Decision making is central to knowledge work and business execution. Regardless of role, every day we make countless decisions and those decisions impact key areas of execution such as customer relationships, competitiveness, innovation. Decision making itself is a function of judgment fueled by information, knowledge and experience.
With so much information available and flowing throughout our businesses, how do we as decision makers know we are paying attention to the information that matters and will help us make better, more informed decisions?
In a prior post I wrote:
A recent discussion with a customer centered on better decision making as their core business objective for using the Attensa platform. It was interesting and blunt. Better information, better decisions. Every employee, regardless of their place in the organization makes many decisions on a daily basis. Regardless of the complexity of the decision, better inputs make for better decisions and better decisions drive better execution, innovation etc.
A recent conversation with Chris Abraham highlighted an important concept that I did not address in the prior post. Over a beer, Chris shared how important Attensa's analytics were to the challenges of keeping on top of information. He is right and his comment triggered this post.
The term attention analytics in Attensa parlance refers to a set of capabilities in the Attensa platform that measure a person’s historic interactions with content (aka, digital footprint) to better assess the value of that content specific to the person reading it. Analytics based on attention have many applications, such as search ranking, smart filters or recommendations. The nature of attention analytics is best understood in the context of how they can be used to improve user experiences and/or business activities. Decision making is a good example.
Decisions are supported by converting information into actionable knowledge.
It sounds a little geeky, but in truth it’s a pretty simple concept. If a decision maker has tools that direct their attention to the most relevant information, they will spend less time hunting and gathering information and more time thinking and making confident decisions. I use a simple graphic to explain this.
Sometimes the information and knowledge is cumulative over time and sometimes it is situational at the time of the decision. Either way, if good information design is in place people will know more in less time.
In the inset image, the green dots represent information that is relevant to the decision and the red dots are information that is not relevant. In every information gathering process there is a process of discernment and there is a point of diminishing returns for efforts to find information. The quality of the decision increases with incremental discovery. The dotted line is the theoretical return on effort invested in discovery. At some point the effort to find more information is not worth as much. This is a lesson I learned as a young attorney when a mentor told me it was time to stop researching and start reasoning and writing. Without that advice, I would have kept scouring through the seemingly endless available case law.
Sorting out relevant and irrelevant information is a process of discernment. Information tools help us, but, ultimately, it is our judgment and applied knowledge—the human reasoning that takes place—that moves us from indecision to decision. This is where Attensa's filtering and analytics come into play. It brings human intelligence and judgment together with the wide body of information available inside a company and on the web. I view Attensa through this lens: Technology-aided discernment, for lack of a better term.
If more relevant information is viewed and can be moved into the early stage of our decision processes, we can make better and more confident decisions sooner.
In this graph, more information is moved into consideration sooner. The return on time invested is high and the decision maker is better informed in less time. This has value in terms of decision quality, efficiency and confidence.
In this case, attention analytics are used to augment our own skills of discernment. There are many other uses and I look forward to exploring those in future posts. Thanks to Chris Abraham for providing the impetus for this post.
