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An Acme company want to give bonus to their sales team. In order to decide which person is the best and how much amount of bonus should be distributed, their use a methodology called "data-driven", by collecting all sales person data for each days. There are three data that their collect: how many kilometers did the person travel each day to the clients, how many clients they meets each day, and how many deals their made each day.

At the end of months we got the reports for the three salesmen sorted by distance, number of clients, and number of deals; in descending order:

+------------+----------------+-------------------------+-------------+
| Sales name | Total distance | Total potential clients | Total deals |
+------------+----------------+-------------------------+-------------+
| John       | 204 km         | 30                      | 3           |
+------------+----------------+-------------------------+-------------+
| Jerry      | 150 km         | 10                      | 8           |
+------------+----------------+-------------------------+-------------+
| Jane       | 103 km         | 22                      | 4           |
+------------+----------------+-------------------------+-------------+

The management looks at the data and find that the distance number is larger and decided to use that as measurement for giving bonus.

* * *

An IT department wants to measure the performances of their developer. Once again, they decide to use "data-driven" by collecting number of commits each developers made each day, number of bugs they solved each days, and number of tasks their completed each days.

At the end of the months, the management get the following reports,

+--------+---------------+-------------------+-----------------------+
| Name   | Total commits | Total bugs fixed  | Total tasks completed |
+--------+---------------+-------------------+-----------------------+
| John   | 204           | 30                | 3                     |
+--------+---------------+-------------------+-----------------------+
| Jerry  | 150           | 10                | 8                     |
+--------+---------------+-------------------+-----------------------+
| Jane   | 103           | 22                | 4                     |
+--------+---------------+-------------------+-----------------------+

The management thoughts that the commits number can be manipulated, so they decided to based the performances based on the total of bugs fixed. One thing that management not know is the bugs that the developer John fixed is from the 3 tasks that he completed.

* * *

A food manufacture that produce instant foods has four pipelines. The first pipeline is for preparing and cleaning up the materials, handled by one machine. The second pipeline is for cooking up the materials, handled by three machines. The third pipeline is for finishing and quality assurance, handled by one machine and by two humans for checking and sampling the output. The last pipeline is packaging, handled by one machine and three humans to store and load the packages.

Given 1000 materials each day, the manufacture can only produce around 800 foods with left over 200 materials from the first pipeline and around 100 produced foods not sampled by humans. Also, most of the times 5 to 10% output got rejected due to the taste is not good, "a little bit stale" according to one of the human that test it, "taste weird" according to others.

The inspector trying to figure out why there is a left over materials and why some finished foods is rejected. First, they measure the time in each pipeline, how long the process take times from the start until it finished and get processed by the next pipeline. Second, they measure the number of input and output produced by each pipeline. Third they measure the number of sample that each quality assurance check each day.

After the data has been collected, the inspector see the report:

+-----------+----------------+-------------+--------------+--------------+
| Pipeline  | Time (minutes) | Total input | Total output | Total sample |
+-----------+----------------+-------------+--------------+--------------+
| 1st       | 30             | 100         | 100          | 0            |
+-----------+----------------+-------------+--------------+--------------+
| 2nd       | 320            | 100         | 100          | 0            |
+-----------+----------------+-------------+--------------+--------------+
| 3rd       | 60             | 100         | 95           | 5            |
+-----------+----------------+-------------+--------------+--------------+
| 4th       | 60             | 95          | 9 boxes      | 0            |
+-----------+----------------+-------------+--------------+--------------+

The inspector see that the second pipeline take most of times and concluded that they need to add more machines to decrease the process.

The factory add the second machine to the second pipeline and gather new data.

+-----------+----------------+-------------+--------------+--------------+
| Pipeline  | Time (minutes) | Total input | Total output | Total sample |
+-----------+----------------+-------------+--------------+--------------+
| 1st       | 30             | 100         | 100          | 0            |
+-----------+----------------+-------------+--------------+--------------+
| 2nd       | 110            | 100         | 100          | 0            |
+-----------+----------------+-------------+--------------+--------------+
| 3rd       | 110            | 100         | 95           | 5            |
+-----------+----------------+-------------+--------------+--------------+
| 4th       | 110            | 95          | 9 boxes      | 0            |
+-----------+----------------+-------------+--------------+--------------+

The time to process on the second pipeline decreased but the time on third and fourth pipelines now increased due to amount of input that need to be processed double.

A couple of weeks later, a government from public health department inspect the factory after some reports from people that they got sicks from the instant foods that the factory produced.

Upon inspection they found that 40% of raw materials that they use are not fresh and there is a dead insects in one of pipeline due to the sweetness that attract them.

* * *

All of the examples above is fictitious, especially the first one, since no sane manager could decide bonus based on number of distance.

The idea of this article is to show us that applying the "data-driven" in the wrong ways may result in the wrong decision, even worse, may blind us from the real issues and cause further damages to our self.