Newsletter 07/2018 - Analytics in Decision Making, Article 7

2frame Analytics' newsletters are back!

This is the seventh in a series of articles on Analytics in Decision Making: Two Examples about Analytics

2frame Analytics addresses here two interesting articles about the importance of Analytics for decisions.

• The first one is about the cost of not using Analytics in decisions. 

• The second one shows an example of Analytics that can be applied in other contexts.

The first article is about one of Sears' management decision.

The core of the article addressed in this post is management's decision to close Sears's product testing laboratory to cut costs in the early 2000s.

Products sold through Sears' own brands were all thoroughly tested in this laboratory. The shutdown provided a cost cut of US$ 7 million/year.

What did the management take into account to close the laboratory? How was this assessed/ estimated? 

• Loss caused by the recall  

• Damage to the company image  

• Use of the incident by competitors in their advertisements  

• Possible lawsuits brought by clients (injuries, for example)  

• Etc. 

All of them were possible to be evaluated using Analytics BEFORE making the decision.

Read the full article, addressing this decision and others in this link.

The second article is about the use of Analytics in resizing patient care in a hospital network with emergency rooms.

Currently the patients in the network under study are redirected to other affiliated hospitals or clinics according to the hospital's current capacity, but this implies that less severe patients who arrived earlier are taking up space in the hospital, causing more severe patients to have to undergo redirection.

Using Analytics, less severe patients arriving before the peaks and, due to their own attendance time, that could generate more congestion in the emergency room during the subsequent peak period, causing redirection of more severe patients, are redirected previously according to the indication of Analytics, streamlining the time of care of the more severe patients.

As a result, the complications that would arise from waiting in line for the most severe patients are minimized:

"But my company is not in the medical-hospital industry, so this second article dealing with patients and hospitals doesn't matter to my businesses..."

"But my company is not a big store, it would never go through a problem described in the first article..."

For example, the second article's approach/ rationale can be used in other situations. By changing "patients in a network of hospitals" for "products in a chain store," we would have as target a shorter shelf life of these products.

Analytics is about solving problems, no matter what they are and where they come from. 

We ask again:

Do you already use Analytics for decision-making in your company?

Read more about the subject of this Newsletter:

1) "Sears: A Case Study in Business Failure", https://www8.gsb.columbia.edu/articles/ideas-work/sears-case-study-business-failure

2) "Shortening ER Wait Times through a Glimpse of the Future", https://www8.gsb.columbia.edu/articles/ideas-work/shortening-er-wait-times-through-glimpse-future

Originally posted on  09/15/2018