In a very short period of time, analytics has moved from shiny new thing to core business function. However, despite widespread recognition of the power that analytics has to inform decision making, we see insufficient investment in the organizational change needed for companies to become truly data driven.
Many of today’s executive decision makers cut their teeth in a web 1.0 world of disjointed CRM systems, focus groups, and judgment based on sheer gut instinct. Today’s world is different. The amount of data now available means that almost any decision in any organization can and should be informed by data. In fact, a recent survey we conducted found that 81 percent of companies agree that data should be at the heart of all decision making.
However, in many companies we find that organizational designs are still immature and executives don’t always appreciate how analytics will fundamentally change business processes and human behavior. Our survey found that only 31 percent of companies have significantly restructured their operations to put data at the heart of their organization.
For every decision that needs to be made, analytics can help provide the answer, but analytics also results in a human being doing something different as a result of the analytics. This human element of analytics has two key facets – having the organizational capability to change, and aligning incentives for those individuals who actually need to make the change. Let’s look at a few examples.
- Recently, a healthcare company conducted some exploratory data mining on its claims and provider data. It found that it could potentially reduce claim costs for different types of “covered” healthcare episodes. If the initial findings are realized, they would result in hundreds of millions of dollars in annual savings. Such potential to make patients healthier and save money seems like it should warrant further investigation. But the organization is finding it hard to mobilize the resources to act on the insights. Translating the potential benefits into real-life examples that justify additional investments in the use of analytics is becoming an important challenge for companies to address.
- An example of the resources being mobilized is a top 50 property and casualty insurance carrier. Faced with ever-increasing customer expectations, the company set out to enhance its customer experience, boost its analytics capabilities, and improve process efficiency in claims. Instead of stretching existing management teams, the company invested in dedicated organizational change-management teams to implement these changes. The resulting quality of employee training, internal communication, and organizational restructuring created an effective analytics program as well as capable, engaged employees, 77 percent of whom said the firm was “changing at a pace that ensures success in the industry.”
- A pharmaceutical company used to audit all expenses for all employees, an incredibly time-consuming exercise that sapped productivity and led to frustration, especially when a lost receipt for a $3 coffee would delay an expense reimbursement worth thousands of dollars. The company introduced an analytics-based fraud-detection program that identified those most likely to be committing expense fraud. For everyone else, the incentive to use the new system was huge – significant time savings and quicker reimbursements.
- Another pharmaceutical company wanted to use analytics to help improve the accuracy of its sales forecast to specific premier customers. This project met internal resistance as many within the salesforce spent 30-40 percent of their time collecting this information manually. It took the intervention of the sales director to reassure the sales team that the analytics program did not threaten their jobs but would help improve the level of service to the end customer. In cases such as this, the incentive takes the form of reducing fear.
- A third pharmaceutical company used predictive analytics to determine which customers were likely to be late on payments. They tested several intervention mechanisms and decided that sending reminder notifications proactively in advance of the due date would have the best outcome. However, the same team that was responsible for generating revenue and increasing customer satisfaction was now also responsible for sending these notifications. This led to conflicting incentives around reducing receivables versus building long-term customer relationships. The result: A far lower number of notifications were sent out compared to what was necessary.
Analytics can be a driver for sweeping and positive change, bringing about cost savings, increasing profits, and guiding the development of new products and services. But in an era when the mantra “our people are our greatest asset” is omnipresent, we continue to see a curious disconnect between analytics initiatives and the people whose behavior they most affect. Companies can take the following steps to help fix the analytics disconnect:
- Focus. Analytics programs require continuous, high-level attention. The CEO must be engaged in the technical, organizational, and human aspects. Unless analytics becomes part of the DNA of an organization, especially its people, it will never realize its full potential.
- Training. The technological investment of an analytics program must have a corresponding level of investment in the human element. The investment should be in everything from training to dedicated organizational change-management teams.
- Organizational design. Analytics success does not happen overnight. Programs grow and evolve as humans adapt and organizational structures adjust. Prioritizing the human element helps prevents the expensive failures, but even the best-planned deployments take time.
Fundamentally, analytics means a human being will need to do something differently, and that change is hard. But if companies are going to seize the once-in-a-decade opportunity that analytics presents to leapfrog competitors, they must treat the human element of analytics as importantly as the technical implementation. After all, analytics insights that are not acted upon or operationalized are usually intellectually interesting but, almost always, practically useless.
As EY’s Global Chief Analytics Officer, Chris Mazzei leads the Global Analytics Center of Excellence which serves as a catalyst for transformation both internally, within EY to embed analytics into its service offerings across all business lines, as well as externally for EY’s clients by delivering analytics offerings that help organizations grow, optimize and protect value. Chris has held a number of senior positions across EY, as head of strategy in the Americas, where he advised EY’s CEO and board on a host of corporate and business unit level strategy development and implementation issues; in EY’s Advisory practice, where he provided strategic and financial decision support to help client executives link key decisions to their financial implications; and in EY’s Center for Strategic Transactions, a unique group focused on helping client CEOs and upper management teams explore the risks and opportunities of transactions and other strategic growth agendas.
Gaurav Gupta, a Partner in EY’s Advanced Analytics practice, focuses on design and delivery of high-value analytics solutions to enable data-driven decision making and rapid business value capture. Gaurav has led complex engagement at multiple Fortune 100 clients across various functional domains such as marketing, finance, supply chain, HR, and strategy/semantic. Key industries include Life Sciences, Media and Entertainment, and Diversified Manufacturing.
Gaurav and his team collaboratively partner with key client executives and their teams across the organization, as well as external research organizations and the business analyst community. Gaurav has created and led an advanced analytics practice in a fast-moving environment and is equally comfortable in the trenches, as well as in the boardroom with senior executives. He is an enthusiastic advocate of new technologies, with the ability to understand the mature solutions available in the marketplace in order to build and sustain truly world-class analytics program/organization.
The views expressed herein are those of the authors and do not necessarily reflect the views of Ernst & Young LLP.
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