Is size still even a question? The new suite of ‘Big’ Data solutions has created a tremendous opportunity for organizations to leap into a digital, personalized, business era. All without the limitations to volume, structure and availability they reluctantly learned to live with in the past.

Today’s question is how to put the fancy technology to work for the organization to become a top performer, whether it pertains to bringing more clients to the yard, optimizing operations or even disrupting business models. By putting unobstructed insights at the heart of its business, an organization will indeed be able to claim that its business is ‘bigger than theirs’.

As big data solutions have matured, preparing for the imminent wave of the Internet of Things (IOT), organizations across industries are looking to collect and transform data into business value. Besides the necessary discussions around the right best practice to implement for their next-generation data management platform (like transforming the data landscape towards a Business Data Lake) organizations are now increasingly looking at defining and realizing the business impact of their Big Data initiatives.

From customer experience and operational excellence (“doing things better”) to innovative business services (“doing better things”), this business impact can either help to survive or truly become a disruptor - by addressing the market with new, innovative services and products.

Consumer product companies aim to better understand the buyers of their brands to better anticipate market trends and design future products before their competitors do.

Telecommunications companies are prioritizing their network optimization efforts to serve their high-value customers more effectively, thus gaining a competitive edge in this dynamic market.

The French branch of Randstad (a multinational HR Consulting firm) wanted to re-boost growth and revive profits by creating innovative, high-margin services that address new customers. It created a digital, dynamic observatory of the French employment market, leveraging Big Data technologies. It allows Randstad to address their customers with new HR services, matching very specific client segments (identify job opportunities & recruiting companies, professional redeployment services, mobility services, to name a few).

To achieve this level of transformation, and move progressively from “doing things better” to “doing better things”, it is critical to think about how to integrate the new insights into business operations: right into the very processes that constitute the way the business is run on a daily basis. Insights and operations should not be considered two separate areas anymore: it’s a matter of fusing them.

A key success factor is the ability to industrialize the Big Data approach. In a highly dynamic and innovative technology ecosystem, it is tempting to get carried away with discussing the latest, shiny open source Big Data solutions. Unfortunately, it tends to keep organizations away from actually creating business value.

Luckily enough, Big Data technology providers are coming together to combine their efforts and ultimately make life simpler for their clients. Initiatives such as the Open Data Platform initiative or the - very important - integration of Spark into Big Data stacks such as Cloudera’s One Platform are illustrative.

And by infusing the incumbent ERP world with next-generation insights (such as in Insight-driven Operations for SAP), the focus once more is back on business outcomes.

The way to succeed a Big Data initiative rarely lies in the ability to leverage the best cutting-edge technology solutions – although less limitations certainly mean more possibilities and opportunities. Thinking value-from insights-from data, all the way through the organizational fabric, will do much better though.

Telling the competition that your data is bigger than theirs, will then mean that your business is doing better.

And that’s the real big thing.

Ron Tolido is ann analyst with Capgemini. This is the first piece in a series of blogs. Also see:

 Thriving On Data #2 - Real Real Time

 Thriving On Data #3 - Now You See Me

 Thriving On Data #4 - Data Apart Together






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