Business analytics: how to make sense of big data
Each week we ask high-profile technology decision-makers three questions.
This week it is Keith Collins, chief technology officer (CTO) of SAS Institute.
The company describes itself as the world's leading business analytics software company. With about 12,000 staff and customers in 126 countries, the company has a turnover of $2.43bn (£1.5bn). Founded in 1976 by Jim Goodnight, the firm prides itself for investing 24% of its revenue in research and development.
What's your biggest technology problem right now?
The biggest challenge is that the problems we are trying to solve have increased in complexity. Companies have more and more data, and more and more issues that they want to answer.
They have a flood of information from mobile devices, and all these data bring issues of large scale process optimisation and how to improve large scale forecasting.
Operational analytics allows people to fine tune their business. For example there is a big shift to trying to understand customers - in every industry. The products they buy, at which price. It's about customer satisfaction, whether it's for a mobile phone firm, an insurance company or ATM [cash] machines.
The analytics shows that consumers are more in charge than ever before.
We recently worked with a bank were customer satisfaction with ATMs was a huge issue, so we had to understand how to minimise the times when a machine runs out of cash, and project when the device fails.
Understanding the data made a huge impact on the customer satisfaction score and brought a $2m reduction in maintenance cost.
It's about bringing analytics to specific business problems. We had very good success with this in the retail space, and also help banks fighting credit card fraud.
Call centre optimisation is another example: How can you make sure you pay attention to your most important customers? When you are talking to a customer, do you know how they would prefer to get their information? And is there an opportunity to give them offers, to upsell?
There is an explosion in the understanding in the value of analytics. One problem is actually acquiring enough talent fast enough to deal with the demand.
So we are helping multiple colleges around the world to launch or improve and expand their analytics programmes.
What's the next big tech thing in your industry?
We are investing very heavily in top performance analytics and high performance computing.
Today there's just a small set of customers that demand that scale, but that's accelerating quickly. What we now call high performance computing, in three to five years it will be standard.
This will not always be a big company thing. There is a whole shift to being more consumer centric, and making customers mobile.
Almost any new company that is starting out today has a completely digital view of the market. New startups understand that they need analytics as part of their company's DNA.
And lots of small and medium-sized companies are looking for ready business analytics solutions that they can just plug in - whether it is in the cloud or a targeted application. We will see a shift where this software is directly plugged into a company's process and consumed through the cloud.
Even small companies can act big, because everything that works on Amazon's cloud service rivals anything that our largest customers have.
Adoption of these new models depends a bit on the age of a company's leadership. There is a new generation of entrepreneurs who gets it from the beginning. We also see mid-sized retailers changing their game.
Larger companies usually adapt when a new board comes in.
What's the biggest technology mistake you've ever made - either at work or in your own life?
I have a big problem here, picking the toughest one.
I once developed a whole set of brilliant technologies to near readiness, but had failed to tell the rest of the company about how it works.
So it's not just about having a vision, you need to plan the execution as well.
So I had this design technology for a data partition process to have the fastest data warehouse, but I didn't do a good job to educate our sales channel to take advantage of the opportunity.
Another one: I did not realise how fast the market for tablet computers would develop.