Speaking from the perspective of somebody who’s been in this industry for many years, big data is not a new issue. We’ve been through this. We called it the Enterprise Data Warehouse (EDW) before, and everybody debated on how big their data was. It’s not about how big it is. It’s about what you’re going to do with it. That’s why the exciting thing is big analytics – because it’s the analytics that help you do something with all of that data.
We’re going to start to see an amazing transformation as people understand the value of what they can do with the data they have. There’s been a real challenge as we look at the old architectures of our traditional EDWs, because those that were organized around transactions weren’t appropriate for analytics. This has been part of the heritage of SAS. We’ve known for a long time that you really have to organize the data for the way you want to get information out. Now this theory is being validated in the era of big data. More and more people in the industry are understanding the importance of organizing your data in order to process it as quickly as possible.
Yes, it’s great that you can take a customer in retail from optimizing a problem with 270 million SKU combinations and going from 30 hours of process time to two hours. Fantastic. The time savings is important, but what you’ve really done is provided the organization with the ability to do scenario analysis. That’s even more important.
Now that same retailer can really work to see if they have the best plan. Before, they worried about getting through the weekend so they could just have the inventory stocked through Monday. Now they can go through the simulations, they can actually see what the different opportunities are to shift their market and to get ahead of their competitors.
As this example illustrates, one of the things I’m really excited about as we approach high performance analytics is the focus on the next business problems to solve. Now we can ask the question, where are the bottlenecks in the organization? And that’s really changing the outlook of our customers as they look forward. Take the example of how many accurate models can be created. We’ve had customers that went from being able to do just 50 models to doing a thousand models with the same staff of five analysts.
Why does that matter? Again, it’s not the speed so much as the ability to ask – and answer – 20 times more questions and then change the business as a result. So now the percentage change you can make in the business – the lift in sales, the identification of the fraud and so on – goes up. So now you are really having a bottom-line impact on the company.
With high performance analytics, we’re already seeing customers change their thought processes, change their businesses and change their approach to the data.
Banks are changing how they look at risk in risk portfolios, which allows them not just to understand risk at the end of the day but at the point where the transaction is occurring. Likewise, understanding fraud in the public sector is becoming easier. Or in the healthcare industry, we can actually do text mining across emergency medical service logs and start to identify disease outbreaks weeks earlier than you could by looking at hospital records. These are opportunities that we have now with this type of processing power.
Ultimately, you and I are going to benefit from these applications of analytics too. Our economies are stronger when the banks have a better understanding of risk. Our taxes are lower when the government lowers its fraud expenses. And our communities are healthier when disease outbreaks are pinpointed and treated earlier.
That’s why I’m excited about high performance analytics – and why you should be too.