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Former Member

When we talk about SAP HANA the first thing that we think of is the capacity to process large quantities of information at a high speed - with this power there are benefits for companies, such as:

  • Improve the Return of Investment (ROI) and Total Cost of Operation (TCO).
  • Improve the processing time of information significantly to which our customers are accustomed to.

At a high level, we could say that these are the first steps that follow a company in the implementation of some of the schemas that HANA offers..

However, there is one point to my perspective that is most important:

“Break the paradigms for how Customers analyze their information


    • Traditionally, our clients define some Key Performance Indicators (KPI), Process Performance Indicators (PPI) or some other type of indicator or report with which they can measure the performance and/or operation of the company. In almost all cases, they are defined to large time periods (like annual, semi-annual, quarter, monthly or weekly in the best of the case) and at high level. By high level I mean  this is because they are only covered up to a certain level within organizations, in the clients in which I have been at least have been established up to departments or work teams.

But what would happen if instead of defining an indicator on a weekly basis, customers were able to utilize a strategy to generate indicators per day, or even per hour or per minute?

- In this particular case, I had an experience with a customer that uses this information to be able to determine peak hours in the flow of their network. And know they knew how to redistribute the load to not saturate the services they offer to their consumers.

This no doubt helps them to make decisions more quickly and accurately to which they are accustomed, well same exploit the capabilities of the tool to integrate scenarios more complete and complex, in which we can involve complete chains of processes.

To reach this point without a doubt is the FIRST BIG STEP within our customers!

However, we could say that up to this point we are still analyzing the information in the traditional manner, as though we are able to analyze more sophisticated scenarios in a period less than the currently veered, analysis is performed under the current information from our systems.

I'd like to highlight the decision-making process is much more rapid and successful, however still remains reactive, which leads us to the next level.

  • The next step is to analyze and build behaviors on the basis of the historical information of a company but for the future, to do this we would be taking over the Predictive Analytics, which I would like to list a couple of examples:

-   What would happen if our Customer can generate the distribution logistics and resupply of the stock from the stores of a company according to geographic location, time of the year - what effects would that have on our customers?

-   Another example would be that based on certain characteristics of the consumers of the services and/or products of a company, you can determine which other goods or services they could consume according to geographical conditions, economic, climatic, tastes or preferences of consumers. And this would lead us to the next level.

These  kinds of scenarios are perfect for Predictive Analysis.

  • The next step would involve the social networks, blogs, and other viral media, which must operate as trusted networks to analyze the perspective that the consumers have of our Client as a brand, as a supplier of goods or services, as well as to make decisions of what would be the new products to offer their consumers. In a few words: Analyze consumer sentiment.

In a general way this could be a strategy to follow in the analysis of information within a company.

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