Finding & Testing SIMPLE Solutions for COMPLEX Problems

Finding & Testing SIMPLE Solutions for COMPLEX Problems
CASE STUDY 1 Helping achieve “One-Simple-ABB” with “TOC in SAP” within Complex Manufacturing Environment CASE STUDY 2 Finding & Testing a solution to SHORTAGES & SURPLUSES within Book Publishing Supply Chain Presenter: Dr Alan Barnard, CEO Goldratt Research Labs Date: 27th August

Case Study 1 Helping Achieve “One-Simple-ABB” with TOC in SAP
Presenter: Dr Alan Barnard, CEO Goldratt Research Labs Contributors: Dr Katja Rajaniemi, Improvement Manager ABB BU Fredrik Nordstrom, Regional Manager ABB Ops Development Group Lukasz Krupa, Leader, ABB Manufacturing IS Solutions Alex D’ ’Anci, Regional Manager, ABB Ops Development Group Eli Schragenheim, Goldratt Schools

Presentation Outline Research Background ABB Case Study:
Facts about ABB ABB’s Continuous Improvement Evolution at ROI The “One-Simple-ABB” Challenge for Operations Excellence Conflict in leveraging and standardizing on best practices across ABB Conflict in leveraging and standardizing on a single IT Platform and ERP system Finding a Solution to the “One-simple-ABB” Challenge Defining a simple yet robust TOC solution for 300+ different factories Defining “TOC in SAP” using Goldratt’s “Strategy and Tactic” (S&T) process Testing “TOC in SAP” solution through series of Pilots Results achieved to date & next steps Research Conclusions

Research Background RESEARCH PROBLEM
Most companies today, have left the final choice of which which Planning, Execution and Continuous improvement (PECI) methods and which IT systems to support these to Business Units because BUs are: Responsible for continuously improving on their result. In the best position to decide which methods & systems best meet their specific requirements. Normally responsible for pay for these. No wonder BU’s have resisted most attempts to standardize or centralize IT and PECI’s …

Research Background RESEARCH PROBLEM
However, not standardizing and leveraging Best Practices and a common IT platform, has major negatives for the Company as a whole… Providing Support to multiple IT platforms and different Improvement methods is a nightmare for Centralized functions and very costly Ensuring fast and reliable integration of data between different systems is a major challenge and occupies valuable management time every month Business Processes cannot be standardized to enable fast and accurate transactions. Best Practices are not shared and results achieved are not duplicated

Research Background RESEARCH QUESTIONS
Q1: Is it possible to find a "one-solution-fits-all" both in rules and ERP technology when it comes to planning, execution and improvement of operations especially considering the many specific local considerations resulting in "we are different”)? Q2. Even if it was possible to theoretically find such a solution that could meet most business requirements, would it be possible to get buy-in from regional and plant managers under pressure to improve performance & reduce costs to test such a solution?

Research Background RESEARCH METHOD
Literature Review to identify which companies have tried and succeeded and which not and Why? Consultation with Experts to determine if a “One-Solution-fits-all” solution design was possible and then whether such a solution can be implemented within a standard ERP System (the hypothesis to be tested) Followed Action Research method using “Plan, Do, Review & Act” cycles to validate and continuously improve hypothesis

Case Study: Facts about ABB
Power Products Power Systems Automation Products Process Automation Robotics ABB is the world’s leading provider of power and automation technologies with strong market positions in core businesses ABB’s goal is to create value for their stakeholders by helping customers Use Electrical Power more Efficiently, Increase Industrial Productivity, Lower Environmental impact in a sustainable way Revenues in 2007: $29.2 billion and Orders for $34.3 b (large backlog) Headquarters: Zurich, Switzerland About 107,000 employees in 100 countries with Market-leading positions in most key products Robust global value chain to serve established and emerging markets 300+ factories around the world

