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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 fisrt 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.
Shortly thereafter, a stove from Sears' own brand had to be recalled due to a problem that would have been diagnosed by this laboratory. The oven door could not handle the weight of a Thanksgiving turkey leaning on it.
What did the management take into account to close the laboratory? How was this assessed/ estimated?
Loss cause 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)
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.
The emergency rooms don't receive patients evenly over the course of the day: they come in waves and there are arrival spikes during the attendance.
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:
reduction of the total time of care of the entire affiliated network of hospitals,
resulting in a reduction in the total time spent on attendance with all patients in the network of hospitals that share patients,
and a resulting decrease of the death risk for the patient aggregate.
Read the full article in this link.
"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..."
2frame Analytics brings examples from different areas to show that Analytics can be used (and is used) in all business areas.
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?
We are available to meet you: let's talk about analysis designed by humans for humans, with the help of computers.
Contact us and schedule a meeting between your company and 2frame Analytics.
Telephone: +55 (11) 3042-2433 / +1 (585) 290-3019 (WhatsApp)
Email / Google Hangout: firstname.lastname@example.org
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