For those of us who have spent our careers helping organizations get more value out of their customer data assets, the recent surge of press, interest, and early investment related to Big Data raises many questions about whether companies are finally ready to capitalize on its promise.
Make no mistake, the explosion in data as a by-product of the digital, mobile, and social web is providing us with seemingly endless potential to analyze and understand consumers like never before. Couple that with advances in Big Data technology (Hadoop, MapR, etc.) and we begin to see the potential for getting insights that once took hours or days to process down to minutes or seconds.
But while the term "Big Data" may be new to many of us, I'm having somewhat of a déjà vu moment.
The truth is, large amounts of data about what customers buy, what channels they prefer, and what value they represent to the companies they transact with have lived in the siloed data warehouses of most companies for many years. CRM systems have captured purchase and interaction data. Contact centers have captured service and customer satisfaction data. And, vast networks of web properties have captured content consumption information.
So, while the raw material that is data has become more plentiful and emerging technologies more powerful, many organizations have not progressed very far in the way they mine, disseminate, and apply the kind of consumer intelligence we may now be able to cultivate.
Sure, the volume and velocity of data has certainly exploded, but not enough has changed in the way organizations have leveraged and applied data.
Recipe for serving up Big Data rewards
So, what missing ingredients should business leaders looking to reap big benefits from Big Data investments focus on? My short list would include five strategic imperatives.
1. Recognize and elevate the importance of the data scientist
There's a virtual renaissance going on in the area of those responsible for turning all that data into the kind of useful and actionable insights that can move critical business KPIs in the right direction. No longer is it practical to expect only Ph.D.s in Applied Statistics to ask the right business questions of the data and see the business opportunity in the intelligence.
For sure, there's a high demand for skilled quantitative professionals to be part of the team, but more and more companies are looking to complement that talent with creative business professionals who are facile at seeing business opportunity in trends and statistics that can produce tangible bottom-line results.
C-suite executives don't have time to consume vast amounts of detailed data. Data science leaders need to transform insights into business opportunities and implications to get the support they're looking for from senior management. It will be increasingly important to serve up Big Data-driven insights in "easy to consume" ways so senior management can cut through the detail and make decisions faster. Data science professionals with strong business acumen can make all the difference in the investment a company makes in collecting, analyzing and mining consumer information, and they are in high demand in today's information-driven economy.
It's time to elevate Data Science out of the backroom and into the boardroom.
2. Organize for one version of the truth
A CMO friend of mine likes to tell the story about bringing his marketing team together to report the performance of last quarter's marketing activity. He goes around the room asking each team to highlight how many sales their programs generated. As he tallies up the results he realizes that if everyone's programs performed as stated, the company's quarterly sales would have been 70 percent greater than they actually were.
Too many marketing departments today are still organized in channel-centric silos, each with their own responsibility to develop marketing plans, implement communications through various channels, and measure the results of their efforts. As a result, most CMOs have struggled to knit together a comprehensive picture of the customer, what's going on in the business, or how best to allocate marketing resources to generate maximum business impact.
In a Big Data world, where insights are potentially sourced and acted upon in mere minutes or even seconds, how will marketing groups organize to maximize the potential of all this enhanced insight?
The silos in today's marketing suites need to be redefined, along with many of the analytic and measurement practices that have served them in the past. Online and offline data need to be integrated into platforms across channels that facilitate a more comprehensive understanding of consumer behaviors to enable predictive analytics to inform real-time interaction strategies.
3. Don't underestimate the data integration challenge
To date, we've lived in a world where most of the data we work with is structured. This makes it easy to categorize and classify, store in conventional data stores, access with various commercially available tools, and analyze offline with plenty of time to identify useful insights that might change the way we market to or serve customers next month or next quarter.
In the Big Data world, we're going to have to extract insights from an explosion of structured and unstructured data—statistical data, social media streams and other web content, smartphone data, videos, PDF files, Excel files—that is not easily digested and deciphered.
Most firms are not ready to take on this effort, and fewer still have the skills and experience to get started. We're all familiar with the failure rate statistics of large technology projects associated with the CRM decade. Just because we can integrate the data doesn't mean it's all worth integrating. CTOs should learn from the past and develop practical, small scale experiments in Big Data applications.
4. Integrate intelligence into customer-facing business practices
Perhaps the most significant opportunity for Big Data will be the potential to identify and integrate insights into customer-facing applications in near real-time.
But as far as CRM analytics has progressed over the past decade, organizations have struggled to push potentially powerful customer intelligence out to front-line applications such as salesforce management systems or customer contact centers.
Customer-value-driven "sense and respond" strategies have been possible for a few years now, but many organizations have not "enabled" front-line staff to take full advantage of a wealth of predictive capability that lives in the analytic suite of most marketing departments.
The potential that more data represents will force companies to integrate and enable their entire customer-facing applications.
5. Use Big Data to accelerate customer-centric transition
In an increasingly competitive environment, delivering an outstanding customer experience is becoming a critical differentiator for organizations. Customer centricity is no longer a nice-to-have strategy. Today, it's a business necessity.
A positive customer experience and engaging interactions can extend customer relationships and drive long-term value for the organization. In a world where customers increasingly expect the companies they do business with to know them and anticipate their needs and preferences, Big Data applications have the potential to "transform" customer experiences in ways that have not been possible.
As a result, it will be even more critical for businesses to re-engineer their customer intelligence efforts. They must ensure that they understand the impact of the experience they are delivering to customers across the entire organization and throughout every stage of the customer lifecycle.
For C-level executives looking at the promise and potential of Big Data to make their businesses more customer-centric, it will be important to think beyond technology and analytics to what organization, process, and people related changes are necessary. It may be that some of these ingredients will be the recipe for success.