Why Operational Excellence is critical to ABB…
4 Competitors also have aggressive operational excellence programs Competitors Customers Sub Sub Suppliers 3 Supply Partners expect Better visibility (and prices) for Improved reliability and response Revenues COPQ EBIT 2 Shareholders expect Increase EBIT (growth) Reduce COPQ (stability) P T 1 Customers expect more for less faster each year

ABB’s Continuous Improvement Evolution
Number of factories using TOC By 2008 ~100 Trained in “Advanced TOC” ~500 in TOC through OEP 2007 TOC in SAP 2008 OEP for Controllers 2005 Test TOC Distribution Solution 2007 OEP for IS 1998 Corp R&D Program for Manufacturing Technologies 1992 Production Technology Organization part of Corp. R&D in Finland 2006 MT R&D Program becomes Operations Development Group. 50 consultants in 4 centers 2001 Eli Goldratt visits ABB 1999 12 Jonahs trained 2003 Operational Excellence Program (OEP) launched as CP3 1993 first DBR implementation 2002 ConWIP 1988 2010 TOC + Lean Thinking + OEP = Operational Excellence

Was the investment in Operational Excellence worth it for ABB?
A study of ABB’s Operations Improvement projects (TOC+LEAN) confirm an average payback time of less than 3 months ! 1) Source: Copenhagen Institute for Futures Studies and Larry Keeley: (3000 projects examined)

Sample TOC & Lean success stories in ABB (1/2)
Distribution Transformers production unit 2005 TPT (Line1) - 75% TPT (Line2) - 65% TPT > - 50% Delivery time > - 25% Total inventory reduction 1,2 MUSD while 40% volume increase LV Motors manufacturing unit Productivity +38% TPT -17% Tap Changer manufacturing unit TPT % Delivery time > - 60% HV Bushings manufacturing unit Capacity +30% TPT - 50% OTD from 8 to 93% Value chain from a component factory in Europe to a product factory in Asia Replenishment time % Total inventory turns % On Time Delivery from 83 to % Technology Development Centre Project OTD from 45 to 87% with significantly reduced cycle time Functional Completion Rate incr. to 100% Cables manufacturing unit 2004 TPT - 80% WIP - 60% TPT - 70% Delivery time - 48% OTD from 70 to 96% while 245% increase in orders received HV Switchgear Capacity +43%

Sample TOC & Lean success stories in ABB (2/2)
Power Transformers production unit 2007 WIP and LT - 40% OTD (On Time Delivery) from 86 to 100% Capacity % without planned expansion Distribution Transformers production unit WIP - 45% TPT - 70% OTD from 45% to 98% Distribution protection and control products manufacturing unit Delivery time % OTD from 40 to 100% Capacity % with existing resources MCB production unit Delivery time - 50% for stock and non-stock items OTD from 84% to 97% 2006 Productivity +30% Delivery time - 50% (from 6 to 3 months) WIP % Capacity +30% TPT - 64% Delivery time - 32% Inventories - 44% OTD from 66 to 98% MV Circuit Breakers manufacturing unit Capacity +260% TPT - 60% Delivery time - 60% OTD from 77 to 100% LV Breakers and Switches production unit Capacity +25% Delivery time - 80% OTD from 23 to 90%

Sanmina-SCI Case Study
What is the benefit of using TOC as a focusing tool for LEAN & Six Sigma vs. using each in isolation? Sanmina-SCI Case Study Leading global electronics manufacturing services (EMS) company employing over 48,000 people and revenue of $11.7 Billion Set-up experiment over 2.5 years to test financial impact of LEAN, Six Sigma and TLS (TOC focusing LEAN & 6S) 21 Participating plants with: 11 Plants on Six Sigma 4 Plants on Lean Plants on TLS TLS, Lean, and Six Sigma all offered benefits TLS showed times greater financial benefit delivering 89% of total benefits achieved from only 6 out of 21 plants Source: Apics Magazine, May 2006 and TOCICO 2007 presentation by Dr Russ Pirasteh, Sanmina-SCI,

