This recent interview on the penetration of Big Data in the insurance industry summarizes it well: there are two key concerns that businesses have when it comes to Big Data initiatives:
1. How much will they cost?Almost Christmas movie streaming
2. What benefits will they provide?
The difficulty many businesses have answering these questions can be instructive to how companies position their Big Data products and services.
The advent of SaaS and cloud-based delivery models have caused a continuing shift away from perpetual license pricing to subscription models. With that shift, the opportunity has emerged for many software vendors to have their products purchased out of OPEX budgets instead of as one-time capital expenditures. But talking OPEX instead of CAPEX implies a discussion about TCO instead of traditional ROI. Big Data’s no longer just a buzzword, but it isn’t quite ready for that conversation yet.
The reason is simple: you can’t calculate TCO if you know neither what the operating costs (the total operating costs–not just the vendor’s quoted price) nor the return will be.
The implications are important to business building Big Data brands:
- You need to position their brands around big benefits that make it worth it for buyers to leap into the unknown. Think monumental advances, not incremental improvements.
- You need to differentiate real Big Data solutions (that deal with massive datasets made up of disparate elements not able to be analyzed with standard tools) from mere analytics offerings (that make sense of complex data), whose costs and benefits can be quantified. Think customer education, not just brand promotion.
- You need case studies. White papers are great at seeding interest among early adopters, but making an enterprise sale is much easier if you can support the thought leadership with your product’s demonstrated impact on a comparable organization’s bottom line.
Big Data has incredible potential. Target’s success identifying–and capitalizing on–pregnancies makes that clear. But it’s still in its early stages, and the Big Data vendors who realize this are the ones whose brands will be there when the market matures.