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Culture versus strategy

Recently, in one of the company boards that I’m part of, we approved the new product strategy. This strategy is quite a deviation from the previous one in that we balance much more between investing in the current, main product, which used to get virtually all investment earlier, and new product initiatives to serve adjacent markets and help grow the business. However, after the board meeting, we discussed operationalizing the strategy and the main topic was that the most difficult part would be to change the culture of the employees in the business.

As famously said by Peter Drucker, culture eats strategy for breakfast. Once you get a certain culture in place, the general experience is that it’s extremely difficult to change. You can present all the strategy slide decks you want, but it’s surprisingly difficult to actually make people change their ways of working. Although this perspective is quite accurate, it easily puts companies in a bit of a victim role: the culture is what we have and we have to live with it.

Diving a little deeper, I believe that this is a fallacy that we have to avoid falling into. Culture can be defined as the norms and values that we organize ourselves by. Norms are defined as the established standards or expectations and values are the set of beliefs and ideas that we uphold as important within the company.

For example, virtually every company I work with views itself as customer centric. However, the ways this materializes can vary greatly. In the company that triggered this post, the implementation of customer-centricity was to try to respond to every suggestion, request and demand from every customer. The result was a backlog of an infinite amount of minor features that may please some customers but that didn’t move the needle from a competitiveness perspective. The way we responded to this was by setting a strategy where we explicitly allocate resources using the three horizons model and within each horizon with an explicit allocation to roadmap work versus customer requested work. We still allocate resources to respond to customer requests, but significantly less than before.

Now, making this strategy real basically requires us to externalize the norms and values by which we’ve been operating. Once we’ve done this, we have a basis for discussion to realize the changes we’re looking for. Often, it’s not so much that a completely new set of norms and values needs to be defined, but rather that the balance between conflicting norms and values needs to be changed. For example, in some companies, an urgent request from a customer is always prioritized over roadmap work. When it’s time for a retrospective and it’s clear that few of the features on the roadmap were realized, everyone sagely accepts this as there were too many requests from customers that needed to be prioritized.

Read the last sentence again: “needed to be prioritized” is a direct expression of the company culture and something that you as a leader need to be highly sensitive to. Not reacting to such statements makes you immediately complicit in perpetuating the old culture and sabotaging the defined strategy.

'Make the current norms and values explicit'

To realize a new strategy and upgrade your company culture, I believe that at least three actions are key. First, make the current norms and values explicit. Not in general terms, but as specific as possible. Then indicate where the new strategy requires us to make changes in the way we prioritize our time and energy. Exemplify it and make sure that everyone rationally understands what the new strategy means in terms of cultural changes.

Second, as a leader, you need to embody the new strategy. When I lived in the US, many parents told their children: do as I say, not as I do. However, it’s perfectly obvious for any parent that children mimic the behavior of their parents, not their words. The same is the case for employees in a company: people will mimic the behavior of leaders, not their words. So, as Gandhi said, be the change you want to see.

Third, operationalize the strategy for every individual in terms of what it means in terms of day-to-day work, priorities and interaction and follow up on the new ways of working. Humans are habit-driven creatures and it’s too easy to fall back into old ways unless we’re constantly reminded of what’s expected from us. This also requires an escalation path as conflicts will surface between the old and new cultural patterns. If individuals are required to sort out these conflicts themselves, most will fall back into the old, safe ways to avoid any perceived risks. Allowing for escalation will make it safer to take risks as the responsibility is abdicated.

While it’s true that culture eats strategy for breakfast, it doesn’t mean that you can’t realize changes in the company culture that facilitate the strategy you’re looking to operationalize. It requires us to externalize the norms and values in the old culture to make the required changes in priorities explicit, for leaders to embody the new strategy and behave by it and for each individual to operationalize the strategy in concrete, day-to-day terms. This is incredibly hard and time consuming, but the alternative is to not change at all. As Mark Zuckerburg famously said: “The biggest risk is not taking any risk… In a world that is changing really quickly, the only strategy that is guaranteed to fail is not taking risks.”

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“Start with system functions and think beyond the boundaries of your own discipline”

High-tech development processes are becoming so complex that organizations cannot avoid thinking and working in a multidisciplinary way. After all, the ideal solution is rarely one-dimensional. However, collaborating engineers from different fields are only successful if they understand each other’s jargon. VDL ETG T&D sends its technology professionals to the Mechatronics system design training at High Tech Institute so that they can train that skill.

