The Sargasso Sea – how big data can reduce alignment
The Sargasso Sea, a large area in the middle of the Atlantic, used to be famous as a graveyard for ships. Captains would avoid the area for fear of being stuck in the seaweed that collects there. What’s ironic is that the captains of the ships were worried about the seaweed around them and didn’t pay attention to the calm winds that are common in some parts of the Sargasso Sea.
The captains were so busy looking down, they didn’t see the real problem.
They should have been looking up.
I’m a big believer in data-driven decision making. We can’t make effective decisions unless we know what impact they will have on both the activities that foreshadow outcomes and the outcomes themselves.
But we can go the other direction, as well. Too much data can cause us to spend time looking down at the numbers and not up at the business outcomes.
And, unfortunately, big data can make it worse.
I started my career in technology support and immediately was fascinated by the breadth and depth of data I had at my fingertips. Not only could I see the trends, I could dive deep into more than 100 different reports. I could report on minutia that were fundamentally unimportant.
The sheer volume of data led me to a downward-looking approach to management. Actions on one little area, disconnected from their impact on the broader business impact, didn’t lead to inaction, but the wrong action. The kind of feedback that Peter Senge’s describes in The Fifth Discipline as the unintended consequences of simply pressing forward.
In my current position, I’m finding myself awash in data again, this time coming from numerous relational database-based systems. But the sheer volume of information emerges most from Internet-connected equipment. Equipment like bulldozers are providing extremely detailed information on their operation. Sue Marek in a 2014 article on FierceWireless says "In a Cisco-commissioned report on the value of IoT, researchers provided some insight into exactly how much data is likely to be generated every day. For example, a jet engine generates 1 TB of data per flight and a refinery generates 1 TB of raw data per day."
This wealth of data is forcing me to wrestle with the same choices as when I began my career. Look down to the detail or look up to the outcome.
We need to create rules of thumb that help us make decisions when we are faced with new sources of data. Each time my team mines our data (or even choose to store data), team members should be asking themselves (and we try to do so):
- What business value can be derived from this data? For the company? For our customers?
- Will more analysis speed up business operations or slow it down?
- How long should we keep the data?
If we don’t have compelling answers to these questions, we shouldn’t be analyzing that data. If we persist, then we are not looking for ways to move forward.
Organizations that spend too much time in the depths of their big data should heed the words of the chain gang in the opening scene of Les Misérables, “Look down, look down, you’re here until you die.”