Digital 1.0: It is really all about speed
Most of digital to date, Digital 1.0 if you will, has improving speed of response as a primary strategic imperative. For a transaction to be “digital”, it must be immediate enough to react to a customer’s enquiry in real time, via interactive tools and smartly automated processes. For an organization to be “digital”, it must be able to answer most customer queries in real time, catering to customers’ needs as they happen.
For organizations, this means corralling all the information into one “live” source, or at least papering over the cracks to be able to answer most queries or any query where a non-response would prevent a transaction from completing. Digital 1.0 is also about keeping the customer informed with live data—to reassure them that the parcel will arrive, the taxi will come, their plane is on time, which part of the mortgage process their application is stuck in, and that their meal is currently 5 mins away on the A316 by Twickenham Green.
Particularly for transactional queries, this largely pivots an organization to deliver its information to the front office so that customers are able to get this response and enjoy live information flow, with reactions reduced to seconds for simple enquiries. Obviously, the timeframe varies for different industries’ products and services—but ultimately this means a big reduction in processing time and decision cycles, even for complex products like mortgages. Even where processing times cannot be reduced, customers are kept better informed and engaged by live process updates.
Exhibit 1 shows the amount of change companies are currently facing and how much they fear in the future. More than a quarter fear existential disruption in the next 2 years. As you can see, 48% of business leaders experienced existential or significant operational change driven by digital. Yet, this is not the end of the digital shake-up; 58% anticipate similar levels of change in the next two years.
Exhibit 1: Existential requires existential action
Source: HfS Research in Conjunction with KPMG, “State of Operations and Outsourcing 2018, March, 2018. Sample: Enterprise Buyers = 381
Beyond Digital 1.0: You need to anticipate customer requirements
The most disruptive impacts of this first wave of digital are the enormous amount of additional data and the more powerful access and analysis techniques available to apply to data from customers, supply chains, and processes.. This desperate need for rapid and relevant data can have profound impacts on the way organizations develop their products and services and how they target current and potential customers. This is the next wave of disruption and the next step in the digital journey—and the one that will have a bigger impact on operating models than the somewhat superficial levels we’ve seen so far. The data is where disruption happens. Netflix, Uber, get created when talented Silicon Valley types have access to this information.
Usually when we think about the maturity of operating models or disruptive technologies, we think in terms of hierarchical progressions: organizations achieving x and y will now be a Digital 2.0 organization. Or that there is a deterministic inevitability about how organizations will evolve to survive in the digital world—a form of digital Darwinism. However, what is becoming clearer is that organizations are forging their own paths with digital, prioritizing elements that would be last on the list for similar businesses. For example, if personalization is core, then driving the speed to insight is important. If it’s a consumer service, the key is keeping the buyer informed. Innovation cycles for a video streaming service are going to be shorter than for an insurance company. We simply don’t believe that the digital evolution will be a simple process. To add sense to this changing environment we have mapped out a maturity model for digital (see Exhibit 2).
Exhibit 2: Which digital gear are you in?
Source: HfS Research
Let’s tackle the first myth of digital head on. You cannot achieve maturity simply by shifting to the right via an accumulation of components, although this will happen within each of the digital strategic imperatives, and can be seen holding an intrinsic value on the vertical axis on the chart. However, true maturity is achieved through an accumulation of maturity across the imperatives.
Assessing the stages of digital maturity
At its core, digital maturity will be about the ability to deliver faster responses, quicker insight, and the adaptations of processes when markets inevitably shift. It will also be about how integrated the underlying processes are that make this happen. While an organization can make assumptions to paper over the cracks of missing information to make a transaction happen, a more digital organization will be working from more accurate and consistent live data on, for example, stock availability, risk profiles and personnel.
Broadly speaking, the layers of maturity are defined as follows:
Single speed: Speed of response
The first wave of digital transformation was driven by the need for digital transactions. The number one organizational imperative is the speed of response and transactional information flow to provide information to customers in the absence of a physical relationship. We can see different levels of Digital 1.0 maturity in these examples of food delivery services in the UK.
- Level 1: The customer purchases food online and is given superficial information about the purchase, but the live data is not real. My local Indian restaurant, for example, let’s me order food via an app and gives me an estimate of how long it will be until my food is delivered, but the estimate is always the same! Another example is the Just Eat app—I get to choose from lots of restaurants, but there’s no live data on where in the process my meal is.
- Level 2: The customer purchases food online and is given some credible real time information, such as the meal is being cooked or the driver is out for delivery. The Domino’s Pizza app tells you the pizza has been cooked and it is out for delivery.
- Level 3: The customer purchases food online, and is given accurate real-time information about the cooking and a real-time map showing where the driver delivering the food is currently located. Deliveroo and Uber Eats provide this level.
- Level 4: This scenario would actually shift food delivery into multi-speed because it requires more insight. This would include better delivery time prediction and tailored recommendations. Shifting into automatic when it anticipates customer needs and helps the organization respond.