The mechanical engineering group of VDL ETG’s Technology & Development department currently employs approximately fifty people, of eight different nationalities. Group leader Bart Schalken notices the differences: “Education in the Netherlands is excellent and the knowledge level is very high. You can only see that clearly when you start recruiting internationally. I grew up in Eindhoven, so in my experience, this is the normal world. However, when you talk to international engineers, you notice how special the technical level is in this region. In the field of precision mechanics, our schools and universities are ahead of their international counterparts.”

'Mechanics may often be the basis here, but that doesn’t mean that you can meet all system requirements.'

Another point where Dutch engineers excel is that they’ve learned to look beyond the boundaries of their own discipline. This quality is becoming increasingly crucial. “Development processes are almost all multidisciplinary and so complex that you can no longer approach them sequentially; you have to move in parallel,” says Schalken. “Mechanics may often be the basis here, but that doesn’t mean that you can meet all system requirements. Then it’s important to involve another discipline. Only by connecting and working together can you ensure that the product will meet the functional requirements.”


“You don’t have to know all the ins and outs of the other discipline, but you do have to master the basics,” says Bart Schalken of VDL ETG T&D. Credit: Bart van Overbeeke

But how do you find the right specialist within a group like Technology & Development that has grown from a few dozen to around three hundred and fifty since its inception eight years ago? To keep an overview and to ensure that everyone knows exactly who to contact, Schalken has carefully mapped out the sub-competences. “I’ve listed more than two hundred competencies and capabilities within mechanics and indicated per employee who has what knowledge. Those scores make it immediately clear who you should go to if you need knowledge about, for example, leaf spring constructions or vacuum systems,” Schalken explains. “Ultimately, the goal is to deliver the best result for our customers, but the know-how for the optimal solution doesn’t necessarily have to come from your project group or department. We make use of all the knowledge we have on board. And if there’s a hiatus, we always have our network of external partners and universities. That’s the atmosphere I want to create.”

Due to the increasing complexity and the urge for a shorter lead time, VDL ETG works with increasingly large project teams. “So the need for multidisciplinary collaboration is getting bigger and bigger,” Schalken experiences. “Normally, we’re in a large office space, but now, because of corona, we often work from home. That doesn’t make it any easier. Of course, we share the most important project information during digital meetings, but what’s missing now are the accidental conversations that arise at the coffee machine. While those are often the lubricant of smooth collaboration in projects.”

Eye-opener

A precondition for good collaboration is that engineers speak the same language. “You only seek each other out if you understand each other’s jargon,” says Schalken. “You don’t have to know all the ins and outs of the other discipline, but you do have to master the basics. Everything revolves around communication.”

To make the collaboration between the disciplines more effective and more decisive, at the beginning of last year, Schalken arranged for the High Tech Institute’s “Mechatronics system design” course to be given in-house at VDL ETG. Many of his people have now attended this training to gain a better understanding of adjacent disciplines. The course covers basic concepts and terminologies and the participants apply them to the disciplines around them.

“My group mainly consists of mechanical engineers, but such a course only really catches on when the other disciplines join as well. That’s why we invited people from the software, electronics and mechatronics groups. In addition to paying attention to theory, the training makes time to work together in teams pragmatically. That provides so much insight. Only when you look at a problem together, you really notice how they approach it from a different discipline. A real eye-opener.”

Check out the training

Although the follow-up process has been temporarily delayed due to the current corona measures, Schalken hopes that eventually most of his own group and as many engineers from other disciplines as possible will learn to speak the common engineering language. “In recent years, TU graduates have been given a broader base and have been trained to think and work in a multidisciplinary manner. For them, the Metron 1 training is no longer necessary and Metron 2 suits them better. That’s perfectly fine, of course – the great thing is that the added value is recognized,” Schalken states.

Start with the function

In addition to the training being an eye-opener for the participants, Schalken is counting on another advantage to become visible. “The core of VDL ETG is in system development, in combination with our manufacturing knowledge,” he explains. “Everything is under one roof. You can walk from the engineering department to the machining hall and the sheet metal shop. We have a lot of knowledge about manufacturability and value engineering. Helping and advising customers with DFX is where it all began. Today, VDL ETG itself is the development party and customers involve us starting from the specifications. We take care of the entire development process up to and including realization. As a result, customers only have one point of contact for the entire process.”


