Demand & Supply Management: The next generation of forecasting

Transcription

1 Demand & Supply Management: The next generation of forecasting Thought Piece 2018

2 Incorporating Forecasting in Demand & Supply Planning Accuracy in forecas ng has the greatest impact on an organiza on s ability to sa sfy customers and manage resources cost effec vely. It is not simply a projec on of future business; it is a request for product and resources that ul mately impacts almost every business decision that the company makes across sales, finance, produc on management, logis cs, supply chain and marke ng. Today, organiza ons are placing more emphasis on forecas ng in demand and supply planning to ensure op mal inventory levels. In such a fast changing business landscape, it is impera ve for organiza ons to automate demand & supply planning enriched with integrated forecas ng modules. Demand & Supply planning process Figuring robust Demand & Supply planning process is at core of inventory and cash management. A well-defined Demand & Supply planning process can improve forecast accuracy and inventory op miza on which further improves business parameters like: Inventory reduc on Increase in revenue Service level improvement Gross margin improvement Increase in order fill rate Typical Demand & Supply Planning Manual and Cumbersome Demand Planning 1 Step 1: Demand Forecast 2 Step 2: Manual Override Supply Planning 3 Step 3: Promo Conversion Baseline Forecast Consensus Forecast Ingredient wise Forecast makes thumb rule approxima ons based on Last year sales Last 3 month average sales Forecast done for next 3 months Sales team tweaks baseline forecast numbers based on their hunch and experience on Last year sales Upcoming marketing promotions breaks forecast SKU s to orderable SKU s (e.g. Product ABC= 1 unit Product DEF + 2 Units Product XYZ, where Product ABC is forecast SKU and Product DEF & XYZ are orderable SKU s Planning Team 4 Step 4: Supply Forecast Baseline Supply Plan (by ingredient) prepares pallet / box wise order quan es based on Opening stock Goods in Transit Max inventory Lead me of delivery Lot mul plier (convert into pallet / min box orderable qty 5 Step 5: Manual Override Consensus Supply Plan (by ingredient) Sales team tweaks baseline supply plan numbers based on their hunch and experience to meet sales targets 6 Step 6: za on Planning tries to manually op mize available shipping container sizes to fit planned orders Planning Team & Sales Team Tradi onally, demand forecast and supply planning follows a siloed structure, making it difficult to account for all the trade-offs in supply and demand planning. Due to lack of integra on, supply planning tends to be reac ve and lacks the ability to sense, flex, and adapt, exposing the company to demand vola lity. The major issue that holds back companies from improving planning capabili es is their reliance on manual spreadsheet-based processes.

3 Process inefficiencies further decrease accuracy and efficiency of Demand & Supply planning. To be relevant in a business economy shaped by uncertain demand and rapid market changes, a robust Demand & Supply planning process should be developed. It should have freedom to change or alternate between different models as a product moves through its life cycle. A best-in-class forecas ng system is one that provides flexibility for users to weight elements and override key parameters in the forecast calcula on based on their intui ve knowledge and market exper se but at the same me keep tracks of user wise changes. Planning Inefficiencies Thumb Rule Approxima ons Demand forecas ng relies on individual s hunch and not sta s cal forecasts Demand planning decisions are based on basic historical sales metrics Planning accuracy is not monitored Documenta on Difficult to track who / when took forecast decisions and the reason for such decisions Collabora on b/w planning & sales teams is difficult without view on historical data Review of past planning is difficult to track Manual Order Consolida on Manual consolida on of different orders into shipping container is inefficient Manual conversion of promo on products to orderable ingredients leads to errors Importance of R and BI tools in forecasting Demand & Supply StrategyConnect prefers R over SAS or SPSS as it has widest range of algorithms. Using R open source libraries, you have a freedom to move to different models and tweak the model as per your requirement. SAS or SPSS do not provide such flexibility. R provides flexible plo ng and data visualiza on as compared to SAS or SPSS. It cost less to deploy R based forecas ng applica on as there are no so ware license fees. Business Intelligence tools have been proven to increase the accuracy, clarity, and comprehensiveness of data and the meliness of the forecas ng process, to ul mately deliver high-quality forecasts. BI can help to analyze historical trends by product and SKUs. StrategyConnect uses BI tools with embedded metrics to give accurate snapshot of present and historical sales and inventory pa erns. It further helps the organiza on to synchronize demand and supply, an cipate produc on needs, modify or tweak forecast to sa sfy seasonal, regional and customer requirements, and ensure that produc on, warehouse, sales and marke ng team are working with the same informa on.

4 StrategyConnect provides solutions at three levels: 1. Baseline Forecasting (Using R) interface 2. Consensus Management Interface 3. ization Interface Baseline Forecasting (Using R) Interface R based module for forecasting Connected to open source libraries Rest API for backend integration Open Source Forecasting Models Solu on: R based open source forecas ng applica on Impact: Low cost of deployment with no so ware license fees Solu on: Connected to R Libraries Impact: Freedom to change or alternate between mul ple models based on forecas ng accuracy & data source Solu on: Ready API Libraries Impact: Easy integra on with current backend using REST API s StrategyConnect: The right choice to develop your forecasting in demand & Supply Planning StrategyConnect deploys sta s cal tools to build demand forecas ng engine that sits on top ERP to pull and push the relevant data. This has enabled clients to build robust supply forecas ng planning process that further helps them in effec ve order booking and hence, be er cash flow management in the longer run. Our applica on allows business owners to manually override mathema cal forecasts to incorporate on the ground market and compe ve reali es. It leverages user-friendly interfaces for users to perform product related scenario analysis. Consensus Management Interface Data Visualization using BI Version management for changing scenarios Log tracking for increased accountability Lot Multiplier Optimization Solu on: SKU wise hyperlinked visualiza on for historical metrics Impact: Effortless consensus building on demand / supply overrides Solu on: Forecas ng / planning version management Impact: Easy to maintain mul ple scenarios by grouping SKU s Solu on: Log tracking on user id s Impact: Easy to follow user wise changes during manual overrides of demand and supply es mates

5 ization Interface Lot Multiplier to group SKU s by orderable qty Optimization using Monte Carlo simulations PO with ERP backend using Rest API s Lot Multiplier Optimization Solu on: Masters table to maintain SKU wise min order qty (pallet/carton) Impact: Easy finaliza on of final orderable qty(carton/pallet) by SKU Solu on: Master table to maintain available container types Impact: Monte Carlo Carlo simula ons simula ons for most for efficient order consignment Solu on: PO Integra on with ERP Impact: Rest API based integra on to relay SKU wise order data for auto PO crea on in ERP With StrategyConnect, your demand and supply planners can transform what may currently be a mul -month effort into just a few days, with significantly higher accuracy and greater confidence. Contact SHUBHAM YADAV MANAGING PARTNER shubham@ HANINDER PAL SINGH MANAGING PARTNER haninder@ TwoFour54, Rotana Office Complex, Abu Dhabi, UAE