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Bethanie:
Good morning. What are we here to talk about today?
Niels:
Good morning, Bethanie. Good to speak to you. We're here to talk about technology to support integrated business planning, automation, augmentation, and human centricity. It's an article I wrote previously last year in Foresight magazine, where I'm also on the board of advisors.
Bethanie:
Interesting. All right. Well, can you give me a short summary?
Niels:
Yeah, of course. Look, technology has made a lot of progress in the last couple of years. And in supply chain, we can apply that and we can deploy that. And we hear a lot about autonomous planning, light touch planning, or no touch planning, which is fantastic and which is great.
Niels:
But in this article, I try to bring some nuances in there because I don't think we should only talk about automation. There's also augmentation of a business user, a supply chain planner. And there's also more human centric decision making in the supply chain. And yeah, that's what I try to explore in this article. And also, make a difference between process automation and decision automation.
Bethanie:
Interesting. So, why do you think the differentiation between augmentation automation and human centricity is so important?
Niels:
Well, I think we're at the start of a big change here. We see all this new technology in the enterprise, and this will change the way of working. This will change the future of work, and it's already changing the future of work.
Operating models will have to be changed based on understanding what can be automated, what has to be augmented and where the human plays a centric role in decision making. The supply chain leaders have to understand this, to create new operating models. And understand organizational design, the processes, what type of capabilities, what type of talent do they need. The roles and responsibilities within those frameworks.
If we only focus on automation and what we can automate, we miss a big piece of the puzzle. Yeah. Hence I wrote this article.
Bethanie:
Can you explain a little bit more about these business planning cycles that you mention in your article?
Niels:
What we look at here is common business planning cycles, or core business planning cycles in the enterprise, in many CPG or food companies where I spent 20 plus years of my supply chain life. And if we read from right to left, how we got the vision, that's where companies really decide who they want to be.
You set your big, hairy, audacious goals for a far away future, but you also define your values and behaviors. So, who do you want to be as a company? Which is really a human centric thing to do. Then we can do strategic planning of course, which is often a yearly exercise where you plan ahead for three to five years. Where you make the big calls on if you want to enter a market, the categories on some big ticket items have to be decided there.
And you got your annual plan, of course, where yearly, you decide next year your commitments, your projection, your sales, your operations. And in the end, your EBIT projection of what you think you're going to make as a business, which is a yearly commitment.
And then we got integrated business planning, which often is used in the enterprise. Which is in a planning cycle and on a frequent basis, often monthly, you check this year's plan and next year's plan. You integrate those plans on all the functions. And you check if you still meet your commitments for this year, but you also peek in through the next year and see. You start shaping the plans for next year, but also check if you're still aligned with your strategic commitment.
And then, in the more short-term, we've got what we call pills and operation execution, which is in the next three months. And that's really short-term decision making in the supply chain. Add to optimize demand versus supply and customer service. Where should I produce? Where should I put my inventory? How should I react to customer orders? These types of short-term questions and decisions.
And of course, we have execution where really, we do the production of products or in the warehouse. We move stock with trucks. This is really the execution of all these plans. And ideally, those plans are all aligned. If you read from right to left, those are the longer term plans. Guide to shorter term plans. And then the shorter term horizon really monitors and updates and checks if those plans are still in balance.
Bethanie:
Okay. That's very complete. That's super helpful. Now, before we touch on why human centricity, automation and augmentation are important. But for my own edification and for the people watching this, could you talk a bit about the difference between automation and augmentation in this context?
Niels:
Yes, I can. And I really think we have to ask yourself, where should we automate? And where should the human be involved in decision making? And if we look back in terms of automation, I take the car industry often as an example. They have been leaders in automation, robotic production has been around there for dozens of years. And it's continuing.
If we take that as an example, and the warehouse automation you've seen lately with the automatic robots going around the warehouse. We see automatic trucks now here in Australia, in the mining here for automated trains and automated vehicles, transporting iron ore.
That automation, it's happening. But we also see examples of where this automation actually reaches a limit. And there are also in the car industry, those examples. Tesla, Elon Musk. When he was first producing the Tesla, the three model, actually mentioned that they're trying to automate too much. They had to take a step back in order to be productive.
And you see Mercedes-Benz as well, putting more humans on the line versus robots because the humans had to reprogram the robots all the time on the production line, which actually took productivity down. So we see actually, that there are limits to what you can automate and how far you can automate. And where augmentation and human centricity has to start to play a role.
Yeah, the final example, which is not a great one, I like to share is the Boeing MAX incidents, of course. Where the human pilots was not allowed to interfere, even when the machine was taking a decision. And they tried to interfere and they couldn't. And that led to some very tragic accidents, of course.
So, these are examples where we see, okay, there's a lot of automation. But hey, there's also limits, and there are circumstances in which we maybe better not automate and give the human some more responsibility.
Bethanie:
Those are really great examples. So, what would you say are the main differentiators that influence this choice between automation and augmentation in regards to planning?
Niels:
So I define six different drivers, which are different shades, automation versus augmentation. Is data granularity. So, at what level in the business planning cycle do you use data, do you need to know data? The decision frequency. So how often do you make a decision? Is that every second, every day, or once a year?
Data generation. So how much data do you generate in that business planning cycle during decision-making? What's your decision impact? Is it low or is it high? Is it worth $1, if it's worth $10 million. What's the system complexity? And the system complexity is all about what are the interconnectivities that support your decision? Is that within a closed environment, or is that in an open, microeconomic global environment? Which is a higher system complexity.