“Only when you look at a problem together, you really notice how they approach it from a different discipline.” Credit: Bart van Overbeeke

This approach means that VDL ETG engineers not only see the theory but are also closely involved in the manufacturing process, assembly and qualification of the end product. “The close connection between theory and practice ensures a steep learning curve for our engineers,” Schalken points out. “This knowledge is further enhanced because they get direct feedback on how the products are performing in the field. For example, we analyze parts that are returned after an update. Any weak links become visible and we take that knowledge with us to improve the next design.”

The mechanical engineers at VDL ETG focus a lot on DFX for series products in high-tech. “This knowledge is now well embedded within the organization,” says Schalken. “The next step is that we learn to think and work from the function of the system. What does the customer really want? What’s the question behind the question? And what roadmap is behind that?”

'The keys are communication and speaking the language of your colleagues from another discipline.'

Because VDL ETG has traditionally been quite focused on mechanical engineering – “our mechanical engineers are often the owner of a system” – the solution to a problem is quickly sought in that corner. “Ultimately, of course, you want to move towards a feasible and cost-efficient design – we’ve already laid that foundation – but the function of the design is the starting point,” Schalken states. “What does it take to make it happen? That’s the goal you must have in mind all the time. The mechatronic systems we develop focus on increasingly faster and more accurate positioning in an increasingly cleaner environment. What competencies do you need to realize such a position accuracy with those preconditions? You don’t have to come up with the solution yourself, but you must understand when to involve whom in the development to reach the end goal. The keys are communication and speaking the language of your colleagues from another discipline.”

This article is written by Alexander Pil, tech editor of Bits&Chips.

Recommendation by former participants

By the end of the training participants are asked to fill out an evaluation form. To the question: 'Would you recommend this training to others?' they responded with a 9.1 out of 10.

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Free webinar 22 March – System Architect Development Program

High Tech Institute organizes a webinar on 22 March 2021, 5 PM (GMT+1) in which the new System Architect Development Program, called ‘System Architecting Masters’ will be introduced.

 

The essentials for leadership in highly demanding development environments

The nine months long System Architecting Masters (Sysam) program focuses on practical no nonsense system architecting development, as well as the essential leadership skills that are vital to exercise this role in technical development environments.

Sysam offers a deeply immersive, rigorous experience for professionals in research, development and engineering organizations who are committed to driving meaningful change within themselves, their teams, and their organizations. Check out the entire description here.

For whom?

Professionals in a technical development and engineering environment with:

  • at least five years of experience
  • at least half a year experience in a system architecting or system engineering role or a leading position that requires you to communicate with a team, customers and management
  • an ambition to bring your leadership skills to a higher level and improving your overall effectivity

Indicators
Sysam helps you to avoid common pitfalls in system development and engineering. You might recognize some them the mentioned below.

  • timing is a problem. Projects run late and over budget;
  • products do not meet the requirements the client needs;
  • technical decisions are done too much separately from other important aspects of the business;
  • technical leaders are not visible enough in the organisation;
  • it is not clear where the responsibilities of the system engineer or system architect starts and ends;
  • systems do not meet the stakeholders expectations, not only from a functional, but especially from a quality point of view.
Webinar outline

 

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Prepare for the worst

Recently, the Netherlands experienced some inclement weather including snowfall and strong winds. Interestingly, the entire country shut down with trains not running, highways closed off and recommendations of staying at home. It led to a bit of hilarity in our Swedish household as we experience this kind of weather regularly during the winter months and we just go about our business without blinking an eye. However, Northern Europe had a few very mild winters recently and people started to expect those to become the new norm.

The pattern of assuming that the most recent data points can be used to accurately predict the future is a deeply human trait that we can see everywhere. A dry summer causes people to complain about global warming changing the climate. A successful quarter or two causes companies to assume that the next quarter will be as successful. Typically, we expect today to be like yesterday and tomorrow to be like today. The main conclusion has to be that human intuition simply sucks at applying statistical principles. It doesn’t mean that changes aren’t happening, but it does mean that we typically need a lot more data points before we can conclude anything definite beyond chance.

