Key is to have an end game. What is the desired outcome (the win). Line up all the questions and let them race (in real-time) to the finish line.

No one knows the winner before they start the race. Let all the questions try to “qualify.”

1. their data is scattered all over the place in different formats

2. their analytical capabilities are seriously lacking, most “analyst” doing basic grunt work, turning out canned reports or just telling the CEO what he want to hear

3. most “analyst” don’t have the freedom to go looking for opportunities in the data, more often some exec will say “this is what I believe, go out and prove my view point”, insights should come from data not vice versa

4. very few executives are either brave or stupid enough to act upon insights that goes against their beliefs, especially if it proves them wrong in the first place

5. most companies do not have an effective measuring, testing or post mortem procedure for action on said analysis, theories are all great and dandy, but until you can demonstrate actual cause and effect, its all blueberries

6. most companies will sweep failures under the rug instead of doing rigorous analysis, as people leave and new people come in, these failures will be repeated

exception companies deal and overcome the above

data and analysis is only as effective as the people and processes you use and the effective actions you can generate

sense-making on streams ( from Jeff Jonas who gave best preso at DeFrag this past week )
1) Evaluate new information against previous information … as it arrives.
2) Determine if what is being observing is relevant.
3) Deliver this relevant, actionable insight fast enough to do something about it … as it’s happening.
4) Do this with sufficient accuracy and scale