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Big data has been discussed endlessly over the last decade, and not without reason. The digital universe is projected to multiply tenfold in less than ten years — from 4.4 zettabytes in 2013 to 44 zettabytes in 2020. And corporate investments in this data speak to its promise. Forbes estimates $8 million in big data investment per enterprise — i.e., $8+ billion spent by the Fortune 1000 — last year alone. Much of that investment is aimed at uncovering new opportunities to grow and to serve customers better.
Advances in capabilities like data collection and computing power enable these investments. But their value is driven by rapidly evolving, increasingly customer-empowered marketplaces. In this environment, large companies need to get closer to their customers, to drive the right behaviors across a distributed workforce, and to adapt at the pace of the market in order to position themselves for success in the next financial period.
The problem: The majority of big data approaches are too slow and specialized to match the pace of a customer-centric world and the related demands on a business’s operations.
Eighty-five percent of business leaders believe in the promise of big data, according to an IDG and Kapow Software study. Yet only 23 percent of business leaders describe their big data projects as successful. Similarly, research by Capgemini consulting found that only 13 percent of companies have effectively incorporated big data extensively into their business operations.
One reason is the difficulty of building effective big data teams. IDG’s study concluded that “it’s really difficult to pinpoint and surgically extract critical insights without hiring expensive consultants or data scientists in short demand.” And even with the right people, the study found that big data projects don’t always deliver actionable, valuable insights. The noted statistician Nate Silver has echoed this conclusion, observing that the “noisiness and messiness” of big data means getting a perfect result every time is usually a sign that your analysis is skewed.
Even when big data projects are successful, IDG’s study found that 60 percent of them take too much time and money. Small, specialized teams are most effective at uncovering and extracting deeply buried insights. But in an increasingly customer-empowered world with shorter market cycles, faster application of insights is becoming increasingly important.
What this means is that focusing solely on labor-intensive ‘deep-dives’ leaves a lot of the value of customer data on the table. Companies need a complementary approach to capture that lost value. That approach should aim for lighter analysis, faster ideation and application of ideas, and a greater pace of learning and improvement on a distributed basis.
The solution: Democratize access to, and interaction with, real-time customer data by wiring it directly to the breadth of your workforce.
This approach starts with a basic premise: that workers want to do good work, to contribute to the company’s success, and to see the difference their efforts make. Customer data enables them to do just that, as well as to be recognized for their efforts and to learn from mistakes. As noted by Fred Reichheld and Rob Markey of Bain & Company, “the best employees…will put in extra discretionary effort because the system is giving them a chance to exercise their judgment, to master a task and to be part of a productive team.”
Additionally, the economics at play are powerful: for the majority of companies, employees represent immense untapped value. In the typical large company, MSW Research estimates that only 29 percent of the workforce is actively engaged. And Gallup estimates that a fully engaged workforce, coupled with engaged customers, can improve business outcomes by as much as 240 percent.
In a data-rich world, where customers are increasingly in control, an employee base represents thousands of motivated supercomputers that can solve challenges in parallel, creatively, and with market context.
To unlock this potential, companies should wire real-time customer data (e.g. customer feedback and related operational measures) into existing employee processes, and give employees the opportunity to take action on that data. Since companies are already paying for employees, incremental investments to boost their effectiveness are small by comparison. And the benefits are significant: productive and satisfied workers, better experiences for customers, and greater value for shareholders.
The levers for accomplishing this are clear. Quantitative research and multiple real-world examples show their additive value.
In a recent study of more than 200 customer experience programs, Medallia found that organizations where a high proportion of employees have access to relevant customer data see Net Promoter Scores on average 12 points higher than companies without broad access.
The Zurich Insurance group offers an example of the benefits of broad access. The company wires real-time customer experience feedback to its entire organization, which spans 5 continents, 40 countries, and 26 languages. This allows employees to identify local trends — and act on them — sooner.
One trend caught early on was confusion over the automatic renewals process in the Turkish market. Local insurance regulations were complicating the process in an unexpected way. Luckily, Zurich’s regional team caught the problem promptly and implemented a fix, causing NPS to rise by 20 points. This all resulted from customer data flowing throughout the organization in real time.
Medallia research shows that the more frequently customer data is accessed at a company’s frontline, the higher the company’s NPS. The research identified similar benefits from using mobile apps to make data more accessible to employees on the go. Companies that did so saw NPS an average of 10 points higher than companies that did not.
Best Western hotels offers an example of this lever’s value. Medallia research found that when properties accessed customer feedback two or more times a day, they increased their occupancy rate twice as fast over the next year as properties that accessed feedback once a day or less. The five percent occupancy growth achieved by these highly engaged properties was also higher than that year’s industry average.
One of the least utilized but most impactful levers for data democratization is to reset the company’s stance on empowerment and accountability. Empowerment refers to giving employees greater freedom to proactively improve how the business operates. This can include both customer experience improvements and removing costs of experience delivery.
Increasing employee empowerment worries many of the business leaders I speak with. They believe variability and related costs in the business will rise, and that employees will, with all the right intentions, destroy shareholder value in the spirit of better service (e.g., giving too many free services to unhappy customers.)
But this mindset overlooks several key factors. First, executives routinely underestimate, or do not want to admit, the degree to which variability already impacts their business. For example, a 2014 article by McKinsey & Co. observed that variability in customer experience in the top North American banks’ branches overshadowed those branches’ efforts to establish a consistent level of experience or to differentiate from competitors. Moreover, as companies interact with customers over an increasing number of channels, consistency across those channels becomes more important than consistency in any particular one. Another McKinsey study compared feedback about overall customer journeys to feedback on multiple journey steps, and found that the former measure was a better predictor of desired business outcomes.
Additionally, increasing employee accountability to match a higher level of empowerment can offset empowerment’s risks. Some of our best-performing clients put in place operational goals and customer experience metrics that cascade to the individual employee (e.g., specific roles at an auto dealership). Others combined this approach with goals that cut across customer journeys (e.g. a customer onboarding experience), forcing different teams to work together.
Finally, customer experience variability has become less risky because it can be tracked and measured in real time. This limits the degree to which performance can get off-track without being flagged, and turns moments of variability into learning opportunities for the broader organization. Four Seasons Hotels gains both of these benefits by giving general managers digital dashboards that track guest experience metrics at every property in real time. Whenever a key metric spikes or dips at a property, others reach out right away to learn what happened — so they can change their own behavior accordingly.
Democratizing customer data can be extremely powerful. It makes the most out of people’s skills and desire to do well, delivers more value to customers, and puts the organization on a more agile and innovative path for continued improvement. For these reasons, it will be a core driver of financial performance in the near future.
How much value are you getting from your customer data? Here are three questions every business leader should ask: