Category: Blogs

An engineer asks:

I am a test expert and I regularly have to try very hard to convince project leaders to have a certain test performed. I find convincing them difficult, especially if the project leader has a dismissive attitude. How can I sell my service better?

The communication trainer answers: 

Even if there is no sales function on your business card, you must regularly “sell” your services to internal customers. For example, because your customer can get your service from outside or simply because he doesn’t need to buy your service or product at all. Selling is a dirty word for many technicians. And yes, selling nonsense or deceiving someone is something you shouldn’t do if you want to sleep peacefully. But if you really have something to add and help the customer solve the problem, you have to bite the bullet.

How do you do that? In the sales process, you go through the steps of the Aipa process: attention, inventory, presentation and approval. The first step involves making it clear who you are and exactly what you or your department is offering. Here, it is important that you know how to get the attention of the customer. In your introduction you will therefore have to name something that you know or estimate that your customer will benefit from. For example, “We are developing a new test that can detect errors in your process early”.

Once interest is piqued, you ‘earn’ the right to start asking questions. The big mistake you can make here is simply telling people how great your service or product is. After all, you don’t know if the customer really needs it at this point yet.

You must look for the problem and the desire of the customer. You do this by asking open questions: “What is the problem?”, “What are you up against?”, “What exactly is going wrong?”, and also “What negative effects does this have?”. In this way, the client’s pain comes to the table and this provides motivation to want to do something about it. You also ask about the goals to be achieved. This creates a creative tension between the here and now (‘ouch’) and where the customer wants to go (smiling faces and full glasses). Your added value lies in helping them to take that step.

Once the problem is on the table, you move to the third step: offering your solution. Here, it is important that you also dare to promise something. After all, you stand for your product. If you can’t guarantee a result yet, state the degree of uncertainty, but do choose a position. Say, for example, “I still see a ten percent risk that we will not achieve the desired result, but I want to go for it and minimize the risk”. Waiting until you are 100 percent sure is science; taking a position in uncertain circumstances is leadership and this is often necessary.

When you explain your solution, don’t immediately count on applause. It is natural that critical questions will come. It is important to find out what is bothering you. That means you have to go back to the inventory phase and ask open questions, until you have the customer’s concern clear. So you have to go from sending (phase 3) back to asking questions (phase 2).

If your proposal meets the customer’s needs, trust and the desire to make joint agreements emerge – the final stage in the Aida process. You have helped the customer.

In many industries, there’s an implied, often underspecified, architecture of how the different stakeholders in the ecosystem interface with each other. By defining their mutual interfaces, it allows for better alignment. For the typical interactions within the ecosystem, this is very helpful as the different parties have predefined expectations about one another, and transactions and integrations can be conducted, built and deployed more easily.

The existing business ecosystem gets encoded in the way a company organizes itself, including the work processes, workflows, automation, tooling and even job titles. For instance, a company that buys embedded subsystems for its products from suppliers will have processes for defining the requirements, purchasing professionals who negotiate the best deal with suppliers and tooling for testing deliveries from suppliers as well as for tracking the realization of requirements to sign off on contracts and allow suppliers to get paid.

However, there’s a downside to this implied ecosystem architecture: it tends to hinder innovation and experimentation by companies. Experimenting with different business models, introducing DevOps for the product throughout its lifetime, exploring new customer segments with the product – it all tends to upset the existing relationships in the ecosystem. This may easily cause a situation where the cost of innovation and experimentation is so high that it doesn’t get done. This is especially so when innovations require changes by multiple ecosystem partners – generally, the more partners are involved, the less likely it is that the innovation is even experimented with.

Let’s say, for example, that the aforementioned company decides to stop using a supplier and bring the development of the subsystem back in-house – something that happened in the automotive industry during the past years with in-vehicle software. This isn’t simply a technology decision. Rather, it requires changes to the tooling, reassigning of people in purchasing, significant changes to ways of working and internal processes as well as a potentially challenging legal situation with the former supplier.

Where the architecture is especially rigid, for instance driven by regulation or a strong government customer, the ecosystem runs the risk of becoming stale. Due to the difficulty of incorporating change, the ecosystem’s ability to adopt productivity-improving innovations is so limited that, rather than individual players, the ecosystem as a whole may be disrupted. Industries such as construction, healthcare and university education are illustrative examples of where the pace of innovation in the ecosystem is particularly slow and where some are predicting a fundamental disruption may happen in the foreseeable future.

When it comes to the digital transformation of your company, this very often requires the organization to strategically reposition itself in its business ecosystem. Digitalization often causes a transition from a transactional to a continuous value delivery to end-customers. This means that companies that happily used wholesalers, resellers, installers and other partners to get their product out in the market are now looking for ways to build direct customer relationships. Removing the intermediaries requires careful management of the relationship with these partners as the old, transactional, and the new, continuous, business often have to coexist for several years, if not longer.

A second typical pattern is that work that was outsourced needs to be brought back in-house as the suppliers are unable to change their operating model to faster feedback cycles, there’s no good business model or the company considers the technology to be so critical that they want to own the competence internally.

Of course, the opposite happens as well: a technology and associated subsystems that were done in-house because of their strategic nature lose that status due to digitalization and need to be outsourced to new partners that might even have been competitors earlier.

A fourth pattern is that the company needs to involve new partners to manage new digital technologies, such as data and AI, or because the new position in the ecosystem requires new relationships with others serving the same customers. This often calls for a careful strategy as to where the company wants to own the market and where it’s open to partnering and letting others coexist.

Finally, there’s the challenge of startups and established, repositioning companies entering your existing or intended market. The organization needs to decide whether to partner or compete with these new entrants.

The digital transformation almost always requires strategic repositioning in your business ecosystem. You need to have a direct relationship with your end-customer, adopt new technologies and associated new partners, reinvent your business model, jump over existing partners without ruining the relationship for your legacy business and so on. This is complex and calls for careful strategizing and execution. But the alternative is that you get disrupted together with the existing business ecosystem. So, next to executing your New Year’s resolutions, also spend some time thinking about how you’ll initiate the work on repositioning your company in your business ecosystem. I wish you a prosperous 2021.

In March it came as a shock: sitting at home and working at home. What have we learned over the past period about what works and what doesn’t? And what can you learn from this for the future?

The pros and cons of working remotely appear to be closely related and are largely determined by the situation. The type of work, the mutual relationship between those who work together and the personality of the individual worker are determining factors whether online works well or not at all. How about that?

Soon during the corona crisis it became clear that much more is possible with working remotely than we thought. It helped of course that the online tools are a lot more stable and advanced than years ago. More is possible. Working from home also prevents the annoying and time-consuming traffic jam. And when you have quiet circumstances at home, it can help you work in a concentrated way. So for some, it can even increase productivity. Many have also experienced that this is not true for everyone. If it’s restless at home or the walls are coming up and you need real people around you, a few days at the office can be a blessing. For the time being we assume that even after the pandemic it will remain a combination of working at the office and at home. Hopefully it will remain possible for everyone to choose their own optimal balance.

Jaco Friedrich is competence owner of the Soft skills & leadership trainings.

Non-verbal communication

When are online conference calls less effective? Three factors determine this. First: when the relationship between the conversation partner is under pressure and conflict is (or already is) lurking, online works less well. After all, you miss a part of the non-verbal communication and therefore ‘feeling’ how someone is in it is a lot more difficult. Especially when you are in a video conference with several people. You are quickly too direct or not clear enough because you do not see how someone reacts to your message. It is less easy to make adjustments. This increases the risk of losing each other.

This also plays a role in situations where you have to be critical of each other’s work, for example at an important review or decision meeting. You are more likely to get into a discussion or people lose the connection and drop out. There is a risk that the quality of reviews will deteriorate as a result.

Secondly, with conference calls it is more difficult to respond to each other quickly, without talking through each other. Being able to connect to each other is less smooth online. For creative sessions it is therefore usually better to meet physically.

The third factor with conference calls is whether the participants already know each other. If that is the case, the relationship is good and there is mutual trust, then working online will also go a lot better. If that trust is not yet there and the participants are new to each other, group formation will be slower than normal. Another factor is that you miss more or less chance encounters. Moments when you ‘drop by someone’, listen in with others, tune something up or chat informally. The part of the information that you normally pick up in this casual way during the day is completely lost.

