The Process of Managment and Business Decision with Data Science 1 Part.

In the past post, we are talking about the how can Data Science help to take the best decision in a company. In that post we introduce the S&OP and the importance of a company. Now, we are talking more details of the principal functions of the S&OP and how to go into data science on the process.

Nowadays, the companies live a constant need to reinvent, the competition is very hard. the executive takes decision every day. In virtually every decision they make, executives today consider some kind of forecast to understand the behavior of the sales.

The principal function of a forecast is to give visibility to the company

But with this revolution of data science is not the only tool to get visibility of the company. The executive needs visibility to take a decision but that not mean just a forecast. Also, they need to know the strengths and weakness of the company and practical diagnose of the situation in all department.

Although we know that is very important information. To get the information and create meeting to talk about the situation for areas take a long the time that executive doesn´t have. In the 80’s born the S&OP.

This process promises to solve situations like the previous one by aligning demand and supply. However, as the process has evolved, it has been understood that its scope is much broader and that well executed it becomes a central process to the integral management of the business.

Sales & Operation Plan (S&OP)

What is an S&OP?

“The integral process of management and business decision making to balance the demand and supply, align the commercial, operational and financial plans with the business strategy in an adequate time horizon”.

The key concept is “integral management process and business decision making”. First, we define the management process:

The one we follow to make a company assign its resources and execute daily actions that are consistent with the plans and objectives.

The one that facilitates the decision making that marks the course of said actions.

That means, prioritize decisions or investment that agree with the goal of the company. To carry out that decisions are very important the metrics we use to follow the plans of the company.

The metrics which are finally governing the behavior of people (they do, what the metrics say) that point is very crucial because If they have great metrics, they have great results.

That is the first point to participate Data Science in process of S&OP. General, there are already metrics to follow objectives and plans. But not always are the correct.

The principal fail is no integrated metrics. The S&OP is the process where it put together different department of the company. So, the departments of the company should have metrics that check the objectives of the different department.

That means, we cannot require sales of the 20% when we do not have the capacity to support the sales for a supply chain. Also, we cannot say to commercial to get the most margin possible occasionally force the inventory management to get GMROI down.

We must align the metrics of the different departments, that means, the metrics of a supply chain are the same for operations, commercial and vice versa.

Data Science participates to separate information and classification of the metrics of the company. In most companies, we have a lot of items to do, coordinate and sell. In some companies we have a classification of this items, the general is for its sales or the frequency of his sales calls it “The ABC Code”. How can you see? it is very simple a general the classification. That generates that although help us to focus on some items. The classification is very general and may is not the correct.

For example, we have classification the sales for ABC codes depends on the frequency of the sales. A is the most frequency sales and C is the fewer sales. The items with a code A may are items that, yes, we sell a lot of that item but may e his margin is not great. Do you need to focus in this item?

Now, data science allows classification in better way. We can classification on variability, margin and sales frequency. That means, products are constants, frequency and generate money.

With a simple classification we can see a better form of the importance of the items and we can get better actions to respond.

In the next post, we can explain more about the classification and another metrics that we can participate in an S&OP and data science help to get it.

High Data Stories

All about the Data Analysis with entrepreneur

Luis Alberto Palacios

Written by

Economist | Strategic Planning | S&OP | Data Scientist | Demand Planning | Consultant

High Data Stories

All about the Data Analysis with entrepreneur

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