One thing was clear at Dreamforce last week, Salesforce’s enormous customer conference — something that has become apparent to anyone paying attention. It’s becoming a data-driven world. We are awash in data, but the problem is figuring out what we are supposed to do with it.
Salesforce wants to be the center of your data-driven customer strategy, of course. To that end, the company introduced the Internet of Things Cloud last week, which is supposed to pull in data from devices, sensors and non-IoT sources like app behavior and social streams. In Salesforce’s view, it’s all in the service of the customer, grabbing data and wrapping a rules engine around it to drive automated actions for the customer.
Salesforce isn’t the only company recognizing the power of data. Whether it’s predictive analytics to drive better sales results, IBM’s Watson to help doctors analyze a patient record and compare it against the medical journal literature, or Okta and Yammer using data to drive their development decisions.
In fact a couple of weeks ago, Okta released a report on cloud usage derived from data that comes through their networks, recognizing what many companies have, data is increasingly a useful byproduct of simply doing business.
Many companies are being built by gathering data, to the point they get a network effect as they grow. The more customers using the software, the more data they gather, the better the product should be.
Data has the power to change the way we do business, helping make better predictions and enabling better, more forward-looking decision making (and better products and services) — at least that’s the theory.
In an on-stage interview at Dreamforce,  Microsoft CEO Satya Nadella talked about the power of data-driven decision making and how he saw Microsoft’s role in all that. “We are building out this intelligent cloud to harness the data asset and convert it into intelligence to empower the intelligence around us,” he said.
It’s about making computing more natural. In Nadella’s ideal world, computing will be ambient and everywhere. But it’s not there yet. As though to prove how fragile the technology still is, Nadella tried to do a data demo using the Cortana voice recognition system, and it simply didn’t work for him.
But companies like Infer and InsideSales, both of whom I spoke to at Dreamforce, are trying to focus on using a set of signals from various sources to direct the sales process to the most promising prospects using data. Since it isn’t trying to boil the ocean, perhaps it’s a bit easier to make use of the data — and both companies appear to be having some success.
The really tough thing though is taking the growing body of unstructured data, that is data that isn’t stored in a database somewhere, and making sense of it. That’s the problem IBM Watson, The Cortana Analytics Suite and others are trying to solve.
The idea says IBM is harnessing that information, reasoning about what it means and utilizing where it makes most sense to drive more sensible decision-making using the strength of the machine to help humans work more intelligently.
In theory all that data is going to produce a data-driven resolution, but in reality, figuring out how to deal with that data is hard work. Companies like Microsoft and Salesforce are hoping to simplify it, but customers don’t always buy the line they are selling.
At the Satya Nadella interview/demo, he was trying to show how data when fed through the Cortana Analytics Suite could help provide a more coherent information flow if you simply query the data and ask the right questions, but one guy near me put it in perspective when he complained:
“There is the universe of data. How am I supposed to make sense of it? If I’m given a world of data, it’s too much for me, and Nadella wants me asking questions. How do I even know what questions I should be asking?”
That’s a big issue for people, and it requires systems of insight, says George Colony, CEO at Forrester, something that we are just beginning to understand. “Imagine a world where every Coke bottle sends data. Imagine the amount of data in real time that is hitting Coke second by second,” he said.
He calls the Salesforce IoT Cloud, ‘a crude system of insight.’ “It’s difficult to show the data visually. It’s difficult to correlate, but it’s at least a step in the right direction,” he said.
Companies need systems which are able to explain large volumes of complex data, but we just aren’t there yet, Colony explained. Ideally, the machine should be doing most of that heavy lifting for us, learning what types of information interest us and surfacing the data that matters most — but in reality we are a long way from that ideal.
“We’re sitting around camp fires chewing on bones. That’s not a knock [on current technology]. It’s just early,” Colony said.
And that’s the challenge. We know that when presented with a body of data, it should help us work smarter, but the reality is that it’s harder than it looks, and the tools and technologies we have in place to attack it, while incredible pieces of technology, have for the most part not allowed average business users to make that leap.
“We need systems which are able to explain large volumes of complex data to [non-technical] executives coherently,” Colony explained. And we just aren’t there yet.
