Schneider Electric: Incentive Payout Campaign

What were the underlying reasons for the need of data? Describe the business and technical challenges the company was facing and how data integrations can help.

During the annual short term incentive payout campaign, the Americas region historically received about 900 to 1000 payout corrections to process outside of the HR system. This resulted in manual work, involved multiple teams, and took months to complete. The application allowed us to connect systems and automate repetitive tasks such as messages and letters inserted into tickets, closing cases without human touch, creation of master file for correction log and no longer required multiple team intervention. These improvements focused on both the front end and back end experience as well as reducing the overall time spent on each correction. This gave us the ability to process more corrections on time instead of late payouts which improved the overall employee experience. The application integration has saved us hundreds of hours of work.

Employees use to receive their productivity payments, but sometimes it is difficult to manage different schedules or positions change between the employees across the company on a yearly basis, that’s why managers require to address mistaken payments to request their correct payment. The option was to use the Schneider Electric’s ticketing system in order to request those changes and corrections, for a time it was ok, but over the years, the requests got bigger and bigger, so a solution was needed in order to collect the data from the system, convert it, manage it and get back to our employees with the new letter. When we received the request, SnapLogic was not an option due the re-attachment of the new letters, but after further investigation we noticed that SnapLogic fit perfectly on the complete request. So, we first needed to receive help from our admins of the Service Now systems to get their help and adapt the requirements from the business into the ticketing system. Once we did it, our Service Now team delivered the needed APIs for us to start with the development. So we had a requirement to get data from the tickets, compile them, wait for the letter and attach it into the ticket and the best part was that we had the perfect tool to create such solution “SNAPLOGIC”.

Describe your data strategy and how you executed the strategy. Include details on how SnapLogic played a role in the strategy and execution, including Snaps and other SnapLogic products/features.

The project consisted of sending corrections of the STIP (Productivity bonus) percentages once the letters were sent with the% to pay of each employee, this process consisted of generating a ticket within the Service Now portal, with which employee data was attached and the percentages to be corrected, with this the information had to be compiled in a master file which provided the necessary data to be included in a macro which generated new letters for the employees already with the requested corrections. For this, a process was generated in SnapLogic with 2 parts, the first one that grabbed the s @ S tickets in the Ready status, the data was obtained if there were less than 10 employees within the ticket and if there were more than 10 through An Excel file, once the data had been obtained, the master file generated and the status of the ticket changed to Work In Progress, the next step was to grab the Work In Progress tickets, search for the new letters in an box folder and through the file name (which included the ticket number) find the ticket with that status in s @ S, attach the letter (s) that belonged to that ticket and close it completely.

For the final output we had to work with the Service Now team, to get the needed APIs, we also worked with the SnapLogic team in order to develop the needed pipelines, for this part it is important to mention that our time zone and SnapLogic’s teammates time zones are completely different, so we also had the challenge to connect at different time zones to finalize the project.
The estimated numbers were approximately 400 hours during the campaign, which ended with a use of less than 100 hours, thus saving 300 hours that were used in other projects and / or processes.

More than 500 tickets were processed and the manual time per ticket was 33 minutes, something that was reduced to a use of between 7 to 10 minutes per ticket.
The delivery was made at the end of February, launching the bot at the beginning of March.
It should be noted that the project was for the US and for South America.
Currently the project is in talks to renew it the next with some improvements.

Who was and how were they involved in building out the solution? (Please include the # of FTEs, any partners or SnapLogic professional services who were involved on the implementation)

FTEs: 5
Only 1 developer
Oscar Rodríguez: Developed the end-to-end solution.
Chandramohan Ananda: SnapLogic architect, supporting questions from our side and sharing recommendations to me.
Sagar Koti: S@S architect who delivered the needed APIs so SnapLogic could get in and work inside s@S.
William Chen: s@S architect who helped to create test tickets to test the SnapLogic solution

What were the business results after achieving this data strategy? Describe how your company, departments, and/or employees/customers benefit from the data, and include any measurable metrics.

File with Savings, has been uploaded below.

We have had less corrections submitted this year because of other actions implemented so it is hard to do an apple to apples compare. But if we had used the same correction process as last year but with the lessor number of corrections, we would be at about 242 hours instead of only 73 hours. That shows we have had a 70% decrease in the number of hours spent on corrections this year!! The impact is in the hours saved for the PeopleLink and Rewards Services team members involvement time. In the past PeopleLink was involved in every single corrections case and now they are included only sporadically. For the Rewards Services team, they would have to help me process the corrections, answer and close tickets, this year it has been only me.

Anything else you would like to add?

The development took around 2 months to be finalized. We also had the challenge to develop a pipeline that needed an access token and a refresh token for security purposes, the goal was to use only the Service Now credentials to obtain the access token and the refresh token, once we got the refresh token we had to use it to obtain new access tokens. If we used SN credentials for more than 5 times on a yearly basis to get the access token, it would be blocked until the SN team had the chance to unblock it, so also we had to develop a solution that could be able to get that access token using only the refresh token that would expire on a yearly basis and have a solution that would be able to create access tokens if the solution had to run for more than 30 minutes (The expire time that the access token has). So as you can see the solution has a process that will run on a yearly basis to obtain the refresh token with the SN credentials and then the daily run will only use that refresh token to create new access tokens every 30 minutes if it’s needed.

The project has 5 Pipelines:

  1. STIP_RefreshToken: Creates the refresh token file for Access token creation.
  2. STIP: Gets the refresh token file and activates the STIP_CreateFiles_ChangeTicketStatus & STIP_Add_PDFFiles Pipelines
  3. STIP_CreateFiles_ChangeTicketStatus: Gets all of the tickets in ready status, separates the tickets (Less than 10 and more than 10 employees) and sends the process to child pipelines for more than 10 employees tickets, for less than 10 employees tickets, the process creates the needed files and change the status from the ticket into work in progress
  4. STIP_DownloadAttached_Files: Downloads the attached files on more than 10 employees’ tickets and chance the status from the ticket into work in progress
  5. STIP_Create_MasterFile: Merge the files in order to create a master file.
  6. STIP_Add_PDFFiles: Gets all of the tickets from Work In progress status, searches for the PDF files, attach them into the ticket (Could be 1 or more files to attach) and change the status to close complete.


STIP_RefreshToken