The traditional view of data is as a cost that must be managed—an overhead. But now, data is an essential source of competitive advantage.
The COVID-19 pandemic has demonstrated the need for companies to be on top of their data, with customer behaviors changing beyond recognition.
It’s time for CEOs to see data as capital to grow and ultimately reinvent their businesses.
Your relationship with data is about to become one of your closest relationships (if it isn’t already). If you can make it core to everything you do, data becomes the new asset class: the fuel for an adaptable business strategy, the shortcut to productivity, and the route to entirely new opportunities.
Data as an asset: The status quo and the burning platform
We all know data volumes are exploding. In 2018, more than 50% of the world’s population was connected to the internet for the first time. This stat alone is a powerful proxy for the data pools that now exist. It’s never been cheaper or easier for human beings and businesses, governments and institutions to interact with each other.
The traditional view of data is as a cost that must be managed—an overhead. But in a digital world, data is now an essential source of competitive advantage. In fact, data is now its own asset class, alongside traditional business assets (such as physical or human assets).
So who recognized its value first? Traditional companies are familiar with developing data strategies for their businesses. But digital natives were faster to understand the potential to develop a business strategy for their data. That is: using their data as an asset, a source of return on investment (ROI) in its own right.
The COVID-19 pandemic has demonstrated the need for companies to be on top of their data, with customer behaviors changing beyond recognition, coupled with crisis-driven innovation and immediate needs for employee safety and experience. More than ever, businesses must be relevant, and to do that, they must harness their data.
So what do companies need to do differently to compete? They must move on from business models that apply digital to traditional approaches and become digital at their core.
Fundamentally, that means doing three things:
1. Treat data as an asset class
Make data central and cyclical.
2. Adopt new business models for data value
Connecting customers through platform models.
3. Develop the flexible mindset to match
AI-fueled business models move faster because they behave differently.
Here are some practical reflections on the steps ahead.
#1: Treat data as an asset class
Make data central and cyclical
How is it that companies like Amazon, Netflix and Google have business models that seem to shapeshift at the flick of a switch? Answer: it’s because their business strategies are driven by intelligence developed from thousands of curated, critical data points. Their data is the key to being able to spot market trends before the competition, and evolve strategies in close to real time.
The key to getting there: scale intelligence and deploy it to the front line (and customers). It sounds obvious, but the idea is that the AI experiments need to leave the lab.
Data and AI are—unsurprisingly—vital to establishing a data-centric business and well as creating productivity gains in the current model to invest in the new one. With automation projected to handle up to 45% of repetitive work, employees are freed up for value-add activities. And the productivity savings can be significant: Accenture analysis suggests up to 10% of tasks in the North American financial services industry could be automated by 2025, generating cumulative productivity savings of up to US$140 billion between 2018 and 2025.
But when you’re deploying these technologies, the real challenge is this: scaling them to the point of delivering the right results. It’s a development challenge rather than a procurement project—and therefore more cyclical in nature, like Amazon’s Flywheel model. It establishes a perpetual cycle of gathering data, analyzing, creating new products or services that entice more customers, creating more data…and on it goes. And every stage of the process is constantly monitored and optimized. Everyone at Amazon understands how it works and how to keep it fed with data. And it stands as an example of how to be a data-driven business.
Up to 10% of tasks in the North American financial services industry could be automated by 2025, generating cumulative productivity savings of up to US$140 billion between 2018 and 2025.
— ACCENTURE RESEARCH
And this type of approach is being adopted more broadly. Think of banking. Neobanks are using data to create different interactions, and bring people network propositions. And generally speaking, customers love them. It’s about giving people what they want, at low cost—all powered by data. And this principle stands, whatever type of bank you are. Accenture research suggests a correlation between banks’ digital maturity and their commercial success. And with just 13% of banks estimated to be digitally mature (and already reaping significant benefits), the space is wide open.
