What does an Emergent Business Execution Platform look like? I asked this question in my last post of 2009. Building up to this question, I had argued that “excellence in execution is infrastructure, because processes and tools can incorporate and model best practices in execution to a degree and with a speed and flexibility not previously achievable for most organizations”. I also argued, using a memorable chicken breeding example, that “companies win or lose based on the performance of their teams, not individuals. And increasingly on the performance of teams of teams, distributed teams of teams, and networks of customer communities and partners. For companies to outperform their peers, they need a platform for group productivity.”
Social collaboration platforms are an important piece of the puzzle, but there’s more to an Emergent Business Execution Platform than you may think. This month’s SDForum Semantic SIG had the perfect line-up to tell this story: Ross Mayfield, Chairman of SocialText, talked passionately about the problems of our current dumb enterprise applications and the need to augment them with intelligence, and Jack Jia, CEO of Baynote told us about the cool things companies can do with automated intelligence.
Ross did a good job of summarizing what’s right and what’s wrong with enterprise software today. We have automated business processes – in ERP, CRM and more – to drive down costs, primarily by decomposing business processes into detailed steps with rigid handovers. Driving down costs is a significant achievement but it has been at a cost. These automated business processes 1) are designed not to change and 2) don’t include the intelligence of the organization’s people. Moreover, hard coded software like this reinforces past thinking.
Ross is advocating for a new breed of software that augments instead of automates, that supports business practices, and that allows for unstructured conversations, a software that enables an emergent intelligence. SocialText’s social collaboration platform is one such product and fits squarely into Andrew McAfee’s definition of Enterprise 2.0:
“the business use of emergent social software platforms (ESSPs)… that support collaborative work without pre-defining its structure. Structure in this context means workflows, roles and responsibilities, interdependencies, and decision rights. ESSPs like wikis, blogs, social bookmarking and social networking software, Twitter, and prediction markets.”
Baynote is a great example of another new breed of software, a new generation of analytical software applications that use data to derive insight, anticipate customer needs, act and learn. This is functionality way beyond traditional definitions of web analytics and business intelligence.
The enterprise software Ross described above delivers the same value whether it is the first, 101st or 1,000,001st interaction. Analytical software delivers increasing value with each interaction because it learns and adapts. In contrast to the enterprise backbone of hard coded intelligence, these analytical applications use real time data sources to derive and apply insights. These insights are another form of an emergent intelligence. McAfee defines emergent: “Emergent means that the software is freeform, and that it contains mechanisms to let the patterns and structure inherent in people’s interactions become visible over time.” While analytics aren’t freeform, they contain similar mechanisms to find the patterns and structure inherent in people’s interactions over time.
Baynote, for example, tracks user interactions on a website to derive that user’s context and intent. It uses the science around like-minded peer groups and “dozens of different behavioral heuristics” to “understand their visitors’ intent and context and automatically display the best content and products based on that insight”. Most websites use user generated content like voting and product reviews, “customers who bought this also bought that” algorithms, or the dreaded personal profile form to guide website content placement and actions. But the vast majority of users don’t add content, and the content that is added has, inevitably because we are human, a lot of cognitive biases (Baynote’s whitepaper on “How To Circumvent The Seven Deadly Biases” is a worthwhile read).
Baynote ’s recommendations work. They produced a 350% lift in direct revenue for Urban Outfitters when compared to their usual recommendation process (using what other customers bought and merchandisers’ suggestions). And in a Fox News competition, Baynote’s recommendation outperformed Fox News editors’ suggestions by 20%.
The take-away is that emergent intelligence comes from people and data. Both software products I have described here deliver intelligence in the enterprise. SocialText’s social collaboration platform enables the intelligence of people to better inform decision making. Baynote’s Collective Intelligence Platform™ uses data it collects to make intelligent decisions about each customer. Augmentation where it makes sense, automation where it makes sense.
Take a customer support example. Text analytics detect a support issue brewing in the broad social media sphere. The company uses a social collaboration platform to collect information, find possible solutions, inform and update the field and support reps. Analytical applications derive a set of compliant options to address the issue that are the best fit for a specific customer and push those options out to the front line in near real time.
That starts to sound like an emergent business execution platform. Are we there yet? More to come.
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