And then we got human centricity. So, what human centristic elements are a part of decision making? All right. If we talk about ethics, for example, yeah. Or if we talk about the failures and behaviors. We talk about very, very human centristic elements in decision making and they start to play a bigger role in the longer term horizon in business planning cycles.
Bethanie:
This is a really great table. I'm wondering if we could specifically go into at least one or two of these and understand more about how they relate to real business processes, perhaps IBP or ops.
Niels:
Yeah. Thanks. Now, look, I'll do that. And I'll have another picture to back that up, what the impact is then on process automation, augmentation, and human centricity. But so for example, data granularity. If I'm producing a product, I need to have information on the lowest level of detail, material level by machine, or work center. While I'm in an IBP, integrated business planning cycle, I'm talking about categories. How the category is going. Or if I talk about strategy, I'm talking even about countries or macroeconomics. The data granularity grows there, which has an impact on your augmentation and automation.
Another one is, for example, decision frequency and execution. I make decisions every second, or minutes. But even within the seconds, decisions need to be made to produce a product. And if I go to the sales and operation execution horizon, that's maybe more days. Okay, where do I have to move my inventory? Or what level should my inventory be? Et cetera.
Once I go to IBP or strategy business planning cycle, you talk about months or even years in terms of the frequency I make decisions. But these are really, yeah, some examples on how these six elements are different across those business planning cycles.
So, if we apply those six, there's six elements on the business planning cycles. And we look at where we can automate processes, automate decisions and where we can augment decisions. We see in the execution horizon, there's a very high opportunity for process and decision automation. Products that produce, that can be all automated.
The example I gave from the car industry, processes and decisions are highly automated. There's a tiny level, maybe a small level of decision augmentation, but it's really highly automated. If we go further into the horizon, sales and operation execution horizon, decisions are being made maybe hourly or daily. So, there is sometime for the business user to be actually augmented and get help from the machine to make better decisions.
However, processes on where I should produce, how much I should produce, where I should put my stock, which order I should fulfill and those decisions, they're quite still reasonably low value and high frequency. They can still be highly automated. Once I go into the IBP and beyond, business planning horizon, really, the decision impact becomes really high.
And usually, when the costs increase, of course, human intervention increases as well. And we need to have some sign off. We need to have some debate. We need to have some collaboration. So the decision automation goes down there. However, we can still automate some of the processes before we make a decision.
And decision augmentation goes up. We want to have advice on the decisions we're making. However, we don't want to automate them because yeah, they might be too high value, or even really, too complex to automate. Once you go through strategy and visioning, yeah, it's very humancentric. I don't think there's any process automation, decision automation possible in strategic and visioning choices. And even decision augmentation is rather low.
We can get some help of course, from predictions and long-term trends and what have you. And gaming, wargaming, for example. However, that augmentation stays rather low. So, the conclusion of this is, we see increased human centricity the longer the planning horizon. And we see more opportunity for process and decision automation in the shorter term horizon.
Bethanie:
Super interesting. Now, let's keep going on that theme of human centricity. Let's talk more about where humans are in this. What is their role in this future, considering how much automation is coming into play?
Niels:
Yeah, look. So, there's absolutely no doubt that it has a big impact, automation. And it already has. What we just discussed automation in the production, in warehousing. And we see it happening around the world and in transport. There's no stopping it and it will have an impact on the workforce there.
However, if you look at an automation leader like Amazon. And they committed $700 million to retrain their employees, or a big part of them. Up to 2025, they committed $700 million to retrain them. So, they take them out of that manual labor force and teach them, or educate them on data or IT architecture or other, say more value added elements in Amazon enterprise. So, there's opportunity there as well for people that work more in the executional environment.
Now, if we go beyond the execution environment, in sales and operation execution, in IBP, I think supply chain planners and the managers have actually a great opportunity to do better work and do more work and more interesting work. I mean, the average supply chain planner actually spends 50% of their time on gathering data, tinkering with it, even before the analysis starts and before they can extract some value out of it. That can all be automated for them.
And a lot of the short-term decisions, where they are not firefighting they're doing now, that can all be all augmented for them. They can actually, can get advice from a platform, from a system on what they should do. So that means they have more time for more strategizing, for collaborating on the right stuff, with their colleagues, or with their customers or with their suppliers. And actually, those capabilities will be more required in the future, I think.
So what we see is that yes, if you're in execution, you will get hit and you are already hit. But we see the leaders are investing to improve that. And I think if you're in supply chain, if you're in a bit longer term horizons, there's actually an interesting change for you.
And yeah, you will work with new capability and you will be augmented by the machine. You have to collaborate with the machine. Which yeah, it's going to be a whole new era, which I believe is interesting for the supply chain professional.
Bethanie:
Very interesting. And I agree. So, how would you summarize all of this, perhaps, if you can, in just a couple key takeaways?
Niels:
Well, I think supply chain leaders really have to start thinking about this. Okay. Where does automation lead me? What's the human role? How should the human collaborate with the machine? Where should the human be augmented? And how does it impact my talent, my need for talent? How does it impact my operating model?
They have to start thinking about that now. There's no going back from automation. There's no going back from the technology advancements we have seen over the years. It will only grow further. So, supply chain leaders have to be ready for that. Understand the differentiation between automation, augmentation, human centricity. The handovers, the collaboration between human and machine.
And again, there will be bumps in the road. And this is not maybe straightforward in the first go, but supply chain leaders have to start working on humans working with the machine in the future of work.
Bethanie:
Awesome. Those are all our questions for today. Thank you so much for taking the time. And until next time.
Niels:
Thanks for having me, Bethanie.
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