Camera and microphone on

What does this mean? Probably working remotely will continue to exist. So the question is how to get the most out of it and avoid the pitfalls. Here are a few practical rules. To minimize missing the non-verbal, I recommend always turning on the cameras as a starting point. In this way you are visible to the others and the others to you. This applies to all participants of the meeting. Possibly this gives bandwidth issues. However, do not, as a precaution, turn off your camera. Turn it on; you can always turn it off.

A next principle is that you do not mute your microphone when you are not talking. Turning it on and off is a threshold – no matter how small – to be able to react quickly to each other. So advice: leave it on. Unless your dog is barking or the neighbor is drilling.

To keep each other informed, it can be useful to start every morning with a ‘stand-up’. Everyone briefly tells you how it goes and what he or she is going to do that day. In this way you pick up on each other’s situation, who needs help or where you might be able to think along with each other. Moreover, it creates a moment to start your work day with a clear focus. That in turn helps to prevent your motivation from dropping. If you don’t have a team, an accountability buddy might be the solution. In plain Dutch: someone with whom you go through the day every morning and who keeps you on your toes (‘Did you finish this yesterday?’, ‘Have you already asked them for help or are you going to postpone that until tomorrow?’).

In addition, for everyone: create physical activity every day, make sure you have social contact, make sure you’re outdoors for a while, take a short break every hour and put your computer out of sight when you’re done with work. Actually, these are good routines anyway, so you can use this time to wear down some good habits.

2020 will go into the annals of history as the year of the Covid-19 pandemic. Many people have seen their lives disrupted, gotten sick or worse and suffered from mental health issues due to isolation and loneliness. All the mayhem caused by the pandemic, though, easily makes us lose sight of all the good things that happened this year.

The first, most obvious, one is the fact that the digital transformation of industry and society took a step function improvement. We’re all much, much better at conducting our work online and even if many of us would really want to travel more and meet people in real life (and actually shake hands or hug), we’re getting things done. Teams and individuals that were convinced that they needed to be onsite and in each other’s face to be able to do their job are now operating remotely and working from home.

One of the advantages is, of course, that the environment is doing better as air pollution levels are lower in many parts of the world. This is especially advantageous in areas that have snow in winter, as the whiter snow reflects more sunlight. Also, there are several reports of improved water quality in rivers and lakes. The reduction in carbon emissions and pollutants, according to a Wikipedia article, saved 77,000 lives over two months.

Science and technology research is continuing to deliver great results. In the sunniest parts of the world, the cost of solar electricity is now below the cost of fossil fuels. This a decade or even decades ahead of earlier predictions. And of course, we’re not done. The improvements in solar are just continuing, driving down prices even further to the point that electricity will become close to free, according to some predictions.

Also, a recent article in Nature describes how the use of a deep-learning program by Google’s Deepmind solved protein folding in biology. A problem that for decades proved to be incredibly difficult to tackle by traditional algorithms was finally cracked by AI. And this is just one of the main benefits that AI is bringing to humankind.

Something that never ceases to amaze me is how quickly we were able to develop vaccines for Covid-19. This article shows a timeline starting with the genetic sequence of the virus being released by the Chinese authorities early this year and nine months later, there’s a vaccine (in fact, multiple!) available with mass distribution starting early next year.

As a space nerd, I was incredibly excited to see SpaceX sending people into space again. After the space race in the 1960s, interest in space took a nosedive, but I’m one of those that believe humans need to get off this planet and spread through the solar system and the universe. A catastrophic event on this planet won’t mean the end of humankind if we have people out there. To build up a space industry and capability, the first step is to have reliable and cost-effective rockets.

Other news that just blew me away this year is that scientists have now managed to reverse aging in cells, specifically in optic nerves and restoring sight in aging mice. Peter Thiel famously said: “Your mind is software. Program it. Your body is a shell. Change it. Death is a disease. Cure it. Extinction is approaching. Fight it.” It looks like we’re on track to actually realize cell rejuvenation in bodies for real and if not abolish then at least delay death.

In my posts, I occasionally comment on the apocaholics in our society (and on the interwebs) who loudly claim that the whole world is going to hell in a handbasket. This is both factually incorrect and, in my opinion, morally wrong as it encourages a victim mindset. Humankind is incredible and has an amazing capability to respond to challenges put in front of it and overcome these. If nothing else, the year 2020 showed, once again, the value of science and technology, the creativity of humans as a species and that, despite everything life throws in our way, we still manage to improve things. I hope you spend Christmas celebrating our combined accomplishments and that you start the new year focusing your energy on what you’re going to do to contribute. Merry Christmas!