Multi speed: Speed of insight, speed to market
Speed of insight and speed to market are the organizational imperatives that come into play for multi-speed digital organizations, where data collection can help drive both macro and micro decision making. Macro decisions drive the strategic direction of whole parts of the company and micro decisions fuel, for example, risk analysis and price-setting. Having the right data to anticipate customer needs and support decisions that serve customers ahead of time delivers significant digital competitive advantage, for example being able to predict when demand for pizza delivery orders may spike outside of obvious events like the Super Bowl—such as during the finale of Game of Thrones. Having data on the effectiveness of different forms of advertising tailored to various products could help with marketing, such as profiling users on Facebook or LinkedIn who might spend $200 on a laptop bag.
You could argue that the big imperative is maturity of speed of response; certainly that is the most visible outcome for organizations on this stage of their journey. The disruption is more noticeable in multi speed digital than in single speed, fuelling such phenomena as fast fashion. Consumers follow fashion trends online and through social media feeds from celebrity bloggers and vloggers, which can cause huge peaks in demand on single items. This helps create demand for ever-faster fashion product life-cycles—cementing the importance of the online part of these businesses. Another side effect is supply chain compression. To an extent, the process is cyclical: retailers and designers are both driving and being driven by speed to insight and speed to market.
Automatic: Speed to anticipate, speed of innovation
In the automatic stage, elements begin to converge. As digital shifts into automatic, the challenge is building an operating model that quickly reacts to change; organizations must quickly react to disruption and then drive disruption themselves. There are two key pillars to the automatic stage: speed to anticipate and speed of innovation.
Speed to anticipate is the first key pillar. As an organization’s overall operating speed increases, it will need to automate more micro decisions. This will enable businesses to react to customer demands based on insight at a sustainable speed and scale. It will also enable them to react to changing industry conditions and divert resources into parts of the organization based on ebb and flow.
The second key pillar is an enterprise’s speed of evolution and innovation. Organizations that merely react to the disruption around them won’t be successful; instead, they should drive the disruption within and without. Let’s take another look at fast fashion where, as with many companies in this pillar, product life cycles are compressing. Fast fashion finds value at this stage by being able to deliver human creativity as efficiently as possible. As speeds to market increase, organizational agility will need to improve—this is about the organization as a whole being able to respond to speed to market ramping up on a large scale. Crucially, underlying processes will have to adapt.
We can see the beginnings of this type of automatic organizational adjustment and innovation in the fintech world as enterprises shift from using data for targeting customers better to using data to redesign and build more customized and customizable financial products, particularly as some customers are demanding more individualized services and the banks are hoping to differentiate with this type of product.
Technology language is driving the operations agenda all the way to the software defined-enterprise
One of the reasons we are thinking about digital’s progression in this way is that businesses are subtly adopting the language of modern IT and applying it to operating models, particularly cloud and as-a-service. Organizations and service providers are talking about hybrid operating models, partly in reference to the mix of technology underpinning them but also referring to the evolved and unevolved processes that make up parts of an organizations business.
We are also hearing IT terminology such as orchestration, as-a-service, on-demand, virtual, and virtualization being applied to business process and operational transformation.
The combination of IT and operations is at the heart of HfS Research’s Digital OneOffice model. One of the impacts of this alignment is making the organization more agile; taking this one step further we can envision a future in which a large part of enterprise operations can be, like many IT organizations, more software enabled. Exhibit 3 shows how this might work as the more digital the process the more management control an organization is able to apply.
Exhibit 3: How software-defined is your enterprise?
Source: HfS Research
Ultimately as an organizations operations are more unpinned by end-to-end digital processes the organization as a whole becomes more controllable—much like virtualization allows more control of IT process within a software-defined data center. The more digital the processes the more elements of the organization can be measured and defined via the operating framework.
Bottom line: The next wave of digital will require faster, better controlled operations. Change gear before your competitors.
The big barrier to overcome, at least when buying services to provide digital transformation and digital operations is the current procurement department. Digital transformation services often come without a defined path and require a degree of experimentation, which requires a new style of vendor management that looks at the whole journey and sees failure as part of an iterative process. Businesses’ adoption of IT language is a sign of C-level management’s acceptance of not only digital, but also of the broader impact of technology on business and that businesses need a symbiotic relationship with IT. This means decision making is elevated; for example, we spoke with the CEO of a large manufacturing organization that dumped both its IT and its digital organization because neither was doing what the business needed to succeed.
The speed of information flow was the fundamental force that enabled the first wave of digital—specifically the speed to transaction. Delivery complexity depends on how complex the product and services are. For some simple products that are warehoused and then shipped, delivery is not terribly complex. Complexity comes with planning stock levels and ensuring the overall supply chain is dynamic—while also developing data analytics that enables the prediction of rapid peaks and troughs in demand. Better, faster information drives this dynamism—this can only be achieved with a truly digital (1.0) organization where live transactional information is held and accessed end to end.
Leveraging the opportunities presented by the next wave of digital requires an even faster response, which makes automation a must-have. It also means knowing how to accelerate the analysis of data, which will force enterprises to look for better systems for not only extracting insight from data, but also applying this insight more speedily. However, the most important thing is that this next level of digital will drive down response times while keeping customers informed in real-time when issue occur, alongside speedier resolution times—an obvious boon to customer experience.
To reach this digital nirvana, however, the trend of increasingly aligned digital and physical operations will need to continue, supported by the realistic possibility of a software-defined enterprise.