Tuesday, September 30, 2014

Decision Driven Data?

Blum, Goldfarb and Lederman have a nice commentary on the use of data driven decision making. We may hope that the collection and analysis of more data leads to more evidence based decision making. However, in many organizations, decision making is advocacy based in which subordinates petition their manager for permission to go ahead with their pet project. In this case, the subordinates have an incentive to cherry-pick the evidence and managers learn not to trust the evidence. If this is not addressed, the promise of "data analytics" is lost.

Blum, Goldfarb and Lederman suggest that the organizational relationships must change in order to make use of all these new data. Advocacy of previously held positions should be minimized. One way is to push decision making down the chain. The role of the manager may be to determine what to test, with the subordinates having decision rights, and responsibility, over how to respond to the test results.


  1. My daughter and her future husband were looking at a foreclosure condo to purchase. They live in a rental in the same development. There costs for the rental (including parking and dog fee) is $2,500 which includes use of the pool and gym; the same as a condo owner in the same development. Her boyfriend was very hot to buy something. He said they would move into the condo and then rent it later as an investment property. They had spoken to a friend who was a real estate agent and she said it was an excellent buy for that community.

    Because of the location of the community, it was eligible for affordable housing purchase incentives. The interest would be 3.5% on a fixed rate 30 year loan with no closing costs. The condo was selling for $285,000. Working with this number, adding in HOA fees of $350 a month for 2015, insurance rates, they figured the mortgage payment, including HOA fees and insurance would work out to the same $2,500 a month. They wanted to make an offer and they came to talk with me.

    I explained that they need to look at all the variables, costs etc… before making a decision. Just because the condo is a good price, it does not mean it is the right purchase for them. And since they do not have discretionary income for investment purposes, this should not be looked at as an investment, but as primary living space. I always tell my children, get all the information you can before making a decision; an informed decision.

    First, I explained, taxes go up every year as so HOA costs and insurance. Your payment will only be $2,500 this year. So unless they have savings they are ready to tap into or can guarantee a raise in salary, they will be paying more money a month within 6 months. Also, they need to take into consideration that if the appliance break or the shower, faucets etc. need repair that is a cost to THEM. They are no longer renting.

    The rental market shows that this condo rents between $2,200 and $2,700 per month. They just cover the costs. They are still responsible for paying for breakage and,, other incremental costs.

    The fact was that they did not have extra money to secure the property whether they lived in the property or rented the property. The only real option was to flip it; purchase the property, paint it, clean the carpets and list it for $355,000 (the last condo sold for $360,000 but was on the market for 11 months.).

    They are still renting. No purchase. That was the right, informed decision.

  2. Data can be spun many ways. There always seems to be an explanation of why data shows things different than what we want. Take the stock market for example. The amount of data mined and collected is incomprehensible. One day it is up, next day it is down. Each day we have an explanation why it did what it did and we are generally satisfied with those explanations. But stop and look at some of the reasons given for the ups and downs. One day we hear Wall Street didn’t like what happened somewhere in the world. Next day the market is up and we hear they liked what happened with the Fed, raising interest rates. The following day we see stocks go down and hear Wall Street didn’t like what the Fed did raising rates. Do we really know why causes markets to up or down? Do analysts look for something they assume caused the change? Does data tell us enough as to why these major moves happen or is all the data useless and we just apply subjective analysis to come up with a hypothesis we believe is reasonable?