Watson is currently in pilots with leading healthcare and financial services organizations and will be expanding to production-level deployments in new use cases and industries going forward. Getting ready to deploy a Watson solution takes thoughtful planning and selection of where and how to apply its power. Laying the groundwork often involves building strong big data and analytics capabilities which are complementary to Watson itself. Doing so on project-by-project basis ensures that each step is justifiable on its own from a financial and business value perspective and also brings you closer to readiness to apply the transformative power of Watson to your business.
Data volume, velocity, and variety is growing at an astounding rate with a full 90% of the world's data less than two years old. But most of this data (as much as 90%) is unstructured meaning that it does not sit in database rows and columns and is therefore off limits to most traditional computing systems. Building capabilities in text analytics, and natural language processing can help bridge this gap to open up access to a world of new, valuable information as well as increase the speed to value of future Watson implementations.
Analytically astute organizations are 260% more likely to be top performers than analytic beginners. Turning information into insight takes rapid analysis of data to tease out hidden patterns from seemingly unrelated data to find performance reporting and decision metrics as well as to anticipate what will happen next. This can help get you out of being reactive and into more proactive decisions as well as generating the key material IBM Watson can use with a complementary solution.