Enterprises need to put data at the heart of business strategy, but it takes more than just technology. What steps then must a business take to build an effective data-driven culture?
Clive Humby, the British mathematician who helped create the UK retailer Tesco’s Clubcard loyalty scheme, coined the now well-known phrase that “‘data is the new oil.” However, when he did so, he added a clear caveat that’s long since been forgotten.
“It’s valuable,” he noted, “but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc., to create a valuable entity that drives profitable activity.”
So it is with data. As Humby said, “data must be broken down, analyzed, for it to have value.”
This is the central challenge for today’s data-driven business. On the one hand, those companies that are using data effectively are reaping tangible rewards. Research from Forrester has shown that organizations with a system of data-driven insights are 140% more likely to create sustainable competitive advantage and 78% more likely to grow revenue. Forrester has even talked about some of these companies as predators, eating into established markets by linking insights to the user experience and continually optimizing.
On the other hand, other organizations are lagging behind, or even retreating from the concept of the data-driven business. A 2019 report by NewVantage Partners focused on organizations as large as American Express, Ford Motor Company and General Electric found that 69% had not created a data-driven organization, while over half were not yet treating data as a business asset. In fact, the percentage of firms identifying themselves as data-driven had declined over the past three years, from 37% in 2017 to 31% in 2019.
Most of all, while the “oil” of data keeps on coming, the “refinement” of big data analytics hasn’t matched the pace. IDC has forecast that the data universe will grow to 175 zettabytes, or 175 billion terabytes, by 2025, with over half that data flowing from new IoT devices. Yet Harvard Business Review reported in 2017 that less than half of an organization’s structured data was actively used to make decisions, while less than 1% of unstructured data was being used or analyzed at all.
To succeed in the digital economy, organizations have to turn this around, putting data right at the heart of their business strategy.
This means finding the right people to oversee and manage it, plus the right tools and technologies to analyze, categorize, store and secure it. True, there are risks if you get it wrong – including data protection fines, security breaches and subsequent brand reputation damage – but these don’t outweigh the opportunities. After all, Forrester’s analysts believe that insights-driven businesses are growing at an average of more than 30% annually and could earn $1.8 trillion by next year.
Of course, becoming a data-driven business isn’t simply a question of hardware and software. It involves changing processes and company culture. When the NewVantage Partners 2019 survey asked executives about the challenges to data-driven business, only 7.5% cited technology as the challenge, while 93% identified people and process issues, including organizational alignment and cultural resistance.
So what can organizations do to forge a data-driven culture?
Cultural change requires support both from the bottom-up and top-down. As Gartner analysts have put it, you need to “engage with stakeholders to secure buy-in and ongoing support in treating data as an asset – not data as a by-product.” This means isolating the key people and showing leadership in how you identify and communicate the business value of data, how you address the impacts of this cultural change, and how you manage the ethical implications. Everyone needs to be convinced that becoming data-driven will be worth the pain, and that you can manage and mitigate the risks.
Many businesses underestimate the amount of data they have at their disposal – not just the data generated through sales and transactions, but reference data on products and services and aggregate data that can be mined for trends. Data may need to be broken out of siloes, and it all needs to be organized and documented.
Open data can also be a rich source of insight. Don’t just consider internal channels, but also external channels like social media, weather forecasts, local demographics or the markets. Collaborating with others in your sector can help all involved face common risks. Be creative. Broader data pools can often open up new insights.
However, all this data needs to be cleaned before it can be analyzed. Without a process of reconciliation and quality assurance, you can find yourself feeding poor data into your process, and it’s a case of “garbage in, garbage out.”
Organizing and aggregating all these data sources in a “single source of truth” means nobody has to waste time hunting for data, and that you don’t find separate, contradictory insights emerging from different sources.
By doing this, not only do you improve employee productivity and streamline your data estate, but you also reduce the chance of having data “siloes” that are unseen and unmanaged.
The further you move into advanced analytics and machine learning, the more crucial it becomes that the models and the insights they produce align to your business objectives. You’re not just looking for information, but information that can improve internal processes or departmental goals, preferably tied into actionable KPIs. Those designing the models need to understand the business decisions that different managers and departments are making every day, and ensure that the models work into their decision-making processes and won’t be ignored for old-fashioned choices from the gut.
The data-driven business only works when everyone has access to the data and insights they need to work effectively. This might mean embedding data and analytics into simple dashboards for frontline workers, or ensuring that insights feed into all decision-making processes.
Everyone from the customer service agent to the sales team to the CEO needs the data relevant to their role in an easily accessible form, and everyone needs to understand how taking action on insights will result in tangible improvements. Here, communicating how data-driven initiatives are directly benefiting teams and projects often helps.
Dashboards aren’t always comprehensible at a glance, and not everyone has training in data science or statistics. Basic training to help workers improve their data literacy and understand what charts or numbers mean can be a big step forward in making data-driven initiatives a success. Organizations need to build a culture where workers understand what data is available and what the different metrics mean, so that everyone understands any resulting insights in the same way. If necessary, build a data glossary with clear, unambiguous definitions.
Take these steps and you’re on your way to a truly data-driven business, where data can optimize operations and inform better decisions. It’s a long process – and quite possibly never-ending – but one that could transform your whole organization for the better.