Through the 2012 merger between Brazil’s top two food companies, Sadia and Perdigão, and continued business growth, BRF (formerly Brasil Foods) has emerged as the world’s seventh largest food company and number one in its home market of Brazil.
The leader in meats, grains and convenience food, BRF’s product innovation generated revenues of $15 billion with 2,000 SKUs and 10 distribution channels across 110 countries.
Exciting new products and vast international growth brought significant business complexity to BRF, including a global list of more than 200 million prices for its 155 branches. Given this complexity, the time to complete price changes grew to exceed two weeks.
Adding to BRF’s pricing challenges was an increased urgency to sell products as their expiration dates approached and their values consequently dropped.
Fortunately, BRF’s pricing team had experience, established processes and ample access to a broad range of data from SAP. However, the team relied on aging analytical systems that lacked the flexibility and features to keep pace with a dynamic market.
BRF was in need of a fresh approach to pricing and a price optimization solution that could help drive the next wave of business growth.
Since the 2012 merger, BRF’s pricing systems had increased to 10 homegrown solutions, each with unique algorithms. Master data resided in SAP, but pricing analysis was commonly performed in spreadsheets.
While data accessibly and quality were sufficient, extracting useful knowledge from the volumes of information available was a monumental challenge for BRF’s pricing team. This left too many unanswered questions:
- Are discounts effectively correlated to product age?
- How well do retail customers price products?
- Do prices reflect brand position and channel?
- Which customers are meeting volume goals?
- Most important to BRF’s senior managers, how can the company significantly reduce the time to change prices and embrace a new culture of business agility?
Was there one solution that could address all of these unanswered questions? The time had come to conduct an extensive search and transition from BRF’s aging systems to a new price optimization solution that would meet the needs of its complex food manufacturing and go-to-market framework.
Because of the project’s importance, BRF sought best-in-class advice from industry peers, analysts and solution vendors across the globe.
After dozens of inquiries and interviews to gain knowledge and narrow down the field, PROS was shortlisted as a technology partner to replace existing systems. After completing a successful proof of concept using six months of sales data, BRF implemented PROS Scientific Analytics. BRF’s pricing team then started receiving valuable knowledge that was previously too complex to parse from SAP and too large to analyze in spreadsheets.
The abundance of insights BRF received from the price structure optimization analysis alone was immense. With this data, the company gained the ability to vastly reduce manual price inputs.
With PROS Scientific Analytics, BRF increased the speed, accuracy and automation of pricing analysis with a single source of truth underlying these calculations.
After applying the four reports received from the proof of concept across all products sold in Brazil, BRF has achieved:
- Lower Operating Expenses: freed 98% of IT capacity for 5 million unique price requests made daily
- Increased Margins: ability to set discount maximums according to product age
- Improved Agility: price cycles completed 70% faster
- Forecast Accuracy: effortless comparisons of pricing plans to actual sales Furthermore, BRF is now able to quickly and accurately provide critical business analysis to product marketing and sales teams around the company.
It didn’t take long for the business impact of PROS Scientific Analytics to pique the interest of the leaders of other BRF divisions. It was becoming very clear that BRF was realizing more than pricing efficiency; the company was gaining valuable business knowledge to improve business outcomes with its increased pricing agility.
While implementing PROS solutions was originally envisioned as a pricing project, the intelligence gained made management start seeing it as something with a more far-reaching business impact. This was the implication when the pricing team received full support to expand the scope of the original deployment.
Other expected gains from the PROS Scientific Analytics deployment include:
- Aligning prices with brand positioning and channel placement
- Measuring return on investment from new advertisements
- Tracking retailer markup and price elasticity
- Margin visibility that includes investments, costs and discounts
As a result of the new price optimization solution, BRF is able to make better and faster business decisions from powerful reports and research.
In just a short time, BRF addressed a range of limitations within an extremely important business function in the food industry — pricing. The results are already positively impacting its bottom line.