Consumer product companies are using it to predict customer behaviour, preferences, and product perception. Advertising and marketing agencies are using it to understand responsiveness to campaigns, promotions, and other advertising mediums. Manufacturers are using to it to predict the optimal time for replacement or maintenance of their products and to trace after-market support issues. Insurance companies are using it to see distinguish between the home insurance applications that can be immediately processed, and the ones that need a validating visit from an agent.
The ‘it’ here is Big Data. What is Big Data, though? Simply put, Big Data is the mining and processing of petabytes of information to gain insights into consumer behavior, promotion success, distribution efficiency, and a multitude of other aspects of business performance. An important question that may arise is whether such advanced analytics capability is worth the investment. In other words, does your organisation really need Big Data? Indeed, it does. Here’s why:
Understanding Target Audience
Big Data analysis allows Wal-Mart to better predict what products will sell and car insurance companies to understand how safely their customers actually drive. Even politician are making heavy use of Big Data and analytics to optimize their election campaigns – be it Obama in the US in 2012 or Narendra Modi in India in 2014.
Understanding the target audience and their preferences and buying patterns is one of the major areas where Big Data is being leveraged in a big way today. Companies are expanding their field of analysis by combining their traditional data sets with social media data, browser logs, text analytics, and sensor data to get a fuller picture of their customers. The most obvious and important objective is, of course, to create predictive models for successful business performance. Therefore, if you want to better the chances of your products and services succeeding with your clientele, your organisation needs a Big Data plan.
The Harvard Business Review reports that the New York City Police Department makes use of Big Data Analysis “to geolocate and analyze ‘historical arrest patterns’ while cross-tabbing them with sporting events, paydays, rainfall, traffic flows, and federal holidays to identify what NYPD calls likely crime ‘hot spots.’” Apparently, “such insight can help deploy officers to locations where crimes are likely to occur before they are actually committed.”
Indeed, the days of going with your gut alone are long gone – even for the police force, arguably one of the most instinct-driven of organizations. Today, technology makes it possible for the NYPD and other police departments to accurately anticipate and identify crime for swifter action. The same logic can be applied in a number of other fields – and Big Data is today being leveraged in many industries with impressive results. Financial institutions are using data mined from customer interactions to categorise their users into finely tuned segments that enable them to create increasingly relevant offers, web-based businesses are developing information products that combine data gathered from customers to offer more appealing recommendations and coupon programs, sports teams are using data for tracking team strategies and ticket sales, and so on.
This does not suggest that the role of human intuition, emotion, and reason in business have all been rendered redundant. But it does imply that Big Data is creating a context in which organisations can operate more efficiently. A well crafted and meticulously executed Big Data and analytics strategy makes your organization smarter.
Optimizing business processes:
Based on predictions generated from social media data, web search trends, and weather forecasts, retailers are now able to optimise their stock. HR businesses are increasingly optimizing their talent acquisition methods, as well as measurement of company culture and staff engagement using big data tools. Big Data is also being effectively tapped for supply chain optimization. Here, geographic positioning and radio frequency identification sensors are used to track goods or delivery vehicles and optimise routes by integrating live traffic data, driving conditions, etc.
Thus, Big Data is being increasingly used to optimise business processes – for organisations big and small. It can similarly help your organisation function at an optimal level.
Enabling cross-channel conversations with customers:
For most business organizations today, it is all but impossible to maintain the kind of quality conversation with customers that laid the foundation for consumer trust in the yesteryears. The volume of queries, comments, and feedback coming in from various sources is simply too massive. This is where technical infrastructure to support dynamic, cross-channel conversations with customers becomes absolutely necessary for organisational impact. Investing in a sound Big Data plan lets you stay close to your customers by providing you with customer insight.
McKinsey&Company’s iConsumer research suggests that “behavioral and transactional data from web usage, in-person observational research, and interviews can be analyzed to help companies make the right investments, whether based upon global, market, and customer segment level trends, or discreet consumer usage, buying factors, and attitudes.”
Preparing your organization for reversals:
The iConsumer report accounts for why organisations need to make structural changes related to Big Data. Reversals, as has been interestingly noted, “come gradually until they come suddenly.” For instance, the newspaper industry moved from booming to near obsolete within a decade of the advent of online publishing. Another reversal was seen in the recording industry, which saw CD sales go from booming to obsolete with the advent of digital music – again within a decade. Both these reversals were initially gradual and non-alarming, but they suddenly became massive in their impact.
Industry analysts and media experts anticipate the digitization of all customer-facing organizational systems (service, sales,marketing) as the next major reversal. Thus, from the smallest local chains to the largest multinational companies – organisations that resist a systematic approach to data analysis, online marketing, digital distribution, etc. run the risk of becoming obsolete when the reversal comes suddenly. Adopting Big Data while we are still in the gradual phase of the reversal will see your organisation through the reversal.
Big Data is indeed the next big thing in business. Is your organisation equipped to keep up?