The 4 Stages of Digital Transformation

Digital technologies play a transformative role in modern economic life. However, most companies are still struggling to understand how to capture the various types of value these technologies provide. It is not easy to develop a strategy that fully leverages the digital value of these technologies. Firms often assume that digital technology will bring about a digital transformation without a thorough assessment of the potential benefits. Many firms make haphazard business decisions regarding digital technology and end up losing competitive advantages despite large investments.

Let’s take a look at the following four examples to get an idea of the value digital technologies can bring. Each one highlights the strategic benefits available at a different stage of digital transformation.

Stage 1: Operational efficiency. Ford uses augmented and virtual reality, the Internet of Things and AI to automate inspection of paint jobs at its plants. These technologies allow Ford for blemish detection in real time and reduce defects in its cars.

Stage 2: Advanced operational efficiency. Caterpillar places sensors on its construction equipment to monitor how each one is being used at construction sites. For instance, it discovered that customers used their motor graders more frequently to level lighter gravel than they did to level heavy dirt. The company uses this information to create a motor grader that is more cost-effective and specifically designed for gravel than dirt.

Caterpillar, like Ford, also benefits from operational efficiency improvements by increasing product-development productivity. However, the difference is that Caterpillar’s sensor data comes not from manufacturing plant assets but from customers who use their products. This customer dimension presents additional challenges.

Stage 3: Data-driven services based on value chains. GE monitors product-sensor data from jet engines and analyzes it with AI to provide real-time guidance to pilots so they can fly in ways that maximize fuel efficiency. GE then takes a portion of the cost savings made by their customers through new annuities that are based on “outcome-based revenues”. In other words, their customers pay GE a portion of the fuel savings they make and what they pay for product.

This initiative involves changing the business model of GE from one that is focused on selling products to one that offers data-driven services for digital customers. GE’s R&D and product development departments as well as its after-sales services units are digitally connected to collect, analyze, share, create, share and react to IoT and sensor data from thousands upon thousands of discrete products. This creates new revenue streams and improves operational efficiency.

Stage 4: Data-driven services using digital platforms. Peloton uses product sensor data from its exercise equipment in order to build a community and match users with the right trainers. Peloton’s products produce user-interaction data which is used by the company to facilitate interactions between its customers and third-party entities that are not part of its value chain. Artificial intelligence algorithms match users with suitable trainers by analyzing product-user interaction data. This is similar to how Uber matches drivers and riders using data from their apps.

Peloton is generating new revenue from its data-driven service. It’s doing so by extending its products to digital platforms. This stage of digital transformation can be particularly challenging for legacy industrial-era firms and firms with limited experience with digital platforms and value-chain-driven business models.

Drivers for Digital Value

For these four stages of digital transformation to be properly understood, it is important to first recognize two key value drivers for modern digital technologies: data and emerging digital ecosystems. Let’s take a look at each one.

Data. In the past, data was episodic generated by discrete events, such as the shipment from a supplier of a component. But data is now interactive and generated continuously by sensors and IoT to track information and act upon it. For example, you can transform the user experience by embedding sensors in certain products. Smart mattresses can track user’s heart rate, breathing patterns and movements and adjust their shape to suit users’ needs. Sensors embedded in cars can give feedback that allows people to drive more cautiously.

This interactivity, more fundamentally, reverses the roles products and data play. While data has always supported products, it is increasingly becoming clear that products now support data. Products are no longer limited to delivering functionality or helping build brands, nor do they generate revenue. They now serve as conduits for interactive information and source of new customer experiences.

Firms need to have a network of data recipients and generators in order to take advantage of interactive data’s expanded role. These networks can be created by IoT-enabled sensor connectivity.

Digital ecosystems. There are two main types of digital ecosystems that have emerged. Neither existed prior to the advent of data and digital connectivity. The production environment is one type. It includes digital linkages within value chain. For instance, car companies can provide predictive maintenance services by linking sensor and IoT data from cars with spare-part suppliers, warehouses and service dealers. Another type is the consume ecosystem. This involves networks that are not part of a company’s value-chain. Smart street lamps with gunshot detection capabilities can be thought of as smart light bulbs. Their consumption ecosystems consist of a network that includes camera feeds, 911 operators and ambulances. All of these help improve street safety.

Interactive data can drive new value in both production and consumption ecosystems. This holds true across all four stages discussed in digital transformation. The production ecosystems are the foundation of the first three stages The fourth relies on consumption ecosystems.

Which Stages Are Right for Your Company?

To determine your optimal digital-transformation strategy, assess your need to engage at each of the four stages and then focus on investments that will help you harness the benefits of interactive data and digital ecosystems.

Stage 1. The vast majority of digital-transformation initiatives take place in this stage, which is especially important if operational efficiencies are a big part of a firm’s strategic thrust. For example, oil and gas companies have billion-dollar investments in pipelines and oil wells. These companies can save up to 60% on their operational costs by using IoT devices, AI, and AI to locate reserves and maintain pipelines and assets. This stage faces key challenges, like including the installation of widespread interactive data generation for asset utilization and breaking down silos around data sharing.

Stage 2. Companies that sell products that can access interactive data from their users. This data can be used for strategic advantages beyond those available at stage 1. This category includes many consumer-packaged goods. Interactive data is used in these businesses primarily to improve product-development and advertising efficiencies.

Stage 3. Companies that recognize they can create data-driven services using products and value chains are in stage 3 of the digital transformation. To increase their strategic advantage, such firms will need to enrich their production ecosystems in order to generate new data-driven services.

This stage allows firms to cross a critical barrier. Instead of using data for operational efficiency, they use it to generate revenue. Stage three is for companies that don’t have access the consumption ecosystem. Although sensors and AI-equipped dishwashers are able to anticipate component failures and offer predictive services, they’re difficult to connect to digital platforms and other objects. However, many firms overlook the potential consumer ecosystems for their product or think it is too risky to expand their products onto digital platforms. This is a common trap for many companies and needs to be avoided as the examples of Nordic Track and Peloton show.

Stage 4. At this stage, emerging consumption ecosystems are of strategic importance for firms. Firms that remain within their production systems run the risk of being commoditized. Their key challenge is to extend products to digital platforms.

Not every company will be able or willing to transform on all four stages. While some may choose to concentrate on one or two stages all firms must be aware of the growing number of possibilities. Opportunities abound, and a thoughtful digital-transformation strategy, based on the framework presented here, will help companies remain relevant in the modern world.

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