00:00:03 Fear in innovation and supply chain.
00:02:01 Workforce fears: mechanization and automation.
00:04:54 Potential automation impact on white-collar workers.
00:06:39 Transition: Mitigating fear, improving situations.
00:07:26 Gradual deployment: Minimizing workforce disruption.
00:08:53 Machine learning: New jobs, reduced headcount.
00:10:42 A gateway to company expansion.
00:11:35 Smooth automation transition strategies.
00:14:01 Data quality and control roles.
00:16:03 Individual roles in company technology implementation.
00:16:35 Adapting to technology: Acquiring expert knowledge.
00:18:22 Understand your company’s operations, constraints.
00:19:25 Learning from industry leaders.
00:21:15 Embrace modernized processes.
Summary
In an episode of Lokad TV, Joannes Vermorel, Lokad’s founder, discusses the fear factor within the realm of supply chain innovation. Vermorel expounds on the inherent risks, primarily the potential for losses outweighing the profits from innovations. He addresses resistance to change, especially towards innovations that threaten job roles, in areas such as automation and quantitative supply chain management. The discussion includes strategies for gradual innovation implementation, using natural workforce attrition and role evolution. It underscores the importance of identifying individual agendas within a company. Finally, Vermorel encourages businesses to transition to advanced supply chain management, highlighting the growing market dominance of companies like Amazon.
Extended Summary
In the latest episode of Lokad TV, Kieran Chandler, the host, is engaging in a conversation with Joannes Vermorel, Lokad’s founder, on the theme of fear, specifically within the context of supply chain innovation. Vermorel is illustrating the asymmetrical risks that exist in the supply chain, highlighting how fear of loss often dominates potential innovation rewards.
Vermorel shares that when businesses elevate their current operations, the advancements usually produce only a slight percentage of extra profit or cost cutbacks. He indicates the high bar for achieving this because most firms already operate efficiently. However, should these changes backfire, the losses might be substantial, possibly surpassing the anticipated gains. This situation results in a logical tendency toward conservatism in businesses, promoting a beneficial fear of new ideas and innovations that could potentially disrupt supply chains.
Vermorel adds that this fear isn’t entirely baseless, as even prosperous firms exhibit a level of reluctance to change due to the inherent risk of disruption. This resistance or caution is generally targeted at innovations that endanger existing job roles.
Vermorel is distinguishing between two kinds of innovation that could potentially trigger this fear. The first relates to mechanization or automation, like autonomous vehicles, which immediately threaten jobs such as truck driving. The fear arises from the perceived certainty of job displacement due to these innovations.
The second kind of innovation pertains to the quantitative approach in supply chain management, where tasks performed by supply chain clerks—like managing Excel spreadsheets—are automated. This automation doesn’t necessarily pose an immediate job threat, but the fear emerges from the anticipation of a future where such jobs are redundant. These roles would be replaced by deep learning algorithms and supply chain scientists overseeing operations.
Vermorel points out an intriguing predicament in the decision-making process surrounding these innovations. For example, a truck driver would likely refuse autonomous trucks to protect their job. Similarly, white-collar workers performing manual statistical forecasting currently would resist a more automated process as it threatens their positions. This resistance is intrinsic and must be acknowledged in discussions and implementation of supply chain innovation.
He suggests that the headquarters, where planning and forecasting occur, including supply chain management support functions, may contain many white-collar jobs related to the supply chain, indicating potential resistance against automation from this workforce segment, fearing job displacement due to technological innovation.
However, the speakers argue that it’s not all negative. They propose a strategy for firms to slowly introduce supply chain automation, reducing the fear and resistance from employees. Firms could leverage the natural attrition of employees, with about 10% retiring annually and a similar fraction moving to other roles or transitioning within the company. This would allow companies to avoid large-scale layoffs and instead embrace a more gradual, less disruptive approach.
Moreover, they insist that shifting to machine learning setups or similar technologies could also generate new opportunities. Although the total number of jobs might diminish, the remaining roles could be more engaging and valuable. They don’t deny the possibility of a reduction in headcount but contend that industrial progress has always implied accomplishing more with fewer people. They compare this to past occupations like carrying water buckets in Paris, a job that has long disappeared due to progress, yet is not missed.