A management consultant asks:

In my job, I deal with multiple projects from different clients. That variety makes the work exciting, but the pile of memos and reports is getting too much. When I go home in the evening, I haven’t been able to do what I had planned because of all the phone calls, emails and meetings. It’s very frustrating and I’m getting more and more often commented on not meeting deadlines. How do I create order out of this chaos?

The communication trainer answers:

The theory about prioritizing is simple, but applying it is oh so tricky. Why? Because there are many factors at play at the same time that vary from person to person and from workplace to workplace, and are also constantly changing. Important factors are for example the dynamics of the work, the extent to which you can delegate, the level of the people around you and of course your own personality. Personal tendencies, that can make it difficult for you, are perfectionism (‘never finish, because it has to be 110 percent right’), pleasing (‘if I say I won’t do it, he won’t like me anymore’), disaster thinking (‘if I make a mistake, things will go terribly wrong, so I procrastinate’), enthusiasm (‘I like everything, finishing is something I am less good at’) and helpfulness (‘I like helping people, so I hardly get around to my own work’). All these personal factors in combination with all the constantly changing circumstances mean that you constantly have to be consciously and actively engaged in setting priorities.

How do you do that? In brief, the theory. The priority of a task is determined by the factor ‘importance’ and the factor ‘time’. Whether something is important depends primarily on your core task. What are you paid for? Suppose you are an architect, so working on the architecture of a machine is important. Arranging a meeting or making a calculation that perhaps an engineer could do is less important. Next, you check the urgency. Does it have to be done quickly or can it be left? And for how long?

Based on these two criteria, you decide how much time to spend on a task and when. Is it important and urgent? Then you do it now and well. If it is important and not urgent, you can schedule the work or make a start. Is it not important but urgent? Let someone else do the work or spend as little time as possible on it yourself. Not important and not urgent? Ignore them!

Check with yourself: what gives the most pressure, urgency or importance? Right, urgency. We are lived by the delusion of the day. We give in to pressure. Someone at your desk, an email, everything requires attention now. Some of that stuff you have to do to keep things going, but some of it is a waste of your time. The time you lose because of this, you lack in carrying out the important tasks, which also become urgent as a result.

Prioritizing therefore requires an active attitude and regularly selling no, but with a justification. The approach is as follows.

1) List for yourself the most important and difficult tasks that you really need to do.

2) Make sure you make time in your calendar to do these tasks and be prepared to defend this very hard.

3) Make sure you leave enough time for all kinds of ‘in-between’ things (thirty percent on average).

4) Be prepared to adjust your agenda and planning at any time if necessary.

One last piece of advice: make a realistic schedule and communicate what you can and cannot do. This will make you a reliable colleague. The world is not going to run according to your schedule. You will need to be continuously flexible, but never lose sight of your main goals.

Last week, we organized the sprint 19 reporting workshop of Software Center. The opening keynote by Frances Paulisch (Siemens Healthineers) was about the transition from a transactional business model to continuous value delivery to customers. The closing keynote of Aleksander Fabijan (Microsoft) discussed starting and scaling A/B testing. Though the keynotes focused on very different topics, they shared a common theme.

This theme was concerned with driving change and the challenge of successfully implementing the change. Both Frances and Aleksander raised the point that most changes in organizations touch many individuals, functions and departments, as well as numerous processes and ways of working. As I discussed in earlier posts, in most organizations, to change anything, you have to change everything. However, it’s impossible to change everything completely at the same time. And this is where I see many organizations get stuck.

The way out of this is to accept that all change will need to be gradual and that rather than accomplishing the change in one fell swoop, it will have to be a continuous process for an extended time. The analogy is that of a flywheel. Getting a flywheel from a complete stop to at least some rotation requires quite a bit of energy. Once there’s some motion, you need to keep exerting power to speed up. However, once it achieves more speed, it becomes easier and easier to maintain that speed. The question is how we achieve that in organizations. In my experience, there are three main aspects: showcase the value, increase engagement and build infrastructure.

