Smart Inventory Planning Optimization Solution Overview Smart Inventory

Smart Inventory Planning & Optimization: Solution Overview

Smart Inventory Planning & Optimization IP&O Platform for NAV: • Demand Planning • Inventory Optimization • Operational Analytics • NAV Integration • Hosted by Amazon (AWS) 2

Demand Planning & Inventory Optimization Workflow Service Level Targets, Inventory Budgets Business Knowledge Statistical Forecasting Collaboration Consensus Forecast Inventory Optimization Smart IP&O Orders, Receipts, Shipments, History NAV Current Safety Stocks and Reorder Point, Order Qty Inventory Levels, Inventory Policy Optimal Forecasts, Safety Stocks, Reorder Point, Order Qty Orders, jobs, transfers 3

Smart IP&O for NAV is Mission Critical for Inventory Planning • NAV generates hundreds of order recommendations, material transfers, and production jobs daily • These suggestions are based on the forecasts, Reorder Point, Order Quantity, and Safety Stock parameters • You must enter these values for MRP to work. Many companies turn to: o One-sized fits all rule of thumb methods o Inaccurate sales/customer forecasts o Reactive, manual planning approaches Infrequently calculated or rule of thumb based planning inputs contribute to excess inventory, poor customer service, and lack of trust in the NAV outputs 4

Rule-of-Thumb leads to Misallocated Inventory Example: Order more when On Hand Inventory < = 2 x’s Lead time Demand: Shortage Order Point 6000 units 4000 units Overstock 2000 units Forecast Actual J F M Item A Stable demand pattern A M J J F M A M J Item B Volatile demand pattern © Smart Software, Inc. 2017, All Rights Reserved 5

Smart IP&O for NAV Integration • No base NAV Object modifications • One click setup in NAV to publish the required web services 6

Software Demo Demand Planning 1. Automatic Forecasting 2. Collaborate and Apply Forecast Overrides 3. Develop Consensus Forecast and return to NAV Inventory Optimization 1. Predictive Metrics – How will my current policy perform? 2. What if Analysis – How will proposed policies perform? 3. Optimize Planning Parameters and return to NAV 7

Summary • Complements NAV – seamless integration • See results in 12 weeks • Fills a major need for organizations that struggle with § § § Proactively shaping inventory to achieve desired metrics Measuring actual service and delivery performance Predicting future inventory costs, orders, and performance Assessing the potential impact of policy changes Understanding how inventory got to where it is today Customers see a 10 -25% reduction in inventory and a 5 -20% increase in service level © Smart Software, Inc. 2018 – Proprietary & Confidential 8

Contact Archer. Point: info@archerpoint. com or www. archerpoint. com Smart Software: www. smartcorp. com 9

Reference Slides 10

What is Intermittent Demand? • Slow-moving, irregular, or sporadic demand • Demand history contains a large percentage of zero values, often 30 percent or more, with non-zero values mixed in randomly • Exceptionally difficult to forecast, common among service parts • Instead of focusing on “per-period” forecasts, find the “Sweet Spot” – the minimum inventory needed to achieve the desired service level. • Traditional Statistical Forecasting Approaches will not hit the sweet spot when intermittent demand is present © Smart Software, Inc. 2017, All Rights Reserved 11

Intermittent Demand leads to Misallocated Inventory Forecasting doesn’t help optimize inventory © Smart Software, Inc. 2016 – Proprietary & Confidential 12

Reactive Policy Misallocates Inventory • • • Planning inputs ignored or manually overridden at time of order Make a change and “Wait and See” If dial is turned too far in one direction, you don’t know it until it is too late You then turn dial in other direction, rinse & repeat Once overridden, inputs remain unchanged for many months Ordering decisions based exclusively on “tribal knowledge” Each planner may have a different approach – many approaches per company There is no way to distill how inventory ended up where it is No way to shape the policy – because no policy exists © Smart Software, Inc. 2017, All Rights Reserved 13

Why Smart IP&O for NAV • Automating business processes is not enough to compete in a data driven world • Winners leverage their data for prescriptive solutions to core business problems. • Smart IP&O provides data driven predictive & prescriptive analytics proven to: Reduce inventory - Improve service levels - Provide Executive visibility and Control over Demand Inventory Planning 14

Smart Inventory Optimization (SIO) • • Predicts metrics and costs associated with current planning parameters Calculates optimal planning parameters based on “total lowest cost” Recommends optimal service levels targets Develop, share, and compare collaborative “what if” scenarios Identify exceptions when chosen policy will yield different metrics and/or costs Auto tracks exceptions between actual ordering and planned ordering Exports min/max, R/Q, Safety Stock to client ERP Role Based Authorizations & Access 15

Smart Operational Analytics (SOA) • Monitor actual state of operations • Measure Supply Chain KPI’s such as service level, fill rate, time to ship • Measure and Compare Supplier Performance • Identify Excess/Shortage/Order Cancellations/Transfers • Analyze inventory levels and metrics over any time frame • Custom Reporting within days • Exports all report in variety of formats 16

Platform functionality • • • Common Data Model Auto Item Classification based on volume and frequency User Roles & Authorizations Job scheduling to manage import/exports Multi-Language NAV Integration System Configurations Custom Groupings Alerts 17

Smart Demand Planner (SDP) • Automatically Forecast Demand • Account for trends, seasonality, intermittency • User Overrides and User Defined Methods • Multi-level Hierarchical Planning • Import Forecasts from external sources • Collaboration & Consensus Planning • Reporting vs. Actuals • Role Based Authorizations & Access 18

Simulate Replenishment: Don’t wait and See Automatically Simulate demand replenishment cycles to stress test existing policy and predict metrics • • Service Level Fill Rates Turns Average Inventory Value Holding Costs Ordering Costs # Orders Is performance/cost acceptable? If not, optimize 19

Smart Operational Analytics (SOA) • • Monitor actual state of operations Measure Supply Chain KPI’s Measure and Compare Supplier Performance Identify Excess/Shortage/Order Cancellations/Transfers Identify Items likely to breach Reorder Points Analyze and trend over any time frame Custom Reporting within days Exports all report in variety of formats 20

Use Probabilistic Modeling to see entire range of possibilities th 50 ile t n e c r Pe me i T d a Le nd a m e D t) s a c e r (fo th 95 ile t n e c r pe 21 © Smart Software, Inc. 2017, All Rights Reserved 21