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This week, we're taking a look at Complexity: the third concept in the VUCA framework. In this sense, a complex world means a world where you deal with many interconnected parts and variables, and large amounts of information need to be processed to make sense of all aspects and their influence.
Understanding Complexity
Many things drive Complexity – as almost anything can be complex. Therefore, this concept has many facets, but we will focus on a few prominent ones here. In last week's article, we discussed businesses are moving away from linear supply chains towards complex ecosystems. These ecosystems need to be managed. In the first article, we have touched upon globalization as a megatrend driving VUCA, which plays a significant role in understanding Complexity.
For instance, increasing globalization, through trade liberalization and emerging market growth, allows us to do business in many countries but, at the same time, introduces new competitors to the market. We see Complexity manifest itself, for instance, in the regulation of food packaging. For example: whereas in the EU food packaging primarily uses grams, the United States uses ounces. On top of this, the EU lists calories per 100 grams; the US lists calories per serving. Beyond packaging, there are various ingredients or additives approved for food usage in the US that are not in the EU – and vice versa.
However, when thinking about dealing with Complexity, the answer is not becoming less complex because this would often mean selling less or sticking to only one specific type of product. In dealing with globalization, increasing individualizations and regulations is more about managing Complexity than reducing it. We need to ask ourselves, how do I combine external flexibility with internal efficiency?
Managing Complexity
In a complex world, it is crucial to understand the cost of Complexity. Concretely, this means collecting and understanding the data that tells you which parts of business profitable, and which ones aren't, which improves performance. This allows us to optimize how to service customers and achieve maximum profitability, by balancing profitability and individual customer wishes. Using supply chain analytics platforms to do this, will show us where costs lie and enable fact-based decision-making. Good analytics help you understand what is just driving up costs, and what is bringing you profit.
Another pillar in managing Complexity is agility, for instance, through asset modularity and workforce upskilling. Agility towards the outside helps with efficiency on the inside. When I work with modules, it becomes easier to deal with outside Complexity because I can react to it much better. I can combine these modules in different ways, while at the same time, everything is already in place internally, allowing for efficiency. Modularization is a strategy often used in mechanical engineering or the automotive industry – where individual products are built from modules used in a large number of other products.
Finally, reviewing your asset strategy, including its geographical footprint, may help you manage Complexity. When your supply chain covers many different regions, this involves many stakeholders and legislators to take into account. We're witnessing a trend towards regionalization: even though this means the need to build up local supply chains, it comes with the benefit of agility, which, as discussed, is a strength in dealing with Complexity. Especially when taking into account regional legislation, a localized supply chain becomes easier to manage.
Summarizing: when managing Complexity, the ultimate goal is not to reduce Complexity, but rather to balance external flexibility with internal efficiency. In doing this, managing the cost of Complexity is essential: data and analytics can help you balance cost and Complexity to optimize profitability. Agility and modularization can help you increase flexibility without paying in efficiency. Reviewing your asset strategy and focusing on more localized supply chains can help reduce Complexity. In the next article, we will cover Ambiguity.
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