Clients
Case Study:
Tootsie Roll
Founded in 1896, Tootsie Roll has become one of the country's largest candy companies, with operations throughout North America and distribution channels in more than 75 countries.
"Optimum is a wonderful partner. They took an interest not only in the Demantra piece, but also in the other parts of our ERP, and what we did that was unique to us. Their efforts delivered a quality solution for our forecasting and planning needs."
John Majors,
Vice PresidentTootsie Roll
Implementation Profile:
Demantra 7.2.0
Oracle 10g Database
Oracle Release 12 Advanced Supply Chain Planning (ASCP)
The Challenge:
Tootsie Roll needed to replace their manual forecasting process and faced many challenges including forecasting for new products, products with seasonality, and products with intermittent demand – along with integrating Demantra with Oracle’s Release 12 Advanced Supply Chain Planning (ASCP) product. With a very aggressive timeline, Optimum was called upon to implement the solution in 3 months.
The Solution:
Optimum assisted Tootsie Roll with the implementation of the Demantra Demand Management module and integrations with Oracle's EBS R12. Optimum was able to quickly develop a demand management solution utilizing Demantra 7.2.0 on an Oracle 10g database environment which included the integration of Tootsie Roll’s legacy Order Management system into the Demantra application. Optimum’s unique solution allowed for forecast fine-tuning to accommodate seasonal demand patterns, the enabling of exception management via workflow notifications, and the development of training materials and training of marketing managers on Demantra.
Strategic Results:
"Optimum was a wonderful partner for our Demantra implementation,” notes John Majors, Vice President. “They delivered a quality solution for our forecasting and planning needs.”
By leveraging a fully-integrated Demantra solution, Tootsie Roll is now strategically positioned to:
- Improve forecasting and planning accuracy
- Forecast new items and/or customers that have no sales history
- Phase out items and replace with new ones while maintaining demand/shipment history
- Accurately forecast items that exhibit seasonal demand patterns
- Allow for exception management based on current vs prior year demand trends

