In a great video-gone-viral, EMC’s Big Data guru Bill Schmarzo lays out a roadmap for companies looking to take on the world of Big Data. He packs a lot into seven minutes, introducing the idea of a Big Data Business Model Maturity Index, which maps where most organizations sit on the hierarchy of Big Data progress. He also lays the business models for each stage and key business drivers, like real-time access to data and predictive analytics, that can help propel organizations toward Big Data mastery.
The five main stages are:
- Business Monitoring
- Business Insights
- Business Optimization
- Data Monetization
- Business Metamorphosis
Let’s look at them one at a time, because each stage is nuanced and leads to incrementally greater value, if executed correctly.
Business Monitoring – This first stage is where most businesses are at today. It requires competence in traditional data warehousing and business intelligence (BI), and has companies struggling to collect, monitor and maintain massive amounts of internal data – sometimes decades of it – as well as unstructured data.
Business Insights – Organizations can graduate to this stage once they have succeeded in taking business insights into their key business processes and use them to guide decision-making. These insights tell leaders and managers what’s working and what’s not, and can influence business strategy across an organization.
Business Optimization – In this phase, there is a continuous loop of fine tuning performed by analytics (machines, not humans). And with all the nuggets of information dropping out of the analytics, organizations can move to stage four.
Data Monetization – In this stage, it is actually the insights that are being monetized. These data insights include things like consumer buying patterns, which is a valuable asset that can be sold to partners. This stage level of customer intelligence brings out product innovation, like smart cars and appliances in tune with consumers’ personal behaviors, so they can offer a better, more satisfying user experience that then leads to better business bottom lines.
Business Metamorphosis – This final stage is a bit like Big Data Nirvana. Organizations graduate from a product-centric focus to a platform or ecosystem-based environment, capturing and monetizing even more useful insights from their many surrounding partners and connections. Schmarzo’s video doesn’t fully explain how this ideal state will be achieved, but it’s an interesting concept to reflect on and look forward to.
Again, the interesting thing here is that Schmarzo steers clear of talking technology, and instead gives us a structure to think about how to tackle Big Data projects, one stage at a time.
For a refresher on common mistakes companies make when starting up the Big Data learning curve, check out Lynn Langit’s guest post from earlier this year, Pitfalls to Avoid when Starting a Big Data Project.
Image credit: Tom Beuthin
Posted in Big Data by Lisa PetrucciLisa Petrucci is Vice President of Dun & Bradstreet Global Alliances and Partnerships.