Regarding supply chain management, the speakers predict that in the future, fewer individuals may be needed to maintain large Excel sheets or other tasks which machines could do more efficiently. Companies could then reassign their human resources to roles that machines cannot perform as easily. For instance, negotiating better prices with suppliers, improving last-mile delivery, or better understanding the specific needs of their clients.
Touching on the subject of implementing these technological solutions, the speakers highlight the need to recognize the individual agendas of people within the company. Managers of teams whose roles might be made redundant due to automation might resist these changes due
to job insecurity. They advise top-level executives to be alert to such potential resistance and not to expect full support from middle management. They point out that many employees may not be excited about efficiency improvements if those improvements directly threaten their job security.
Vermorel starts by addressing the anxiety among managers regarding the prospect of automation. He suggests that in a traditional organization, the number of people under a manager often correlates with the manager’s perceived power and influence. Therefore, automation, which lessens the need for a large workforce, could be viewed as a threat to their status or perceived power.
Vermorel advises companies to carefully consider the potential impact of automation on various roles and prepare a career path for these individuals that allows them to evolve within the new company structure. He suggests that planners, for instance, could transition towards roles involving data quality control, as automation would require a greater dependence on data quality. Also, management could refocus their efforts towards reevaluating constraints associated with the supply chain process, as opposed to engaging in tedious manual number-crunching.
Even if managers lose part of their teams to automation, Vermorel suggests they can still add substantial value to the company through these new roles. Success through these innovations opens up different but equally rewarding career paths within the organization, both financially and in terms of status.
Vermorel also provides advice for entry-level planners who might fear obsolescence due to automation. He suggests they redirect their focus from clerical tasks to understanding the processes they model in Excel. This is due to the immutable nature of supply chain constraints, like the physical network organization, vehicle capacities, and cost structures. These realities persist, regardless of the level of automation. By gaining expertise in these areas, employees will remain valuable, even when software innovations are deployed, ensuring their ongoing relevance.
Vermorel concludes by stating that while these e-commerce giants cannot seize every market immediately, companies should initiate the transition towards advanced supply chain management practices sooner rather than later. They must not delay until their competitors have acquired insurmountable skills and market advantage.
Full Transcript
Kieran Chandler: Today on Lokad TV, we’re going to be discussing the topic of fear and how many can adapt to the new world that they’re facing. So Joannes, this sounds like a bit of a deep topic this week. Why are we talking about fear so specifically in the context of this channel, where we are frequently discussing about innovation, and especially innovation in supply chain?
Joannes Vermorel: Supply chain typically has very asymmetrical risks. If you do something better than what you’re currently doing, you’re going to have like a few extra percent of reward compared to what you were doing previously. So, your costs are going to be reduced by a few percent, maybe your margins are going to be increased by a few percent if you do it better, which is already a high bar because many companies are already quite efficient. But if you screw it up completely, the loss can be gigantic, it can be a significant multiple of what you expect to gain. The very rational position is to be quite conservative and to have a healthy fear of novelty and innovation if it has a potential to wreak havoc in your supply chain. Very good companies are relatively conservative, which means a certain degree of wariness and resistance to novelty, because it has a potential to disrupt and negate what you were expecting to gain in the first place through innovation.
Kieran Chandler: It sounds like there’s a lot of positives to come out of these changes. But what is it that people are actually afraid of?
Joannes Vermorel: There are several levels. In certain classes of innovations, like automation, obviously if your job is to be a truck driver, the idea of having autonomous vehicles does not look good. People will be very scared because they feel that they will lose their job and even if they are not immediately fired, it will mean that a decade down the line their entire job will disappear. In Lokad, with our quantitative supply chain approach, it’s not the truck drivers that we are automating, it’s the supply chain clerks - the people who are diligently editing Excel spreadsheets to ensure everything flows through the supply chain. These tasks will be largely automated, perhaps with AI or deep learning algorithms, plus supply chain scientists to orchestrate the whole thing. The interesting thing is, if you ask someone who is presently doing statistical forecasting in a semi-manual way whether they think they have a positive or negative opinion about an innovation that basically aims to do it in a much more highly automated way, you can expect a negative response. It’s the same situation as with the truck driver versus autonomous vehicle - you cannot realistically favor something that will entirely displace your job position.
