When Bing came out last year they presented it as a Decision Engine. Microsoft caused a strong reaction in the Decision Management space.
“What are they talking about? No way! Non sense!!! Have they gone mad?”
Well, of course, it took a few minutes, days, weeks, months to get our minds out of the trenches (if at all) and welcome the new perspective. Okay, it requires being incredibly open-minded for a devout decision management expert but, once you make the jump, there is a fascinating world to discover and embrace. Really.
Is it true? Yeah!
Since this old announcement, and with no correlation I must add, I have boosted my social media presence and experimentations, fine-tuning what to share with whom. In the process I ran into some very interesting blogs and presentations. I was inspired and impressed by many. For instance, I was just listening to the excellent webinar by Brian Solis on Hubspot on “SEO is the new Social Media Optimization”. I liked and tweeted one of his quotes:
“Social Media affects every step of the decision making process”
— Brian Solis
May sound like a blanket statement to some but please think about it… In every decision we make day in and day out, we start our decisioning process with some thinking. We ask friends and family, we research specialized websites, we mine our past (personal or corporate), etc. It often starts with a search of some sort. So from that perspective search is a decision engine! Well, a decision support tool…
Decisioning is not all about decision automation like we, in the industry, tend to think. The world of decisions is not limited to those transactions you process in high volume. There are manual, sometimes isolated decisions that can benefit from decision support. All those decisions you make at home about buying a house, where to go on vacation, which movie to watch, what school to attend or what to cook tonight. Do not think those point decisions only happen at home. Corporate life is made of many similar decisions: when to open a new store, who should be promoted, when to sunset a product, etc.
Steve Hendrick put together a great chart at one IDC breakfast I attended earlier this year. I am sure this will be presented again as it does illustrate very well the different nature of tactical decisions (High volume, Low individual impact) and strategic decisions (Low volume, High impact). Obviously BRMS plays in the first category. Decision Management as it is defined today plays in the first category. The larger, more strategic Decision Management has not been invented yet as the traditional Business Intelligence tools are barely connected to the decision automation technology.
How does Search affect Decision Management today and tomorrow?
Social Media is actually the key element of change here. Granted you can search for product comparison or heated reviews and stuff like that online and claim that the web helped you make a decision but this is only step one. Traditional search helps quite a bit here and this is where Google and possibly Bing get their initial start. This is nothing compared to the potential though.
Social Media brings tons of knowledge into the equation. I was intrigued by sites like Hunch that collect tribal knowledge on popular one-of decisions and turn that into decision trees that guide visitors. Again, this is only the tip of the iceberg… There is more.
I see a wonderful opportunity with social media data enrichment for decisions. The opportunity created by the ability to search, the ability to understand, the ability to rank, and the ability to discover the many facets of the subject of your decision is humongous. This obviously goes beyond traditional search. Brian Solis listed real-time and social searches as two key ingredients that complement traditional search. Social searches outperform by far traditional searches like Google to access Press information. People trust people they know and they share. This is a wonderful source of information: just knowing who recommended it, who is connected to whom. I am eager to see the evolution of Reputation in the industry.
If I recall, SAS created a Fraud Management application that incorporated social search so that fraud case workers could better understand relationships extracted out of those social networks. If you befriend fraudsters, it may increase you likelihood of being a fraudster. Sound like patterns could emerge from the real-time data that can be acquired out of those social networks and be leveraged very effectively. This is brilliant and yet so simple. In a few years all systems will have those social aspects incorporated and we will not think twice about it. How exciting to be watching the transformation!
The Chicken and the Egg…
So Social Media Searches could very well start as the decision support tool, but it may also very well provide the necessary data that will feed into decision management solutions tomorrow.
As Google changes its PageRank algorithm to account for the needs of humans — pulling more real-time social results like tweets in the pages but in reasonable amounts — it begs the question “How would decision algorithms need to evolve?”
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