The nature of what the digital revolution means is evolving as organisations adopt digital in more mature and fundamental ways and as AI becomes an increasing factor in organisation's digital strategies.
Digital started at the edge of the organisation, where the organisation touches its customers and has evolved ever deeper into the organisation to where it now enables completely new ways of creating and delivering value.
This evolution is a continuum of change. But, I find it helpful to divide it into four distinct phases.
1. E-commerce
The first phase allowed businesses to market and sell their (existing) products and services to more customers more easily over digital channels. It started with marketing. Using informational websites, email and social media to reach customers. It gradually grew to include selling and eventually servicing.
This first wave of e-commerce is often referred to as Web 1.0. A myriad of startups flooded the market selling everything from books to pet food, whilst established pre-e-commerce business struggled to keep up. The inevitable bust which followed the boom left a much smaller number of massive winners (think Amazon.com), a much larger number of failures (think Pets.com). Almost no businesses exist today without a website.
E-commerce had more fundamental impacts on business strategy, though. Most importantly, it exposed how a lack of integration within the organisation and its system made it difficult if not impossible to deliver coherent DIY and self-service solutions to the end customers. From this, the concept of customer-centricity was born. (Although this term has now taken on a life of its own and been widely misappropriated.)
2. Supply chain automation
Whilst the focus of this first phase of e-commerce was on end consumers, the second phase tackled the B2B relationship between corporate buyers and their suppliers. B2B e-commerce sites quickly evolved to provide more direct integration between buyer and supplier systems. Standards, such as XML, evolved to facilitate this, and more recently we've seen a drive towards API-first business models.
Supply chain automation makes existing exchanges of information more efficient. It also increases the flow of information. For example, RFID allows retailers, distributors and manufacturers to track stock levels and movement, automating stock management and better integrating with robotics.
Not only did this improve efficiencies, with smaller orders and faster delivery cycles, but it also allowed previously monolithic organisations to disaggregate into networks of smaller interdependent and more specialised suppliers.
In 2017 McKinsey & Co estimated that whilst 49% of companies invest in E-commerce, only 2% of companies invest in digitalising their supply chain. A more recent 2023 study by PWC, found that 83% of executives said their supply chain technology investments haven't fully delivered expected results and that few said their companies are using or panning to use technology to enhance the execution of their supply chain over the next 24 months. A 2024 study by KPMG, in contrast, found that 50% of supply chain organisations will invest in application that support AI and advanced analytics, and that 2/3rds have already adopted low-code int their supply chains.
3. Workforce automation
With both the customer and supplier ends of the value chain being digitised it was inevitable that digitisation would begin to encroach on the work done by employees in between.
Although we've had expert systems for many years, it is the development of digital customer and supplier interfaces which generate the data required to move them towards true artificial intelligence. For an explanation of this effect, see More data usually beats better algorithms.
The now general release of Generative AI has significantly accelerated this trend.
Information-based jobs will inevitably be hardest hit first. Think of insurance underwriters and claims managers, fund managers, accountants, etc. But inevitably most jobs with any element of repetition will be impacted. Taxi drivers are at risk from autonomous vehicles, for example, and there is already talk of robots performing some surgeries more accurately than skilled surgeons. There is already evidence that banks are hiring fewer people with finance backgrounds to do the work, and more people with technology skills to automate it.
I prefer to think of workforce automation in terms of augmentation, rather than replacement of people. The industrial revolution provides a well-established narrative of technology replacing labour and yet somehow creating new and different jobs in the process. Most of us are grateful that we don't have to do the heavy labour now replaced by machines. And future generations will be grateful not to have to do some of the repetitive and uncreative jobs many people do today. (The emerging millennial workforce is already rejecting much of this kind of work.)
Ultimately, however, we should expect that computers and machines will eventually become better than humans at all tasks.
It strikes me as anachronistic that organisations are slow to adapt and to provide their employees with the same level of tools to use in their jobs as other companies provide them to use as their customers. Ultimately, this flows through into the customer experience when call centre operators are unable to provide quick and definitive solutions, leaving you with the impression they are still switching between multiple disconnected systems to get answers and process requests.
4. Digitisation
The resulting end-to-end digitisation of the value chain opens up possibilities. Not just for delivering existing products and services more effectively. But also for creating entirely new products and services.
Again, this started with information-based products. Think of the development of subscription-based streaming media services, compared to purchased physical media or broadcast services. But it is now moving increasingly into physical products as well.
This is enabled by the Internet of Things (IoT): a network of sometimes semi-autonomous things able to sense elements of the real world and communicate with each other and controlling systems. Already we have devices fitted in cars which can collect data about the performance of the car and can communicate this to service technicians and insurance companies. We also have activity trackers. These measure things like sleep, activity levels and heart rate on a continuous basis. They upload this data to servers for more detailed analysis.
Of course, it is still hard to imagine where this could go. Imagine that your calendar/organiser is able to determine where you are now, where you need to get to for your next meeting, and can arrange for an autonomous vehicle to take you there, all without you needing to do anything.
Note only does digitisation replace or enhance physical products, and create completely new entirely digital products, it also often develops whole new ecosystems of digitally connected organisations, people and devices which collaborate together in previously unimaginable ways.
In 2017 McKinsey and Co research suggested that 70% of companies approach digitisation without changing their overall strategy, but that the 30% that do, generate 3 times the profit. More recently, in 2021, an Infosys MIT Technology Review survey of more than 250 business leaders and senior executives revealed that more than half of the enterprises realised new business models because of participating in the data economy. (Source)
When I look at offices and factories full of people hunched over keyboards, screens and other equipment, I always get the sense that somehow it is the people working to satisfy the requirements of the machines. I read today a prediction that in 10 years time, most interfaces will not have a screen. I believe that is because the machines will talk to us, as we now talk to each other, and talk to each other silently using some form of wireless protocol. In a fully digitised world with a fully developed IoT, you can imagine that finally, it will be the machines who serve the people, fading into the background as they do.
Lessons
I think there are two key lessons from understanding this evolution of digital strategy:
- Organisations who remain focused on e-commerce alone will eventually be outcompeted by those that embrace all four stages of digitisation. All organisations must now look at all four phases of digital in parallel in order to remain competitive.
- Organisations where a high proportion of the total labour cost is direct (that is directly proportionate to the volume of products and services provided to customers) rather than indirect (that is devoted to researching and developing new and improved propositions) will fall behind. Employees should be firmly focused on creating new sources of value, and not delivering existing sources of value.
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