Kieran Chandler: If we talk about those people, how many people are we talking about here? How much of the company do they make up?
Joannes Vermorel: When we consider those present in a company’s headquarter, they can potentially represent a significant percentage of the world headquarters, right? Because actually, the vast majority of the people operating in supply chains are working on the ground, such as truck drivers, warehouse workers, and factory workers. However, these individuals aren’t usually close to the decision-making processes of the company that are happening at the headquarters.
If you look at what the headquarters is responsible for, it’s primarily planning, forecasting, and other support functions. Thus, the number of white-collar jobs at the headquarter that are related to supply chain can be relatively numerous. This suggests that when a company operating a large supply chain wants to upgrade, there could be strong resistance at their headquarters. Dozens of people might fear this kind of innovation entering the company. They might highlight the risks involved, pointing out how much risk they are taking on by implementing these changes.
Kieran Chandler: Of course, it’s not all doom and gloom, is it? We’re in sunny Paris after all, so let’s try to put a more positive spin on this. How can we mitigate this kind of fear and improve upon the situation?
Joannes Vermorel: If you are a supply chain director and you want to roll out something that will fundamentally mechanize classes of white-collar jobs in your company, the first thing to understand is that you’re not going to fire all those people. Unless the management side of the company is brutal, most companies, especially in Europe, would not proceed in that way.
What you would do first is, because of the risks involved, you would not roll out the new system all at once. You would do a gradual deployment. Furthermore, in your staff, you likely have people who are nearing retirement or who might take on another job at a different company. You also have people who move internally within the company.
So, if you look at it, you have about 10% of the people who retire each year, another 10% of people who leave for another job, and 10% who move inside the company. This equates to one third of your staff rotating each year. If you’re a large company and you do a gradual deployment, this results in a gentle transition where people move to other positions gradually, and you don’t have to fire everyone at once.
Moreover, transitioning towards a machine learning setup or a similar class of setup creates new jobs. Maybe not as many as before, but it certainly creates more opportunities for people to move into jobs that are typically even more interesting.
Kieran Chandler: So, we’re not just kind of appeasing our conscience slightly, there’s surely going to be a bit of a reduction in headcount due to this, right?
Joannes Vermorel: Yes, and that has been the essence of industrial progress for the last couple of centuries. A couple of hundred years ago, the number one job in Paris was actually people carrying buckets of water, a significant portion of the population, to ensure water distribution. Nowadays, we have running water so this job has entirely disappeared. I don’t think there is anyone who truly regrets the disappearance of having an entire army of people carrying buckets of water.
Kieran Chandler: In the grand scheme of things, the same can be said about the supply chain, particularly when there are armies of clerks spending their days manually or semi-manually editing massive Excel sheets. It doesn’t make much sense to employ people who could be doing more intelligent tasks, bringing much more value to the company, just to have them perform such tedious clerical tasks. These are tasks that machines could largely handle. Yes, there might be a reduction in staff numbers, but mostly in supply chain. If you can do more with fewer people, chances are that in the end, you’re not just going to shrink or downsize your company. Rather, you will expand to do more, to provide better service. You want to pay more attention to what you’re doing, particularly in the last mile for e-commerce. You want to have better negotiations with your suppliers so that you can adjust your own supply chain operations, making it easier for your suppliers to serve you. This way, you can negotiate better prices. In the same vein, you can have more people available to discuss with your clients to better understand how to serve their specific needs. It takes more people to do this and it’s not as easily automated as crunching Excel sheets. Now, let’s talk about the implementation of this solution. How can we ensure that this transition happens as smoothly as possible?
Joannes Vermorel: First, I think if you’re a CEO or a supply chain director of a company operating a large supply chain, you have to acknowledge that people may have agendas that directly oppose the improvements you want to implement. This doesn’t necessarily mean that they’re against company strategies, but you can’t realistically expect people to move in a direction where they feel extremely insecure.
Let’s imagine you’re the head of a demand planning team with 20 employees under your command. You need 20 people because they’re all planning through Excel. If you present to this manager the fantastic opportunity of upgrading to a software that only requires two data scientists to do the same job, they might not be thrilled by this perspective. The same job would be done with much more sophisticated methods than the ones currently being used. The manager might not even be the right person to manage these future data scientists. So, don’t expect too much support from the existing hierarchy, even up to a fairly high level.
