Big Data and Listening Capabilities: Can They Deliver Strategic Intelligence?

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Leading companies are developing next-generation strategic intelligence capabilities that use enterprise, market and social data in concert to uncover new insights into opportunities and emerging risks. Several factors are contributing to this trend, among them the continuing, exponential increase in information both within and outside the enterprise. The widespread availability of technologies such as natural language processing and the emergence of a new generation of analytics talent are making it possible to tackle high-value problems through data tailoring, contextualization, visualization and workflow integration. Even with these exciting developments, though, some business leaders may be thinking, “I’ve invested in business analytics resources time and again over the years and lately in social listening tools. Is there real value in investing more for next-generation capabilities?"

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What’s really different here?
We’ve invested in business analytics systems that can crunch the data. Our human analysts know how to mine information. Why do I need these new capabilities and tools?
There’s now a premium on flexibility.
Many analytics tools are point solutions built to address small, defined problems. They are not capable of triangulating across disparate data sets to deliver comprehensive strategic insights. Today, though, businesses need approaches that both capture information from disparate sources and are flexible enough to explore various situations that inform a company’s strategic viewpoint. In particular, these conditions are making the role of the “data scientist” more important. Data scientists immerse themselves in volumes of data to identify patterns, extract insights, and then – most important – apply their findings in the context of strategic business questions that need to be answered rapidly.
What are we to do with all this new data?
We keep hearing we need to merge social data with our internal data and other external data to uncover new insights. But we’re already drowning in data. Where does it end?
Get ready, because there’s more on the way.
Data growth is inevitable. And even if you’re not mining the new sources, it’s likely your competitors are. But the focus shouldn't be on the data. Instead, each business is different, so it’s vital to focus on specific, critical questions. The new analytical tools and skills can equip you to track a cross-section of hundreds of leading indicators, look for anomalies and patterns as they unfold, and contextualize the findings to your business strategy. Meanwhile, technology is reducing the need for humans to handle routine information gathering and analysis tasks, both providing consistent process quality and freeing personnel for more value-added activities.
We already have analytics teams focused on answering specific high-value questions – are we just talking about addressing them differently?
Is it really worth making the investment to cut through all the noise in hopes of uncovering new insights?
The key is to build a capability to continuously monitor the changing context around the high-value bets and help make adjustments to the strategy as the situation unfolds. Number crunching solutions or social media listening is not enough to monitor the context.
The next-generation engines are not plug-and-play, and they can’t be applied to every question. Instead, their value lies in customizing and training them to not only analyze specific sets of critical factors, but also related information around those factors that may define new signals. Narrowing the focus to high-value issues improves your ability to uncover nuggets of insight than can make the entire effort worthwhile. And, the new tools are flexible and reusable, opening the door to further serendipitous discovery.
There are many off-the-shelf tools available to mine social data.
Doesn’t it make sense to give these tools a spin to gain social media insight?
It’s about a lot more than social data.
These new tools aren’t just for social data mining. Social is a piece of the puzzle and can be used effectively on a small set of defined problems in an organization. But gaining strategic insight can require marrying social insight with what’s revealed in your organizational data and other publicly available data.
We’ve tried this before.
We have introduced new tools in the past, and they end up sitting on a shelf.
It comes down to culture. You don’t need yet another report that won’t be read.
Don’t mess with what is working well. Instead, solve high-value questions that are pain points and provide the answers to people as a part of their natural day to day workflow. Even the best strategy or analysis will be set aside if it doesn’t become part of the day-to-day life and work of the people it’s supposed to help. Therefore, it’s important to integrate the information into the organizational workflow, delivering it to the right people, at the right cadence, in the right context. And delivering it rapidly is critical.

My take

us_vikram_mahidhar_135x155_101513.jpg us_vijaysharma_135x155_101513.jpg
Vikram Mahidhar, director, Innovation,
Deloitte LLP
Vijay Sharma, senior manager, Innovation, Deloitte LLP


The concept of information asymmetry is well known in the business world. Simply put, having information that a competitor doesn’t have can be a factor for winning more business, reducing organizational risk, and making more money.

But that’s not the end of the story. As we explored in an article in Deloitte's Business Trends 2013 report, companies can now apply advanced analytical tools to such information to create a new level of advantage – insight asymmetry. Not only can they gain a knowledge edge, but they can also uncover the true value in the constant streams of information coursing through the enterprise. New analytical capabilities help equip businesses to identify the right questions and then look for signals on an ongoing basis that are conceptualized and customized based on business needs.

Three factors are important in capitalizing on insight asymmetry. First, have the capability to be flexible in using information. Next, develop the capacity to bring scale to strategic analysis quickly and efficiently. And finally, provide information to people in a form that is usable and becomes part of their day-to-day business activities.

Of course, companies are at different stages of maturity in their deployment of analytic capabilities, and some may believe they aren’t equipped to handle new technologies. The good news for these businesses is that they can deploy this next generation of insights engines without having to take a stepwise approach. Instead, they can leapfrog to these new capabilities and make up ground on their competitors.

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