operational excellence is about aligning and improving processes, tools and people :
- overinvestment in tools (collaboration, knowledge management)
- Processes have remained archaic.
- As for the people, they were seen only in terms of knowledge acquisition, not in terms of the context of its use.
In the meantime:
- We have a real problem with the collective efficiency of knowledge workers.
- This problem is certainly not far from quality issues.
- A subject that is close to the employee experience issues with an impact on individual and collective efficiency, employee engagement/frustration.
- And in the end we have a customer satisfaction and perceived value issue.
As this New York Times article pointed out:
“Peter Drucker noted that during the twentieth century, the productivity of manual workers in the manufacturing sector increased by a factor of fifty as we got smarter about the best way to build products. He argued that the knowledge sector, by contrast, had hardly begun a similar process of self-examination and improvement, existing at the end of the twentieth century where manufacturing had been a hundred years earlier”
Maybe it’s time to take care of it, don’t you think? And how about you ? Have you seen initiatives in this direction? Do you notice that the vagueness and the ambient inefficiency are considered as a necessary and inevitable evil?
Image : Knowledge worker de pathdoc via Shutterstock