Case Study: Blue Ridge Area Food Bank





non-profit food distribution

distributes food and other donated grocery items to nonprofit agencies in western and central Virginia

business challenge

to determine if their supply chain operation is strategically positioned to effectively and efficiently serve the future needs of Partner Agencies and Sponsored Programs



BRAFB and Competitive Insights Project Team members worked very closely together throughout this effort. Competitive insight's step-by-step solution approach was thorough and fact-based driven. It clearly facilitated internal consensus of the results.
Ron Morris • COO • Blue Ridge Area Food Bank


solution

operational assessment & strategic capacity analysis

descriptive • diagnostic • prescriptive analytics
supply chain • finance

data assurance • operational baselining • cost to serve • inventory • transportation • multiple scenarios network optimization




  • mapping

    operational data to major work flows for all facilities



  • gaining

    consensus on each component of operating cost/facility



  • providing

    visibility to inventory turns by product category and the impact on facility capacities

  • establishing

    insights on future facility & transportation requirements



  • proposing

    potential network alignment strategies to meet future Partner Agency and Program requirements






The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Case Study: Under Armour





sporting apparel($4 billion revenue)

supplier of performance apparel - gear engineered to keep athletes cool, dry and light

business challenge

to gain greater detailed performance insights for profit improvement opportunities



The actionable performance insights they provide through their cloud-based application CI.RADAaR™ is game changing. It will be the basis for how innovative companies compete in the future.
James H. Hardy • Former EVP, Global Operations • Under Armour


solution

profit performance analysis

descriptive • diagnostic analytics
supply chain • finance • sales

data governance • cross-functional agreement on detailed performance information




  • insights

    into profitability of each product to the product variation level



  • insights

    for auto replenishment planning from Style Profitability Performance



  • identifying

    unexpected profit performance in product lifecycles



  • internal benchmarking

    of customer financial contributions against "like" customers




The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Case Study: Auto Parts Distributor & Retailer





















industry

auto parts distributor and retailer

($2 billion revenue)

business challenge

to gain financial visibility into SKU performance from multiple operating and financial systems and identify opportunities to improve profitability






solution

product & channel analysis

descriptive • diagnostic analytics
supply chain • finance

data governance • organize and tie together data by each supply chain component • analyze profitability of each SKU

  • explored

    SKU specific visibility into financial performance for every Channel Customer & Stores (costs & profits)



  • addressed

    opportunities to improve operational data that would positively impact ongoing management



  • identified

    specific product segmentation insights regarding profitability



  • utilized

    inventory diagnostics to identify working capital reduction opportunities




The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Case Study: ConAgra Foods

food processing($18 billion revenue)

makes and sells packaged foods available in supermarkets, restaurants & food service

business challenge

to identify the more efficient network design in order to consolidate 14 separate networks



We were very pleased with the deliverables for this project. The results were not just theoretical but grounded on the real needs of the business.
Stephen Tibey • Senior Vice President , Integrated Logistics • ConAgra


solution

network optimization

descriptive • prescriptive analytics
supply chain • finance • sales

data governance • model actual costs associated with each component of the product flows and running the Distribution Centers




  • 7 digit

    savings was identified with consolidated network



  • improved

    servicing customers with regional insights



  • insight

    to specific regional strategies




The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Case Study: Hershey Company







food processing($7 billion revenue)

chocolate manufacturer

business challenge

to determine best product mix by production line and to support projected future growth



As Hershey pursues a strategy to go more global, there were some assumptions about how the supply chain worked and what the right decision would be that needed to go through the filter of objective analysis.
Greg Kaiser • Vice President, Global Logistics and Customer Service • Hershey Company


solution

network optimization

descriptive • prescriptive analytics
supply chain • finance

data governance • model extremely complex operations from manufacturing through customer deliveries




  • $3 million

    savings opportunities by changing product mix



  • 5%

    capacity gain opportunity identified



  • identified

    methods to handle increased demand




The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Case Study: Fresh Food Distribution





















industry

fresh food distributor

($2 billion revenue)

business challenge

to identify the primary factors that were driving costs to climb and margins to erode






solution

product analysis

descriptive • diagnostic analytics
supply chain • finance • sales

data governance • organize and tie together data by each supply chain component • analyze profitability of each SKU

  • reduced

    costs by re-architect Customer Delivery routes



  • explored

    conversion of some Free-On-Board (FOB) Inbound Transportation to managed transportation



  • addressed

    negative margin position of specific SKUs



  • identified

    supply chain-related Data Quality issues




The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Case Study: Monsanto

agribusiness ($15 billion revenue)

producer of genetically engineered seed and herbicide

business challenge

to improve alignment among the brands by either increasing utilization of existing distribution capabilities or developing new go-to-market strategies




The business insights that we obtained from CI’s approach in solving this problem were outstanding. They were able to take a very complex situation and bring clarity to our operational options.
Scott Dantuono • Distribution Manager • Monsanto


solution

network optimization

descriptive • diagnostic • prescriptive analytics
supply chain • finance • sales • marketing

data governance • model extremely complex operations from manufacturing through customer deliveries



  • reduced costs

    of inter-facility transportation with better product positioning



  • reduced storage costs

    with better facilities utilization



  • decreased

    operational complexity




The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Case Study: Non-Metallic Mineral Manufacturing





















industry

nonmetallic mineral manufacturing

($500 million revenue)

business challenge

to identify near term, specific opportunities to reduce transportation costs






solution

transportation analysis

descriptive • diagnostic • predictive analytics
supply chain • finance • sales

data governance • segmented analysis into inbound, inter-facility and outbound to dive deep into transportation costs for savings opportunities

  • $2 million

    savings opportunity identified from low cost carrier selection



  • $1.3 million

    savings opportunity identified from carrier consolidation



  • $2.1 million

    savings opportunity identified from applying discount to high volume lanes



  • $400 thousand

    savings opportunity identified from shipping directly from plant instead of going through a Distribution Center




The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Case Study: Hospira





pharmaceuticals($5 billion revenue)

provider of injectable drugs and infusion technologies

business challenge

to gain greater detailed performance insights into the operating network to determine if there is a better approach for servicing customers




I continue to be impressed by the system.
John Elliot • Senior Vice President of Operations • Hospira


solution

network optimization &
performance analysis

\ descriptive • diagnostic • prescriptive analytics
supply chain • finance • sales

data governance • cross-functional agreement on detailed performance information • tracking ongoing performance




  • $20 million

    savings opportunity identified



  • insights

    for SKU-level strategies



  • data refreshing

    revelaed profit opportunities that can be tracked



  • cross-functional

    use of profit insights




The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.

Case Study: Darden Restaurants



food services($6 billion revenue)

operating multi-brand casual dining restaurant chains

business challenge

to identify the best strategies for Resource Allocation to position people and money in order to enable the supply chain to most effectively respond to risk 

solution

supply chain risk analysis

descriptive • diagnostic • prescriptive analytics
supply chain • finance • sales

identify areas of supply chain risk • develop mitigation strategies to minimize financial impact from supply chain disruptions



  • created

    a common language and supply chain platform around risk



  • established

    organizational focus on critical vulnerabilities



  • connected

    implications of global forces to supply chain execution, vulnerability, guest and shareholder value



  • devised

    mitigation strategies to minimize exposure to vulnerability




The results illustrated in this case study are specific to the particular situations, business models, data input, and computing environments described herein. Each Competitive Insights (CI) customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. CI does not guarantee or represent that every customer will achieve similar results.