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THE vALuE Of BIg DATA: HOw ANALyTIcS DIffERENTIATE wINNERS

A DATA DRIvEN fuTuRE

Big data is fast becoming the term keeping senior executives up at night. The promise of the op-portunities it unlocks is sufficiently attractive, yet the sophistication required to extract the claimed benefits is thinly spread and as such, the challenge is how to unlock the benefits of Big Data before the competition. In our discussions with senior executives the key message we have picked up is that the level of understanding is as high as it needs to be, but the capability to execute is far below most executives’ expectations.

The Seymour Sloan view is that a small percentage of organisations have real strength in analyt-ics, an elite group that deploys the correct people, tools, data and organisational focus. These are the companies that are already using analytics insights to alter and improve the way they operate or to improve their products and services. The difference is already visible. These companies are:

• Twice as likely to be in the top quartile of financial performance within their industries• Three times more likely to execute decisions as intended• Five times more likely to make decisions faster

Achieving excellence with Big Data is a three-part process that requires; defining the ambition, de-veloping the analytics capability and shaping the company to maximise the opportunity. Here, we will examine the second step—building up the analytics capability—to understand how leaders use Big Data as a competitive advantage.

Data, tools, people and intent

Strong organisations build up their analytic capabilities through investing in four things: data-savvy people, quality data, sophisticated tools, and processes and incentives that support analytical de-cision making. We estimate, based on our high-level survey, a third of companies do not excel at any of these elements, while many of the rest excel in only one or two areas. Building a high per-forming analytics capability requires that you do all four well. Success in each capability depends on strength in the others. It is a self-sustaining structure.

Data is the cornerstone of any analytical capability. Often, research suggests that between 50-70% of organisations are unhappy with the quality of their data, extending well into the Forbes 500. This is somewhat alarming, but also, a legacy of the relatively low status data was given in boom years. That data strategy must align with the overall business view of how the data will generate real insight and subsequently, value. We estimate that just over half of the companies lack the right systems to capture the data they needed or were not collecting useful data, with two-thirds lacking the right technology to store and access data. A good data policy identifies relevant data sources and

builds a data view on the business to—and this is the critical part—differentiate your company’s analytics capabilities and perspective from competitors. A critical aspect of good data policy is to focus on identifying relevant sources of data. For example, capturing all queries made on the company website or from customer support calls, emails or chat lines, regardless of their outcome, may have significant value in identifying emerging trends; however, keeping detailed logs of re-quests that were easily handled might be less valuable. An important additional element is the ability to identify external sources of data that will further assist in providing a deeper view on the customer. An example is how such consumer finance houses use browsing behaviour as an indi-cator of credit risk.

In terms of analytical tools, we suggest that organisations ‘aim for the sky.’ In such a nascent peri-od of analytics development, the key is to ensure you both acquire the most sophisticated analyt-ics as well as being able to improve capabilities as more tools become available.

Advanced analytics and Big Data tools are developing so rapidly that they’re likely to help you get to potential insights and statistical novelties in ways that were not possible even as recently as a year ago. Tools and platforms like Hadoop, HPCC and NoSQL are rapidly emerging and evolving to address analytics opportunities, as is the rich ecosystem of mature analytics, visualization and data management. Today, these tools are available from a wide range of vendors and an even larger community of open-source developers.

We find it surprising that less than a third of the executives we spoke with were aware of the possi-bilities these tools could offer. This is time for a massive education exercise for executives around the future of Big Data. They should be sufficiently knowledgeable in order to be the champion of big data and to understand the impact of investing or not investing.