And for another industry: let’s look at Vodafone. Its Intelligent Care model manages customer contacts in a whole new way, taking cost out while revolutionizing customer experience. Using data and analytics, Vodafone can predict pretty accurately when customers will call (e.g., when they’ve just returned from overseas and may now have a higher bill than usual) and send them a proactive text to explain why. The customer is freed from having to contact Vodafone, and cost to serve is lower. And when you do need to call, their data models may well know why, and send you a text with an online link for the service they think you need (so you hang up and self-serve, for better results all round). And here’s the crux: the data is the essence, not the add-on!
We know that under duress, customers want to talk to a human agent. The pandemic escalated that need like never before, with close to 60% of customers wanting to speak to a person about their situation.
Data comes into its own in the black swan event
To change the data relationship, businesses must put data at the center of their processes and functional capabilities. Recent months have demonstrated the value of being able to interpret insight and signals and act faster than ever before.
To change the data relationship, businesses must put data at the center of their processes and functional capabilities.
And the smart money is on applying the same approaches to employees, with the employee experience and relationship with the employer becoming critically important. In 2020, employee engagement took a significant hit, with more than 50 percent of United States employees “disengaged” (the lowest drop in employee engagement since 2000). And this matters: numerous sources suggest companies that make their employee experience (EX) a differentiator outperform their rivals in earnings. Companies are having to reinvent their entire employee value proposition (EVP). And that means increasing personalization of the EX, fuelled by…you guessed it…data.
COVID-19 has amplified the importance of that employee value proposition. In 2020 Karmarama (part of Accenture Interactive) took the pulse of the UK during lockdown and shortly after. More than 60% of people in the UK planned to spend more with companies that had treated their employees well. A true example of doing good and doing well.
Let’s not forget the need to be prepared for the black swan event in terms of customer contact volumes and needs (like Vodafone, you’ll be glad you had the contact strategy planned out and supported by AI, data and analytics). Here’s why: we know that under duress, customers want to talk to a human agent. The pandemic escalated that need like never before, with close to 60% of customers wanting to speak to a person about their situation.
Bet you’re glad you got those channels in place and data and analytics to re-route all those non-urgent calls, so you can be there for your vulnerable customers or those who really need the human agent.
#2: Adopt new business models for data value
Connecting customers through platform models
When data is fuel, you can use it to drive entirely new business models. One dominant example is the platform business model (which may also be a platform business). How is it different? While traditional businesses focus on delivering a specific product or service, platform businesses focus on connecting customers with what they need. They create value as networks, bringing an ecosystem of players together. And to do that, they must also treat data very differently. It’s their critical asset—and they organize their business to exploit it to the max.
percent of traditional businesses say that they expect their industry to be disrupted within the next five years, but 80% also say that they aren’t prepared.
They’re generating true disruption. Consumers are already spending less on food, entertainment and clothing as platform business models create deflationary pressures on prices for commoditized goods. Traditional businesses are seeing the trouble ahead: 93% percent say that they expect their industry to be disrupted within the next five years, but 80% also say that they aren’t prepared.
And with COVID-19 upending assumptions around footfall and customer behavior in 2020, companies are having to change their business models on the fly and in totally new ways. Look at Pret a Manger. It’s launched a drinks subscription service for £20 a month (YourPret Barista). Want up to five drinks a day? That’s your reason to visit. And while you’re there, you’ll probably buy lunch, or a muffin with your coffee, and remember your old buying habits as you transition back to the office. It’s a creative way to generate new footfall. And it may just work, with Forbes reporting a similar US model attracting more than 800,000 sign-ups so far.
When data is fuel, you can use it to drive entirely new business models.
And cross-selling for network economics
Traditional companies should look to augment their product/service business towards one enhanced by network economics. It’s not easy, as it requires thinking like a data business at all levels. This is both a practical issue of using data, but also a cultural one of how to embrace it.
However, once businesses start to put data and connections at their core, they will be able to find the products and service propositions that cater best to their customers.