The primary defense against this is summarized in the proverb “hope for the best; prepare for the worst.” On the personal side, the Stoics practice a habit that I think can be incredibly helpful. Promoted by Seneca, the idea is that you daily imagine the worst thing that could happen to you and try to experience and live through it in your head. This helps you build up the mental fortitude for the situation where something bad does happen so that you don’t collapse under the weight of what life throws at you. And, of course, it also helps you feel grateful when bad things do not happen. A second habit of the Stoics is to, once per month, wear the most basic of clothes, eat the simplest food and sleep in the most rudimentary bed to experience what life would be like if you were to be down on your luck and lose everything. And to do all this, asking yourself that if this was the worst that could happen, is it really that bad?

In business, the key challenge very often is the focus on efficiency. It’s inefficient to put resources aside for cases outside a very narrow band for which companies optimize as these resources aren’t utilized sufficiently. So, companies often fail to proactively prepare for bad situations and need to scramble to respond whenever the market or society suddenly shifts. The ongoing pandemic is a great example of how many were caught off guard.

'Innovation is by its very nature inefficient'

However, the main victim of the focus on efficiency typically is innovation. Innovation is by its very nature inefficient. As a team, you develop hypotheses of what might help develop and grow the business, but the fact is that you’re most likely wrong and will only find out after having spent resources on testing and validating the hypothesis. The very nature of innovation is such that the majority of innovative ideas don’t pan out and it’s the few that do that have to pay for all the failed ones. Of course, principles such as those defined in the lean startup or our research aim to minimize the resources invested in each idea by creating multiple proof points that need to be met to invest more. But the fact remains that innovation is inefficient by the metrics of modern companies.

The main concern of assuming that tomorrow will be like yesterday and today is that you’re woefully unprepared for “black swan” events and become extremely fragile as a business. Some companies invest significant effort in scenario planning where multiple more likely and less likely scenarios of how the future might unfold are evaluated and responses are developed for each of these scenarios. The scenarios themselves will never occur as predicted, but they’ll inform and accelerate the response to what will happen and help in the case of unexpected events.

Human intuition is extremely poor at statistical analysis and companies tend to suffer from “recency bias.” This makes them fragile and brittle, causing them to break and fail in the face of unexpected situations. As the future is fundamentally unpredictable, we need to protect ourselves from ourselves by balancing efficiency and preparedness, conducting scenario planning to have clear playbooks to use and investing in innovation. As Alan Kay famously said, the best way to predict the future is to create it. No matter how inefficient and resource consuming it may be. Remember: prepare for the worst while hoping for the best!

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Bringing AI to the edge

It seems that much of my work these days is concerned with bringing AI to the embedded-systems domain, understanding what the implications are and how companies should deal with it. In the discussions with technical experts and business leaders, however, I constantly run into several misconceptions.

First, there are still several people out there who think about ML/DL models as single-point solutions for a specific problem where we can build the model, integrate it, deploy the resulting software and be done. Although one could operate in this way, it’s basically ignoring the vast majority of benefits that you could deliver. Instead, it’s about continuous everything. It’s about a constant flow of software updates to the field, a constant flow of data coming back from your systems, constant retraining and updating of models. We all read about DevOps, DataOps and AIOps, but that really is what it’s all about. The shorter you can make the cycles, the more value you can deliver.

Second, many view AI as a technical challenge to be solved by R&D but unrelated to the rest of the company. The fact is that it will change your business model. If you’re currently using a transactional business model where you get a one-time payment when you sell the product but need to provide software updates throughout the economic life of the product, you’re in trouble as your cost is continuous while your revenue is not. The only way to get around this is to align your revenue model with your cost model. For most companies that I work with, it means combining the upfront product sales with a continuous service revenue model. This is actually a great way to generate more revenue from your customers.

Third, especially in companies that build large, complex and expensive systems, such as in automotive, telecommunications or automation, there’s no clear definition or understanding of the actual value provided to customers. The whole package sells and consequently, the whole package is valuable. When moving towards continuous improvement of systems, you need to choose where to focus your energy and time. And this requires you to understand what’s actually valuable in your offering as improving commodity functionality using ML/DL models or otherwise doesn’t help your customer. We’ve worked quite a bit with companies on modeling the value of their solutions or products to customers and it’s surprisingly hard to be precise and concrete.