First, showcasing the value requires finding a small scope where success is virtually guaranteed but where the value of the change you’re looking to accomplish is clearly demonstrated. As you initially have to realize all of this with a small team, it’s important to keep what you’re looking to accomplish as much as possible in your scope of control to minimize the risk of others torpedoing your efforts. For example, when running your first A/B experiment, pick a topic where opinions are highly diverse in the organization, ensure data quality from the A/B experiment and use this to engage with relevant stakeholders to show how the data from the experiment benefits the organization.

Second, once you have a successful case, engage the stakeholders that you need to convince to increase the scope of the change and show the real, concrete, tangible benefits you created in the first loop. Use this to increase engagement with the people that you need in the next iteration of the flywheel to create the next showcase. For example, when upping the release frequency of software on your way to DevOps, initially often the ability to rapidly resolve defects in the field can easily be used as a means to increase awareness and buy-in with relevant stakeholders.

Third, look for ways to automate some of the activities you’ve so far conducted through manual effort so that over time the cost of running through the iterations of the flywheel becomes lower. This is concerned with building the infrastructure for the change you’re looking to realize. For A/B testing, this may mean automating parts of the data collection pipeline and for adopting DevOps, this typically requires automating the CI/CD pipeline, as well as the test infrastructure.

Once you’ve gone through the first iteration of the flywheel, it’s basically rinse and repeat to take the next step and try to accelerate. It’s easy to get discouraged when trying this, but remember that flywheels accelerate very slowly and require a lot of energy to get moving at all. And initially, as everything needs to be done manually, the flywheel has a lot of resistance. With more and more of the infrastructure in place, it rotates easier and easier.

Many of the companies I work with struggle with realizing the changes required in their organization. Some oscillate between trying to realize a big-bang change and a complete deadlock where nothing happens. The most effective way to realize change is the persistent, perhaps slow, but continuous accelerating of the flywheel through showcasing value, engaging stakeholders and building infrastructure. Accept that it takes time and, because of that, start yesterday instead of tomorrow. Build your flywheel and get it spinning!

As it was Thanksgiving in the US last week, I wanted to follow up with a reflection on the notion of scarcity and abundance. Many in industry operate with a scarcity mindset, believing that basically everything we’re concerned with is available only in limited amounts. Whether it’s ‘winning’ a customer, being promoted or getting a project that you asked for, the basic assumption is that either someone else gets it or you get it. It’s a win-lose situation.

The reason for this can, of course, be found in the evolution of humankind. For the hundreds of thousands of years that the predecessors of modern-day humans roamed the earth, everything was driven by scarcity. Food was scarce, safe places to live were scarce, people to partner with safely were scarce, and so on. And this translates into many of our current behaviors in society. In football games, one team wins and the other loses. In television shows, there’s one winner. In computer gaming, the battle royale games go through successive rounds of fights until only one player is left.

For virtually everyone in the western world, scarcity is largely an illusion. We all have access to food, a safe place to live, access to healthcare, protection from threats, and so on. Using Maslov’s theory as a basis, our physiological and safety needs are largely taken care of and these basic needs were historically where scarcity existed. Our psychological and self-fulfillment needs are typically not where scarcity is an issue. When someone else enters a relationship, it doesn’t reduce your opportunities to enter a relationship. When a colleague of mine publishes a paper, it doesn’t affect my opportunities to publish a paper.

In our economy and business, we have the same misconception of scarcity. Most people seem to miss that the economy is growing all the time. GDP growth means that there’s more value, with money as its proxy, created by an economy. That value and money don’t mean that a country had to lose for another country to win. In some way, we’re creating value and money ‘out of thin air’ (see Wikipedia for a longer exploration of this topic). Thanks to the digitalization of society, more and more of that value is digital, as can be witnessed by the valuations of technology behemoths such as Microsoft, Facebook and Google. And because of that, our planet’s physical resources are less and less the source of value creation, which is a good thing from an environmental perspective.

The point I’m trying to make is that we live in an age of abundance. For most of us, we can put virtually all our life energy into self-actualization and creating a positive impact on the world we live in. We can do this through work, volunteering, relationships, community efforts, politics or any other means. But we should view the world around us through the lens of abundance, rather than the lens of scarcity.

