Advanced Forecasting Analytics

Major US e-tailer of Outdoor Gear and Accessories
Objective: Develop a planning system for a high SKU, high variability, seasonal business with 350,000+ SKUS

    Advanced Forecasting Analytics
  • Help managers develop and refine revenue budgets, inventory budgets
  • Help planners reallocate Open-to-Buy budget during the year to meet sales and inventory goals
  • Help planners to create appropriate forecasts to drive pre-season and in-season replenishments
  • Help buyers manage inventory replenishment dynamically and surgically identifying which items to replenish and which to cut, based on near-real time sales data
    Challenges Faced :
  • 350,000+ SKUs of which 90,000 are new to current season
  • Frequent SKU changes within style, high variation in sales with sudden movements, frequent promotions
  • Client had limited dynamic budgets, vendor had limited, dynamic inventories
  • Limited team to handle large merchandize assortment
  • Inventory not cleared at end of season subject to severe markdowns, may not even be saleable
    Approach :
  • Clean, parse, and tag historical data
  • Develop future/ to-be business process for merchandise planning and buying
  • Design hierarchical forecasting and replenishment planning models
  • Developed and implemented a rapid response replenishment ordering system
  • Deploy models in Oracle Demantra with integration to source and destination systems
    Results :
  • Automated SKU level forecasting for 350,000+ skus
  • Prioritized, exception based merchandize planning
  • Exception based planning for key SKUs and styles, automated planning for the rest of skus based on latest / real-time data
  • New planning process allows Planners and Buyers to maximize GMROI because they have clear access to GMROI projections before taking actions

Business Intelligence

Major Quick Service Restaurant Company in India
Objective: To help the Supply Chain team get real time data driven analytics

    Work Carried Out:
  • Analyse 200+ SKUS and their consumption pattern over 6 years
  • Choose and select a software solution for BI and a system integrator to implement the technology
  • Integrate data across multiple source IT systems
  • Develop standard metrics and embed them in the form of reports for each role and function
    Challenges Faced:
  • SKUs being planned and introduced in IT systems independently without collaboration between SCM, Marketing & Operations, and sometimes SKUs having different names & UOM in each system
  • 5 major warehouses each having different warehouse size and SKU packaging size
  • Client had limited dynamic budgets, vendor had limited, dynamic inventories
  • Large number of suppliers spread across India and some specific to warehouses
  • Archaic reporting tools and data extraction procedures
    Approach:
  • Integrate data from ERP and POS systems to a single repository
  • Clean, parse, and tag supply chain performance data
  • Developed BI reports for each area e.g. supplier dashboards, forecast dashboards, inventory dashboards, etc. with aggregations and drill downs
  • Data synchronized and structured so that end users could create reports and drilldowns on the fly
    Results:
  • Real time performance visibility across entire Supply chain
  • Better negotiation power by using objective supplier performance reports
  • Increased supply chain planning effectiveness and increased accountability
  • Improved forecast accuracy due to regular review and collaboration
  • Higher inventory turns, reduction in excess inventories
  • 45+ different supply chain scenarios were analyzed to fully convince management and the board of the optimal solution
  • The number of European distribution centers was consolidated from 9 to 2
  • ~45% reduction in inventory levels
  • Reduction in annual supply chain costs of ~10-11%

Optimizing Complex Manufacturing Network

Major European Manufacturer of Light Industrial Equipment
Objective: Rationalize European distribution network to reflect latest business conditions and strategy

    Work Carried Out:
  • Understand target customer service levels and historical performance
  • Identify new candidate locations in Europe based on greenfield analysis
  • Develop models that accurately reflect financial, operational, and customer service performance levels of current and proposed networks
  • Analyse various supply chain scenarios and fully convince the board of all considerations that have gone into the development of the new distribution network
    Challenges Faced:
  • With changing products, customer expectations, and business conditions, distribution network needed to be realigned to new business conditions and business strategy
  • Owners of the company were asking management to drive supply chain efficiencies in order to meet shareholder expectations of financial performance
  • Each country office had it�s own country level organization, local warehouse and logistics operations. Country managers fought hard for dedicated local presence in the country to serve their customers
    Approach :
  • Management reports, business forecasts, and transactional data were reconciled at a detailed level across multiple business units and countries with business heads and controllers for each country in EU
  • A Center of gravity optimization was run to determine candidate locations. Inputs from 3PLs was sought to finalize list of candidate locations
  • Detailed mixed integer supply chain optimization model using Llamasoft
  • Scenario and sensitivity analysis were performed
  • Financial modeling of benefits
    Results :
  • Production cost was reduced by 15% and throughput was increased by 10%
  • Company realized the benefits of process improvement initiatives using simulations and incorporated simulation into their six-sigma toolkit

Process Improvement Using Simulation

Major Manufacturer of Ball Bearings for the 2 Wheeler Industry
Objective: Design a new manufacturing layout to reduce production costs by 15% and increases throughput by 10%

    Work Carried Out:
  • Use lean techniques to design an efficient manufacturing process
  • Focus on leveraging existing equipment for manufacturing two-wheeler ball bearings
  • Carry out multiple experiments for various manufacturing flow layouts, equipment settings, configurations, and production policies
    Challenges Faced:
  • Renowned company in bearing industry losing market share to low cost competitors
  • Over-engineered product design leading to high total production costs without adding value to customer
  • Production system is a high velocity line and cannot be take offline, except under exceptional circumstances
    Approach :
  • Conduct brainstorming sessions with design team to come up with proposed manufacturing line layout designs
  • Develop process maps and alternate manufacturing layout and configuration scenarios
  • Use Discrete Event Simulation along with statistical tools for output analysis to evaluate the alternate configurations and perform sensitivity analysis.
  • Conduct analysis of operational and financial benefits
  • Automated forecast accuracy reporting and analysis through dashboards equipped with aggregations and drill-downs
    Results :
  • Streamlined monthly S & OP cycle, now completes within first 2 weeks of month
  • Increased S & OP effectiveness and increased accountability
  • Improved forecast accuracy
  • Lower inventory turns, reduction in excess and obsolete (E & O) inventory exposure

Sales and Operations Planning

Major US Manufacturer of Instruments for Communication Networks
Objective: Develop an integrated sales and operations planning process to develop an integrated enterprise S&OP plan, and knit together 90+ planners and managers at various levels across 3 continents

    Work Carried Out:
  • Establish a single set of shared forecasts and plans across Marketing, Planning, and Finance
  • Establish data integrity and traceability for the entire S & OP process
  • Monitor performance to forecast, analyze affect on supply, and adjust demand between S & OP cycles
  • Enabled planners to respond proactively to supply shortages and excess inventory situations
    Challenges Faced:
  • 6 Business Groups with 18 BUs and 123 Product Families (22,000 sellable items + 2500 packages)
  • Mfg: 6 factories on 4 disjointed ERP systems + 4 Drop Ship CMs
  • Supply: Hundreds of suppliers, tens of thousands of purchased items
  • 90 individuals involved in S & OP across Sales, BUs, Ops, Finance
  • All main products are primarily Assemble / Configure-To-Order (ATO/CTO), with CTO parts nested in the BOM
  • Volumes vary widely month to month at the SKU level
    Approach:
  • Integrate data from 4 enterprise information systems (OneVoice, EBS, ICON, OBIEE)
  • Clean, parse, and tag historical data
  • Implemented statistical forecasting models to enable multi-product, multi-country forecasting