Importance of Data Analytics.

We have learned about what are data in our previous topic. Now let's discuss the importance of data in our daily lives. More often than not  we are faced with multiple options where we need to make a decision. Most of the time we end up making a decision based on our previous experiences and rough logic, and we usually say that this is a “rational” decision because we have weighed all the pro’s and cons. This type of decision making are carried into situations where the impact of one’s choices are critical in shaping future outcomes, say for example choosing the right job, where to invest money, what kind of drug should be prescribed or what kind of research methodology should be applied. In this kind of situation previous experience and sound logic is not enough.  There is a need to mine and filter data that is hidden behind the situation. In this case, the situation and all the variables that are interfering with the data collectively termed as the noise and the data that is hidden form this is termed as the signal. You must learn to sort and filter these data, make analysis, interpret the outcome then use the result to make the decision.

Let me give you a simple example of the importance of data to perform a decision, something that data analytics is good at. I recently met a friend who lives in Makati City and is also a data scientist. He left the research career for a more greener and bountiful field in the corporate world, he is aiming at the position of an associate business intelligence analyst. All of the companies he applied to are BPO’s.  The schedules are all the same, time starts at 10:00 p.m. and time ends at 6:00 a.m. The first company was located in Diliman Commercial Complex at Commonwealth Quezon City, the offer is around Php. 30,000.00 (basic pay only). The second company is located in Ortigas, the offer is also Php 30,000.00 (basic pay only). The third company is located in Nuvali, Sta. Rosa Laguna the offer is also Php. 30,000.00 (basic pay only). The fourth company is just a few blocks away from his house, a 5 minute walk or a 3 minute jeepney ride away, the offer was Php 24,000.00 (basic pay only). The fifth company is located in Pasig city with a basic pay (only) of Php 24,000.00. He received a job offer from all of these companies, and he asked to give him 48 hours for the reply.

His apartment is strategically located in Makati, at the front part is the bus route going to Nuvali, Sta. Rosa Laguna.  It’s a one (45 minutes) ride from Makati to Nuvali and vice versa. On the other hand, A few walks away from his apartment are jeeps going to the MRT, buses that pass through Ortigas as well as through Diliman Commercial Complex via the Fairview route. With this accessibility to all the companies, given the compensation, he asked me one problem: Which of the company should he choose?

If we make rush decision we can say that the best option is the company in Makati because it is just located around his neighborhood and less the travel stress. The Php. 30,000.00 offered by the other companies will just be reduced roughly to almost the same as Php 24,000.00 due the expense of the travel costs not to mention that this is a 20 days a month of work.

During our conversation, we played around with the possible scenarios and performed a simple analytics. We filter out some rough data that are hidden in the situation and these are:

Obviously the basic pay, another thing we should look at is the night differential, we assumed that it is 20% of the basic:

Night Differential = 20% x Basic pay

We also take into account the travel cost which consisted of the following:

Jeepney Fare

Bus Fare

MRT Fare

And of course you need to eat, so we placed in meals (lunch break meals, snacks, etc.):

Meal Allowance= Php. 100.00 per day x 20 days = Php 2,000.00

We also take into account the deductibles such as the tax and the benefits here we termed as “other deductibles”. We assume the tax to be 20% of the basic pay and the night differential:

Tax= 20% x (Basic Pay + Night Differential)

Other Deductibles (SSS, PhilHealth, Pag-Ibig, HMO) = Php 2,000.00

Then we tried to calculate his monthly earnings, this is the net amount of money he would receive after all the deductibles, excluding the "other deductibles", have been reduced from his basic pay.

Net Monthly earnings = basic pay + 20% night differential - travel cost - meal - tax.

 His net monthly earnings is divided into two, the first fifteen days is his net salary in which the other deductibles is not yet reduced.

On the other hand, his net earnings for the last 15 days is simply his monthly earnings divided by two and reduced by the “other deductibles”.

Therefore his net salary is simply the sum of his first 15 and his last 15 days:

Net Monthly Salary = net earnings for the first and last 15 days

% Revenue is defined in this situation as the net earnings he have accrued during a month’s work, this is the percentage of money he will obtain after all deductibles have been reduced from his basic pay relative to the given basic pay, to put it simply the percent excess money he will have after everything is deducted from the basic pay.

 As you can see this is very tricky because if you look at the % revenue of the company in Makati City is at 79.33% while that of the company in Commonwealth is 78.20% however the net monthly earnings for the company in commonwealth is at Php. 23,460.00 which is greater that the net monthly earnings that is offered by the company located at the Makati office (Php 19,040.00).

To solve this we need to compare the companies by % Relative Revenue this is defined as the net earnings you have accrued during a month’s work, this is the excess money you will obtain after all deductibles have been reduced from your basic pay relative to the highest basic pay offered.

Here we can see the ranking of the companies who gives a better pay. Obviously the company located at Ortigas ranks highest compared to the rest.

Z scores further strengthens our previous result, by doing a Z-score, we can describe which of the companies where he can really have a high earning. The Z-score showed that the company from Ortigas is the highest followed by the one in Commonwealth and the one from Nuvali. So the data dictates his decision.

Obviously there are many variables that one needs to consider when it comes to looking for the right work, this includes work place environment, co-employees, how the management and admin team handle the employees, other benefits, personal lifestyle, rent, credit cards, recreational activities during the week ends, among others. But we have to admit that a good compensation usually motivates an employee to be productive.

Hopefully, I hope this simple example have made you appreciate the importance of data analytics and the power it can have to influence your decision.