Most people don’t have a vested interest in improving the company’s efficiency if that means losing status. Even if the manager isn’t in danger of losing his job, he may lose his headcount. In large companies, the number of people you manage is a symbol of power. People aren’t exactly overjoyed, even within management layers, with the idea of doing a lot more with a lot fewer people if that means losing their sphere of influence within the company.
What you need to do, I believe, is to carefully identify the agendas that people might have and then offer a career path for all those people so that they can evolve in the new version of the company. This means, for example, that planners can move towards tasks that involve data quality and data control. If you want to have a more automated system, then you’re critically dependent on the quality of data. This means that part of the staff you had crunching Excel can be repurposed to add much more value on the data control side.
Kieran Chandler: Some of these tools can be used to acquire more data that is not present in your system yet. For the management, this implies that they might need to shift towards different sorts of tasks. They might need to refocus more on what is happening on the supplier side, the client side, or their internal processes. Perhaps they will need to spend more time reconsidering the very constraints associated with the company’s supply chain process, as opposed to spending a lot of time merely crunching the numbers in a semi-manual manner.
Joannes Vermorel: Exactly. This can present opportunities for management. They might find themselves focusing on tasks that add significant value to the company. This could motivate a manager, even if, in the end, they lose a good portion of the headcount they once managed. If a manager succeeds in adding value through the deployed innovation, it opens a different career path. One that could still be quite valued within the company, both financially and in terms of status. They could still be seen as someone performing an essential and valuable function for the company. This holds true even in a world where such innovation is being rolled out.
Kieran Chandler: You spoke about the managers, but what about the people that the manager is managing? What kind of tips do you have for them to move on with this implementation, and what about their roles?
Joannes Vermorel: If you’ve been doing manual Excel sheet editing for a decade, and your job has been primarily clerical tasks, my suggestion is to learn more about the type of processes that you’re modeling. The physical reality of your supply chain isn’t going away, even if the calculation methods change. The Excel sheets might be discarded for a better class of software, but the fundamental processes at the physical level won’t change. Some things will partially change, like the introduction of autonomous vehicles, but that won’t fundamentally alter the fact that you need a specific network to organize your distribution.
A truck can only be in one place at one time, has a fixed capacity, and costs money by the kilometer. These constraints will still be true even with the roll-out of this innovation. So, my suggestion is to focus more on what is not going to change within your supply chains. Try to acquire some expert knowledge, so when this software innovation gets deployed, you will still be seen as valuable to the company. You understand how things operate. So, if people start thinking about how to improve these processes or need help to measure the improvement, they will turn to you. Not for your Excel skills, but because you are fundamentally familiar with the way the company and the supply chain operate, and understand all the constraints that come with it.
Kieran Chandler: Are there still truths that hold even when you roll out your software innovation? As a final point, what advice would you give to top-level executives?
Joannes Vermorel: My final tip for executives would be to pay close attention to what Amazon is doing. Amazon is aggressively gaining market share in a multitude of markets. They have been banking on highly automated supply chains for over a decade, and they are becoming exceedingly proficient at it. For most supply chains, if you don’t start paying attention to what advanced statistical software can deliver to your supply chain, your competitors who are already paying attention will have an advantage.
In the end, it will really be about whether you want to be completely disrupted or if you want to start the transition now. Amazon cannot attack all verticals frontally, which means they are progressing in many verticals simultaneously. This buys you time because they cannot capture every single market overnight. It will take them a decade or more.
Therefore, you still have time, but you should start using this time now and not wait another decade until Amazon, or Alibaba from China, or the next generation e-commerce platforms like Zalando in Europe, have gained so much skill at being better at supply chain management that you can’t recover the lost time.
There’s plenty of time to make a gradual transition rather than keeping all your processes immutable.
Kieran Chandler: Alright, well I think we will wrap things up there. It seems that the only thing to fear is fear itself.
Joannes Vermorel: Yes, that’s correct.
Kieran Chandler: So, that’s it for this week. We’ll be back again next week with another episode, but until then, we’ll see you soon. Goodbye.
Joannes Vermorel: Goodbye.