In business, this means that a competitor or partner doing well doesn’t mean that you lose opportunities to do well. In fact, several of the startups I’m involved in celebrate when companies in the same space do well as it means that the size of the cake is growing. Especially for new companies, it’s not the competition that’s the concern, but overcoming non-consumption, eg companies that continue to use pen and paper instead of the nifty tool you created. So, instead of competing at the sharp end of the knife with a scarcity mindset, look for ways to create win-win situations and adopt an abundance mindset. There’s more than enough for all of us. Your growth is only helping my growth!

Many who will read this will undoubtedly point to all the pain and suffering that still exist in the world and I don’t want to ignore that or sweep it under the rug. But the fact is that virtually every metric concerning the quality of life in the world, ranging from war deaths and people living in poverty to child mortality and life expectancy, is improving and humanity has never lived in a better age. We live in the age of abundance and, for all the troubles in the world today, I believe it’s good to remember that and be grateful for it.

This week, I attended the International Conference on Software Business (ICSOB 2020) and gave a presentation on autonomously improving systems. The core idea is that software-intensive systems can measure their performance, know what to optimize for and can autonomously experiment with their own behavior.

The history of software-intensive systems can be divided into three main phases. In the first phase, we built systems according to a specification. This specification could either come from the customer or from product managers, but the goal of the R&D team was to build a system that realized the requirements in the specification.

Many online companies, but also the first embedded-systems companies, are operating in the next stage. Here, teams do not get a specification but rather a set of one or more prioritized KPIs to improve. In e-commerce, the predominant KPI often is conversion; in embedded systems, often a weighted mix of performance, reliability and other quality attributes is used. Teams get as a target to improve one or more of these KPIs without (significantly) deteriorating the others. They have to develop hypotheses on this and test them in the field using, for instance, A/B experiments.

Although the second stage is a major step forward for many companies, the problem is that it still is the team doing all the heavy lifting. Especially running many A/B experiments can be quite effort consuming. The next step that some companies are starting to explore is to allow the system to generate its own experiments with the intent to learn about ways to improve its own performance. Theoretically, this falls in the category of reinforcement learning, but it proves to be quite challenging to realize this is an empirical, industrial context.

The evolution companies go through to reach this third stage can be put in a model, showing the activities and technologies that can be used at each level. From level 2, we see some autonomously improving system behavior such as adding intelligent, online selection of experiments, as well as automatically generating experiments. This results in all kinds of challenges, including predicting the worst-case performance of the generated alternatives. If a system autonomously generates and deploys experiments, some of these experiments can exhibit very poor performance, meaning the system requires models to predict the worst-case outcome for each experiment, as well as solutions to cancel ongoing experiments if performance is negatively affected.

With the increasing prevalence of AI, we need to start looking into online reinforcement learning in software-intensive systems as this would facilitate autonomously improving systems. This ambition comes with major challenges that we’re now researching. However, I encourage you to start exploring where the systems that you build could autonomously improve their own behavior. Even starting in a small, risk-free corner of the system can be very helpful to learn about this paradigm. The overall goal is that every day I use your product, I want it to be better!

Recently, in a discussion with a company about becoming data-driven, I ran into the same challenge as many times before: the company claims to gather so much data, but the amount of value generated from that data is very small. It makes one wonder what underlies these patterns of, apparently, enormous amounts of data being collected but very little of that data being used to create something of value. In my experience, there are at least three factors at play: sense of ownership, local optimization and cost of ‘productizing’ data.

A typical pattern in many organizations is that teams generating and collecting data for their purposes feel strong ownership of that data and don’t want others to prod “their data” with their big, fat fingers. It’s theirs and if anyone else needs similar data, they can go and collect it themselves rather than get it for free from the team.

This leads to many small islands of data that are entirely disconnected and don’t aggregate into something more valuable than the sum of the parts. Teams may brag about all their data, but nobody else can use it.

Any team that decides that they need data to improve the quality of their decisions will focus on their own challenge and only collect what they need at the level of detail, frequency and aggregation that they need. In addition, they can decide on a moment’s notice to fundamentally change the way data is collected, as well as what data is collected.

The consequence is that the data typically is hard to use outside of the immediate context for which it was generated. This leads to different teams collecting very similar data, due to the lack of coordination. Also, as few think about the broader use, teams that realize that they need data are unable to reuse any of the existing data as it’s so specific to the use case for which it was collected.

