Cloudforce: Coffee filters out fighting talk for collaborative message

The relationship between CRM and real-time, high volume analytics seems to be getting closer every day, yet when CRM’s 800-lb gorilla, Salesforce.com, comes to town and puts on its annual spectacular, Cloudforce, at London’s ExCell Centre the mention of Big Data and real-time analytics was notable for its absence.

At least it was absent in any direct sense, which seemed strange given that the ability to tease out those vital droplets of information that can be gleaned from vast datasets can mark the difference between cornering a market and being an also-ran. And it wasn’t there in any direct sense because, as the company’s VP and head of platform research, Peter Coffee, pointed out, Salesforce sees the issue of analytics somewhat differently from most others in the CRM business.

“You’ll have noticed in the keynotes today explicit acknowledgement of our customers’ considerable investments in legacy resources including SAP, and that one of the most important contributions we can make is to make the latent value of those SAP investments considerably more operational to the organisation by getting relevant sub-sets of that information in a usable form on hand-held devices. We are not loath to acknowledge that SAP has a franchise with our customers and that it is our goal to be seen as a constructive partner adding value to that rather than an adversarial partner that wants the SAP stuff out of the way.

“We have a public campaign telling SAP customers to look on us as a value-adding tool to that. I should tell you that SAP officials have told me to my face that they regard this as a very hostile manoeuvre on our part. And when I have asked if they see any opportunity to do any co-operative positioning in the marketplace they have essentially said: `no, we’re going to fight you tooth and nail on that’.”

Coffee’s attitude to this is that customers don’t want to hear about vendors fighting each other; they want to hear about vendors looking to complement each other to benefit the customers. In his view, Salesforce talks about customer success, and he doesn’t see traditional IT providers doing that at all. He puts this down to the fact their 'product' is technology, whereas Salesforce only gets paid by customers who find value.

“As for the question of real time analytics specifically, I had someone say that they could see where IT is going. 20 years ago it gave you last year’s results, 10 years ago it gave you last month’s results, and now it is able to give yesterday’s results. We’re getting closer to real time. But in my opinion getting asymptotically closer to real time is a very timid goal. I want to do better than real time. I want to be able to tell you on Friday what is going to happen on Monday.”

So his goal is anticipatory, predictive analytics. Some of that still uses traditional analytics, but he feels that where the premier brands have arisen it has stemmed from where people have been able to pull together the traces of customer desire and recognise the opportunities to meet them with offerings that were not evolutionary but innovative.

“Steve Jobs never used focus groups to design his products. And I believe the world’s premier brands were not created by mere analytics but by insightful interpretation that delivers innovation that customers did not realise they wanted until they see it. And that is a social process.”

So what he sees is a need for more interaction, and not solely human interaction, and this is the key to the Salesforce mantra of the social enterprise.

“The opposite of social is anti-social, which is not desirable in any context. An anti-social system answers the same question in the same way every time, that doesn’t have any sense of the implications of the answer and is driven by schedules and procedures rather than driven by events. The three elements of social behaviour are sensitivity to context, adaptation to changing interests and responsiveness to events rather than rote procedure. And those three can be present, or absent, from an algorithm, a process, or a person.”

This can play the key role in large scale social enterprises by enabling conversation and the spontaneous, intuitive connection of ideas and evidence. “If you can facilitate human interaction with socially conceived algorithms you have scalability, consistency and the chance for continuous improvement,” he added.

Coffee certainly sees real-time analytics as important, particularly in the detailed examination of the available evidence, but it is still ultimately studying the wrong elements. “To me it is like an ever-bigger telescope used to study your rear-view mirror, when you really need to know what is coming up on the road ahead. Mere analytics is very seductive at getting you to believe that harder you look behind you the better idea you’ll have of what’s ahead.”

He certainly believes that analytics can uncover unusual associations, strange clusters of events or sales types, unassumed behaviour patterns amongst customers, and unusual correlations between events, and that these are important grist to the mill. But he makes the point that finding correlations does not automatically lead to the identification of causation. And in sales terms, of course, identifying and understanding what causes quirky sales patterns to happen, and then determining whether the can be repeated and expanded upon to advantage, is actually the key objective.

The key therefore, is to turn the way people behave, communicate and intuit potential solutions to upcoming issues into algorithms.

For Salesforce this manifests itself in the form of Chatter, which Coffee defines as a socially enabling layer of the Force.com platform, rather than being simply a conversational environment. An object, which can be any fact or record, can surface the fact that it has changed state and may require attention. This is another implementation of a growing trend in cloud systems monitoring and management, finding ways of getting exceptions to identify themselves. As Coffee asked, is it better practice to have customer accounts that have gone `into the red’ identify themselves to the account manager, rather than that manager having to keep search all accounts records, just in case. The objective is to allow people more time for value-adding thinking, rather than tasks that can be automated and add no value in their own right.

“This approach lets people do what people do well, which is look at something unusual that is happening and figure out why it is happening, and lets computers do what they do well, which is look through vast quantities of data and find things that don’t seem to fit.”

This exception-targeting approach is certainly an important model that can get individuals and teams focused onto the issues – be they problems or opportunities – that can realise the most value for a business. It is also a model that is most certainly going to help businesses identify the staff with the best insight, intuition and creativity in producing solutions that dig out that value.

In that context what it does suffer from, however, is a somewhat inappropriate brand name. Coffee grudgingly accepted that `Chatter’ does carry with it the connotation of the ephemeral. Chatter is the antithesis of what most business managers would expect from their staff. He had a defence prepared, however.

“Chatter in the intelligence community means the raw material from which you identify facts, and that is the way I look at it myself. But I agree the `civilian’ connotation suggests a degree of frivolity. Getting people to understand the implications of it as a platform layer rather than a conversational tool occupies a fair share of my bandwidth these days.”

Interestingly, his mention of a recent blog post about people using chain saws to cut down trees without starting the motor, and needing to understand how to turn the motor on to gain the advantages, underlines an issue for Salesforce itself. It suggests that while many users may have Chatter, not many may be using it correctly, if at all.

He calls Chatter a wall-to-wall collaboration environment, and in that context one can see its potential, especially if it then works in collaboration with the big data analytics tools now available and the provider of essential feedstock to the intuitive process – a possibility Coffee considers will become increasingly likely.

But he accepts that there is a need for more education and training amongst the user community as to what Chatter really is. In his judgement it is a great deal more than just chat-mode in Facebook.