Our client is an international privately-owned climbing and fall protection products and job site storage boxes manufacturer with headquarters in the Northeast and Midwest U.S. With manufacturing and distribution facilities and offices around the world, the company has grown substantially through new product development and acquisitions. The client was a Legacy On-Prem TM1 (now known as Financial Planning Analytics) customer that decided to join the Bridge to Cloud program for TM1/Production Aggregate (PA).
The client had been managing their production and inventory using a Production Aggregate Plan. Inventory management by the plan resulted in maintaining the right amount of inventory without overbuilding or running out of stock while optimizing production. The Production Aggregate Plan was being completed in Excel, which limited the process. Identified challenges were:
- Time intensive: In Excel, the plan took eight plus hours to complete. Revisions, new machines and processes, and shift changes all added additional time.
- Limited flexibility and expandability: Analysis was limited in Excel causing additional processes to be used. Due to Excel formatting limitations, the client found that there was no easy way to look at trends, to see results in real time, or to get snapshots.
- Decentralized process: To prepare for the monthly plan, the client was required to repeat global assumptions on each plan and sync up. The prior month’s Excel filed were opened in Sharepoint and a complicated set of instructions involving applications and reports were followed to begin preparation.
The complicated, inflexible, time consuming planning process called for a faster, more expanded, more flexible, centralized method.
The client has experienced multiple benefits during their Cloud transitioning process that connect to achieving strategic goals and saving time and money. At this point, some of the positive changes leading to the cost and time savings are as follows:
The client’s decision to use the Production Aggregate (PA) Plan and to transition from the On-Prem TM1 to the Cloud was determined to help achieve strategic goals, to save time and money, and to better serve customers. For the client, PA was a proven solution in use with the existing On-Prem TM1. The Cloud Architecture was ready to go, pulling information from the Netezza data warehousing appliance. The client used CAFÉ in its On-Prem process, which isn’t compatible with PAX on the same personal computer, but new business users of the PA in the Cloud didn’t have issues between CAFÉ and PAx. All these factors led to the final decision to move forward.
In line with the challenges identified, specific issues to be resolved by use of the PA plan in the Cloud included removing manual processes, reducing the time to update or prepare plans, removing duplication of data, providing flexibility to expand plans, and offering capabilities for reporting and analysis of the plans. To solve these issues, LPA worked with the client on the following solutions for the PA process:
- Created a Turbo Integrator (TI) Process to pull inventory, excess inventory & sales forecast
- Created TI processes to update the calendar & dimensions
- Developed centralized business rules for all 3 of their current plan types including the ability to add plan types
- Devised adjustments cube to capture adjustment values and start dates
- Provided users access to a PA Workbook (PAW) & PAx for reporting & analysis
The new PA process removed manual processes and updates, eliminated copy and paste needed to move data, added functionality, preserved the prior month’s plan, consolidated everything needed to one page, eliminated unnecessary scrolling, made all key metrics and charts visible to allow for modification of the plan to smooth out production. LPA wrote a PAW with action buttons to enable the client to prepare the new month’s plan using the new process. The benefits are expected to be fully realized as the transition is completed. Future planning analytics plans include creating a PPF Accuracy Scorecard comparing the production plan forecast to the monthly aggregate plan, devising a full budgeting application, and making a sales and demand forecast model.