If a team would decide to make their data available for others, they would need to provide documentation on the semantics of the data, set up a system for finding and downloading data sets, ensure that changes to the way data is collected, the semantics, and so on, are carefully communicated to stakeholders and, of course, respond to requests from these stakeholders and make changes to the data collection processes not to benefit themselves, but to help others in the organization. And, last but not least, the team may easily be held accountable for privacy, GDPR, security and other concerns that companies have around the stored data.

The consequence is that, unless a counterforce is present, teams will actively try to not share data because of the effort and cost of sharing with others in the organization. This again leads to lots of data recorded, stored and used for specific, narrow use cases, but no synergies, no end-to-end understanding of systems in the field and the way customers are using it, and so on.

The solution to these challenges is to adopt a hierarchical value modeling approach where you connect top-down business KPIs to lower-level metrics that can be collected directly from the field. By building this hierarchical, acyclic, directed graph and quantitatively establishing the relationship between higher and lower-level factors, we can finally start to generate business value from all the data we collect.

Getting from the current state to this hierarchical value model isn’t easy, if only because most people in the companies I work with find it extremely hard to determine what quantitative factors we’re optimizing for, and if we do know, the relative priority of these factors is a source of significant debate. However, it provides enormous benefits as you can focus data collection on the things that matter, use the data to make higher-quality decisions and build data-driven offerings to customers that you couldn’t have created otherwise. As the adage goes, it’s not about what you have, but about how you use it!

An engineer asks:

I have been working as a chief design engineer for many years. However, I am regularly told that I need to communicate better. By now, I’ve gotten to the point where I want to make some improvements, but what exactly do they mean by “communicate better” and how do I do that?

The communication trainer answers:

Good communication skills are necessary to work well together in complex projects. Basically, it’s about knowing how to give a message and knowing how to properly receive the information someone else gives you. The necessary condition for this to succeed is contact between sender and receiver.

Contact is established by paying attention to the person you are talking to. You will therefore have to show interest in the other person. When the other person also pays attention to you, the contact is established. Compare it with calling a colleague. The moment the connection is there and the line is noiseless, you can start discussing things.

By actively listening, you ensure that you understand the other person’s message. You do this by applying: listening, summarizing and asking follow-up questions. Listening means paying attention to the other person. You summarize by saying, for example, “Okay, I understand that …” or “Okay, I hear you say this and that, is that correct?’’ The other person hears what you have learned and receives confirmation that you have understood correctly, or he has the opportunity to make some corrections or adjust the level of his explanation to the level of your understanding. In both cases this is pleasant for the one who is telling and creates clarity.

When sending your message, it is important to be as concrete as possible. Quantify where you can. This always makes your story better. Tune your story to the level of understanding and focus of the other person. What does the other person want to know? Probably your project manager is primarily interested in the schedule, risks or costs and less in technical details. The sales manager is probably more interested in the consequences for his customer than in the problem itself. You can estimate this beforehand and take it into account in your story.

But now the most important thing. The game of sending and receiving rarely runs smoothly. Simply because we all have our own frame of reference and so we don’t understand each other right away. It is therefore extremely important that you pay attention at all times to whether your message is getting through and that you react if it is not.

You notice that your message is getting through when the other person is paying attention to your story and maybe nods in agreement from time to time. However, if the other person suddenly changes position, frowns or starts to say something, this could be a sign that your message is not going down well. It could be that the other person doesn’t understand something, has an interesting association or disagrees. You don’t know until you check.

And so the latter is what you should do. Continuing with your own story while the other person wanders off in their own thoughts accomplishes little. The moment you notice that something is happening with the other person’s attention, the communication turns one hundred and eighty degrees and you switch from sending to receiving. You ask: ‘’I see you frowning, tell …’’ or ‘’You want to say something, tell …’’. In this way, the communication oscillates back and forth and you quickly come to clarity.

Should you immediately stop your story with every muscle that leaves the other person? No, but it is recommended to always remain aware of the other person’s reaction to your story while you are telling it. Check it at least every so often by asking, “How does it sound so far?’’ In that way, you invite the recipient of your message to respond and you get feedback on how your story has arrived.