The biggest challenge facing organisations is the lack of people with the required skills to turn the analytics into actionable information. The ability to turn data into opportunities will become more complex as capabilities improve. The increase in technology must move in lock-step with the increase in skill of your staff. Most organisations agree they are not up to the challenges of iden-tifying and prioritizing what types of insights would be most relevant to the business. Successful analytics teams build those capabilities by blending data, technical and business talent. Think of a band as the model: a team with different but overlapping skills that knows how to effectively and efficiently communicate and collaborate. Success with Big data requires:

• Data scientists, who provide expertise in statistics, correlations and quality• Business analysts, who identify and prioritize the problems worth solving and the business relevance of data anomalies and patterns identified by the data scientists• Technical specialists, who help manage the hardware and software solutions needed to collect, clean and process the data

Success with Big Data requires an acceptance by the organisation that, where possible, data must drive business decisions. The increased analytical capability lies at the core of business strategy with board-level supervision and support. The CEO and top leadership team need to shape the vi-sion of how analytics will drive business improvement, whether by improving existing products and services, optimizing internal processes, building new products or service offerings, or transforming business models. Leading organisations excel at this, often building their organizations around data and a commitment to make data-driven decisions.

Nest serves as an example of an organisation that can shape decisions with Big Data analytics. Other companies provide an ability to remotely control their home thermostats using a Web in-terface or smart phone. Nest goes further, crowdsourcing intelligence about when and how cus-tomers adjust their thermostats to keep their homes comfortable. Nest gathers the information in the cloud, and by correlating it with weather, location, type of home and when people adjust their thermostats, the company can anticipate and control the settings to create a more comfortable environment in their customers’ homes.

Committing to excellence in each area will require significant investment, commitment, and oc-casionally a change in leadership. There is no value in focusing on one area without the other elements. Tools won’t help if the data is of poor quality, and talent will walk if the company isn’t committed to benefiting from the insights. Like an engine that must be firing on all pistons, all four areas must be tuned for peak performance.

The opportunity, the urgency

There is a significant opportunity now to develop and deploy a sophisticated analytical capability. This will place the early-adopters ahead of their rivals, but the window is closing on a daily basis and as sophistication of tools improves, the opportunity for rivals to close the gap improves. The time to act is now.

Industries such as, financial services, technology and healthcare are leading the market in rede-fining the battlegrounds and business models, based on analytic capabilities and insight-driven decisions. But opportunities exist in almost every industry.

An example is the mail-order pharmacy that analysed hundreds of thousands of customer service logs and detected a spike in calls between Days 75 and 105 of some patients’ medication regi-mens. Looking closer, analysts found that the calls correlated with refill dates, and they discovered that some customers were calling for refills because their medications were taken with variable dosages.

To reduce the number of lengthy customer service calls and expensive “emergency” refills and rush orders, the pharmacy began asking patients how many pills they had remaining at Day 30 and Day 60, so that they could better predict when the medication would run out.

And within any industry, some functions can benefit from insights gleaned through Big Data ana-lytics. Call centres, for instance, can be made more effective and efficient by capitalizing on what the company can know about the caller ahead of time. The travel and hotel industry have a great opportunity in this area. By using any unique identifier, they can identify the customer, their value to the company and how much they spend with the company, which allows then to be routed to the right channel at the right level of priority. In addition, the data held on each customer can allow the service agent to predict what the potential issue could be. Although care must be taken so not to tell the customer their problem before the customer has explained it. Other markets can benefit significantly from this, from retail to professional services, the ability to know as much about your customer as possible has unlimited potential.

The next level of sophistication will be when you can see your customer using data beyond that held on proprietary systems. Being able to see the social media analytics and other online details will provide a granular picture of customer behaviour and customer need. The reality is that, with all the new technologies coming online and with the possibilities in relation to combinations, the possibilities are massive, which makes the future an exciting time…if today’s strategy is correct.

The competitive edge to be gained from advanced analytics is no longer limited to a few techy companies or data-intensive industries. It’s here today, in all sectors, and as our survey results demonstrate, companies that commit to making the most of their data and investing in their analyt-ics capabilities are already outperforming their peers financially. A wait-and-see attitude is a luxury that no competitive company can afford.

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