Don’t fight the future: four steps to developing an adaptive operating model
The Matrix is everywhere. It is all around us. Even now, in this very room. You can see it when you look out your window or when you turn on your television. You can feel it when you go to work... when you go to church... when you pay your taxes.Morpheus in The Matrix, 1999
Technology hasn’t become The Matrix (yet!), but it is pervasive and changing at an increasingly rapid rate. Organisations cannot ignore technology change; those that want to survive and thrive must adapt to it. How does an organisation adapt to technology change? Must it run on blockchain? Must it move to the cloud? Must it have in-house data scientists? The truth is that some organisations might, but not all organisations. The keys for an organisation to adapt to technology change are the same as for any other change: knowing its customer, knowing itself, making educated guesses about the future, and measuring its performance. Unlike technology, these keys will never change.
If you feel like technology is changing faster every day, it’s because it is. Anyone who’s studied computer science or read enough business articles will be familiar with Moore’s Law: the computational power of computer chips doubles every two years. But, it’s not just processing power that is growing exponentially; data storage, DNA sequencing, and internet bandwidth all are, too. There’s a wide range of evolving technologies which affect business models, business strategies, and operating models. Organisations ignore these technologies at their peril.
Research from Innosight shows that, while in 1964 it was 33 years, in 2027 the average tenure of companies in the S&P 500 will be only 12 years (that’s not even a teenager!). It’s easy to find examples of failed industry giants: Kodak, Blockbuster, Borders, the list goes on. The thing that connects them was their inability or refusal to adapt. Charles Darwin is often misquoted as saying, “it is not the strongest that survives; but the species that survives is the one that is able best to adapt and adjust to the changing environment.” Just because Darwin didn’t say it, doesn’t mean it’s not true (at least, not in a business sense).
Innosight’s research also finds that the primary driver of this disruption is technology change. So, how should organisations adapt? Must every organisation become a technology organisation? No, they mustn’t (at least, not every organisation). In fact, of the World Economic Forum’s top ten skills for 2020, none are technology-based. Organisations must adapt to technology change the same way they adapt to any other change: by knowing their fundamentals. To survive in the age of disruption, organisations must know their customers, know themselves, invest in themselves to deliver for their customers, and measure their own performance.
- Know your customer (KYC): to truly bring value to the marketplace, an organisation must first understand its customer. Every organisation should ask themselves, “what problem do we solve for our customers?” Next, an organisation should question whether it is solving that problem in the best way: is its product or service the most appropriate for the customer’s needs; is its business model? Lastly, an organisation should use this customer insight to ensure its strategy delivers value to its customers.
For example, General Motors traditionally sold cars, helping customers solve the problem of getting from A to B. With new technology enabling alternative transportation models, customers are increasingly eschewing car ownership in favour of ride sharing through apps like Uber and ViaVan. In response, General Motors developed a strategy based around delivering transportation services, as well as cars themselves.
- Know yourself (KYS): Once it understands its strategy for creating customer value, an organisation must ensure its operating model (i.e. a representation of what it does; how it interacts with customers, suppliers, and the market; how it is structured internally to deliver its products and services; and how it plans to evolve over a set time period) is aligned to that strategy. After all, a strategy is only as good as the mechanism by which it is implemented. Research has shown that organisations with defined operating models reported 33% higher customer satisfaction and a 34% advantage in new product development.
For example, one of IKEA’s core capabilities for delivering its Cost Leadership strategy is procurement. So, it deliberately locates its procurement teams near key suppliers to strengthen relationships, thereby helping to achieve 95% inventory rates.
- Guess the future (GTF): To make correct investment decisions consistently requires three pieces of knowledge: what customers need, what internal capabilities best meet those needs, and what future technologies will best enhance those internal capabilities. No organisation can get all its investments correct, because no organisation can predict future technologies. By at least knowing what its customers need and what internal capabilities best meet those needs, an organisation increases its probability of investment success. By running proof of concepts or pilots within or alongside the core business, an organisation reduces its probability of investment failure. In these ways, leaders can ensure the known investment cost is outweighed by the expected benefit to its internal capabilities and, ultimately, its customers.
Pro tip: Understanding customers (step one above) and internal capabilities (step two above) increases the chance of successful investment. Trialling new concepts in contained environments reduces the chance of unsuccessful investment.
- Measure the present (MTP): Analytics and insight are the basis on which an organisation understands and adjusts its performance. It is also crucial for evaluating return on investments and improving future investment decisions. Quality operating models cascade top-line goals into specific metrics at all levels of the organisation allowing issues to be accurately identified and addressed. The best operating models produce and use those metrics in real-time to drive continuous improvement, thereby addressing issues before they become too costly. Emerging technologies like advanced data and predictive analytics will allow measurement to become not just real-time, but also predictive. They can make links in unstructured data to identify previously hidden patterns and insights, identifying issues or opportunities before they occur.
For example, using a combination of its own and its customers’ data, PepsiCo uses data analytics to manage its supply chain by aligning production with demand. This ensures its customers get the right products in the right volumes at the right times.
Technology change will only continue accelerating, not slow down, and nobody knows where it will take us next. Trying to predict the future of technology is not a recipe for success. But organisations can maximise their chance of success by understanding their customers, themselves, and their performance. Minimising the number of unknown variables will maximise the probability of success.