For example, one financial service business suggests cheaper flight options to its customers when they’re booking a trip. They serve their customers by connecting to other services. They are not a travel agent or a price comparison site, but they are in the business of creating a great experience. And it supports their brand promise of helping customers save and spend better.
A network business model in a nutshell: how is it different?
The delta: decoupling from linear benefits (the 10x, not 10%, mindset)
So why work so hard for these new business models? The reason is simple: it’s a new way to decouple inputs and outputs, and break through linear growth for exponential gains.
Businesses should be aiming to make 10X improvements—i.e., boost their business by a factor of 10, not 1 or 2. And AI, data and platform models offer those expansive new opportunities.
Example: a leading consumer packaged goods (CPG) company has created a platform play by turning to B2B ecommerce. The idea is: they provide the platform (a marketplace) to 1) sell directly to small retailers not covered by existing distribution networks (= more sales) and 2) make the platform available for other CPGs to sell their own products directly for a fee (= new revenues). This new strategy accounts for more than half of the company’s incremental growth. And it’s a great example of economies of scale and new routes to market: not just B2B, but also B2B2C.
One key tool for decoupling inputs and outputs is cloud. It offers flexibility like never before for data storage and managing workloads; plus better server utilization rates, and more energy-efficient infrastructure. And the delta is big, according to Accenture's research: Our analysis of the largest public cloud service providers shows average enterprise-owned-to-cloud migrations can lead to an impressive 65% energy reduction and 84% carbon reduction. And migrations to public cloud can result in up to 30-40% total cost of ownership (TCO) savings.
#3: Develop the flexible mindset to match
AI-fueled business models behave differently, because they’re able to move faster. This changes the nature of how you go to market and the cadence of product/service development. But you have to get your head around it.
It’s about working differently, with a more flexible mindset. For instance: it may be better to pursue a series of smaller bets than fewer, bigger bets—even though many (or even most) of those small bets will fail. It’s about capturing insights fast, acting on the signals generated by those insights, and trying more new things, more frequently. And that type of approach is the determinant of whether businesses can adapt, not get left behind.
By way of example: over the last couple of years, Amazon has tested myriad financial service propositions for its customers, from payments to insurance. This constant experimentation enables Amazon to make its business better benefiting both the company and its customers. Contrast that with traditional financial services/payments companies: many will have a single project running at a time, spanning several years. If it does eventually go to market, it may already be obsolete by its launch date.
The fail fast culture is already making big players much more agile, with GlaxoSmithKiline (GSK) explicitly acknowledging that 95% of experiments would be likely to fail, but those that were successful would be worth it.
But it all relies on the right skills and the right teams. We found only 25% of employees feel able to use data effectively. It’s time to rethink the workforce, and many businesses already have, with upskilling, and reskilling high on the agenda.
It comes down to having a business strategy for your data (not just a data strategy for your business).
The final so what
Leaders must grasp the data-driven challenge and opportunity with both hands. This new asset class is coming at us all fast! (It might have taken years to get the first half of the world’s population online, but the pace of connection is going to increase. Just imagine the volume of new data created).
But getting your head around this is tough. While Accenture research shows CEOs want to become data driven, most admit to struggling to define what that really means and, more importantly, how to get there.
It comes down to having a business strategy for your data (not just a data strategy for your business). What’s your data worth to you and how are you going to use it as an asset? It pays to act now, as more and more companies understand this new paradigm: Rolls-Royce, for instance, has already established R2 labs with the explicit aim of delivering untapped value from data.
It’s time for CEOs to see data as capital to grow and ultimately reinvent their businesses and create the foundation for predictive and adaptable business strategies. If 2020 has shown us anything, it’s that flexibility and speed are the key to future success. Luckily, the tools are already out there to smooth the way, with cloud, for instance, poised to create far more flexibility, with big cost reductions and GHG emissions savings on the table.
It’s time to make your relationship with data central to your future.