'You can’t use AI in isolation'

Fourth, you can’t use AI in isolation. Machine and deep-learning solutions require data for training and operations. The data is generated by software that instruments the system. And of course, ML/DL models are themselves software. The only difference is that AI software is programmed by data and pattern recognition, rather than by humans in an algorithmic fashion. This means that you need to be good at all digital technologies.

The final misconception is that many believe that once they have trained an ML/DL model and it performs well in prototyping, the hard part is done. This couldn’t be further from the truth. The easiest part is actually creating a model and the hard part is industrializing it. Industrializing means setting up the data pipelines, putting monitoring and logging in place, ensuring correct (or at least acceptable) behavior in all cases, developing solutions for DevOps, DataOps and AIOps, and so on. In an earlier post, I wrote about our AI engineering research agenda where we capture the major challenges to be addressed.

AI is moving to the edge – and it should because it has the potential of delivering enormous value. The challenge is that there still are quite a few misconceptions out there about what this actually means in practice. I’ve discussed five of these and provided my viewpoint. AI belongs on the edge, but there’s a lot of work around it that needs to be put in place at the same time. And as it won’t happen by itself, it’s critical that we get going on this yesterday.

 

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Activity isn’t the same as progress

Occasionally, I enjoy playing computer games and during the Christmas break, I spent some time in Eve Online. It’s an open-world game, set in space, where you’re free to do any activity that you like. As I was spending time in this game, I realized something interesting: the return in terms of in-game currency that I was earning with certain activities was orders of magnitude different from other activities I could be spending time on. Not 10 percent but 10x, 100x or even 1000x!

When I look at my life outside of computer games, I notice something similar. Whether it’s publications (I am a professor after all), financial returns (I invest in startups as well as traditional passive index funds) or health returns (I exercise daily), how I decide to spend my time has a significant impact on the return I generate. For instance, standing on a cross-trainer at a moderate setting for 40 minutes has, according to some research that I read, the same cardiovascular effect as three times one minute of full-out high-intensity interval training (HIIT). Three minutes has the same effect as 40 minutes – that’s more than 10x!

In the companies I work with, in various capacities, I see a similar pattern: most of the people I meet are hardworking and well intentioned, but for many, the return on their activities is quite limited. Especially for us, who are toiling to drive change in companies, many initiatives run out into the sand without any real impact as the resistance to change proves too powerful. It easily starts to feel like “shuffling chairs on the deck of the Titanic” – you’re close to the lifeboats, but you’re doing little to avoid disaster.

Many moons ago, when I was working for Nokia, one of the senior leaders in the company mentioned a quote that I’ve taken to heart and try to operationalize as often as I can: activity isn’t the same as progress. Being raised traditional Calvinist protestant, the importance of working hard was ingrained deeply in my upbringing. My dad often told me: “There are workhorses and there are show horses. You’re a showy workhorse.” And I must admit that I’ve never met a successful person who didn’t work his or her behind off.

'It’s not only about working hard but also about working smart'

Hard work is necessary but not sufficient. It’s also about working smart. How do we make sure that the things we spend our time on indeed result in the outcomes we’re looking for? The Pareto principle states that 80 percent of the outcomes result from 20 percent of the causes. The effect of this principle can be found in wealth and income distribution, taxation, quality management, sports and even software development, as the hardest 20 percent of the code takes 80 percent of the time.

The Pareto principle also applies to how we spend our time as professionals. Being creatures of habit, it’s easy to step on the treadmill of our daily, weekly, monthly, quarterly tasks and just execute as this is how we’ve always done it. However, as everything we and our companies do commoditizes over time, we should always look for ways to automate or remove activities that add little value in order to free up time for new activities and initiatives that have the potential of an order of magnitude higher return of investment (RoI). Innovation doesn’t only apply to products and services but also to how we organize our workday.

My challenge to you is to evaluate the effect or impact of the activities you spend your time on. Identify the 80 percent that results in little impact, find ways to automate or get rid of those and use the freed-up time to do more of the 20 percent activities that have the high RoI. In the end, we all want to make a difference and just working hard isn’t the optimal way to get there. Remember: activity isn’t the same as progress.