= Standardize, Do, Check, Act
But how do you achieve Step-Change AND Continuous Improvement within any organization? S D C A = Standardize, Do, Check, Act Continuous (Evolutionary) Improvement through institutionalizing Best Practices P D C A = Plan, Do, Check, Act Step-Change (Revolutionary) Improvement through Constraint Focused interventions (Kaizen) Source: ‘Kaizen: The Key to Japan’s Competitive Success’, by Masaaki Imai

Operational Excellence Acceleration Challenge
What blocks a company such as ABB from identifying and spreading best-practices, learnings and results effectively in a big organization? The “Best Practice” Standardization Dilemma Need Have a way to Roll -out best-practices efficiently & effectively Action Standardize our improvement approach Each BU/Factories is different which mean there are no “one-solution-fits-all” that can be rolled out Because: Conflict Objective Ensure leverage of Best-Practices in all Business units Need Have a way to ensure out- standing result in each BU Action Customize an improvement approach for each business unit Really?

Operational Excellence Acceleration Challenge
Despite the many differences between the plants where TOC+LEAN were implemented, it seemed to deliver similar results without any significant differences in the “what” and “how to”… Resolving the Standardization Dilemma: Need Roll-out best practices effectively Action Standardize our improvement approach Direction of solution: Use TOC to focus & synchronize Planning, Execution & Cont. Improvement solution (TOC + LEAN) and an participative engagement approach for getting contribution and consensus Objective Ensure leverage of Best-Practices in all units Need Ensure out- standing result in each unit Action Develop approach with target unit personnel each time

ABB Gate Model for Process Improvement projects of Best Practices using a holistic TOC approach
…. addressing resistance to change as an organizational constraint: Project scope definition Execution Plan Final solution agreement Hand - over Pilot results Close project Validate Start Agreement 2 3 4 5 1 6 7 Development Piloting Implementation Analysis Planning Sustain 6. Agreement by all collaborators including management that we can move forward with confidence 4. Agreement that no disastrous side effects will result 5. Agreement on the implementation requirements and the plan itself 3. Agreement that the solution will yield the desired results 2. Agreement on the direction of the solution 1. Agreement on the problem But how do a standardize “Best Practices” without standardizing the IT Platform? Source: ABB developed (based on Cooper´s Stage-gate model).

ABB’s ERP System reality after years of acquisitions and empowered BU and Regional IT decision making.. As a result of numerous acquisitions, ABB at one time had more than 500 ERP systems and 70 different ERP brands in operation across its businesses. Most of the factories and distribution centres were also using in-house developed Spreadsheets and Databases for supporting their preferred Planning, Execution and Continuous Improvement Methods Integration of systems and data (and support) had become a nightmare and major risk to the business. In late 2006, a decision was made at the ABB board, to embark on a (challenging) journey of standardization on a common IT / ERP Platform (or at least range of platforms) and simplification based on “best-practices”. The initiative was titled “One-simple-ABB” or “OsA”.

ABB’s “One-simple-ABB” decision and consequences...
Press Release in March 2007 “Today, ABB signed a strategic agreement with the German-based ERP provider, SAP to help deploy common SAP ERP software through its global operations to help unify and simplify some of ABB’s most important business processes. The OsA initial target is one ERP per country, and ultimately one ERP platform per region for all of ABB that would enable a high degree of standardization in the human resources, finance and administration and corporate governance functions as well as in the operational excellence “best-practices” Yes, BUT.... Would it really be possible to find and get agreement that a “One-simple-ABB” solution was possible for managing the diversity and complexity of ABB’s 300+ factories?

The Operations dilemma in supporting ABB’s global “One-Simple-ABB” objective?
The “One-Simple-ABB” Dilemma Need Efficient and fully integrated Finance, HR & OPS business processes across ABB Action Deploy a common ERP platform across ABB and limit selection of SCM & MES systems Each BU/Factory is unique and using a common ERP platform or limiting choices in SCM / MES methods & systems will jeopardize results and or ownership Because: Objective Create long term competitive edge in our industry Need Continuously Improve customer service and sales through efficient & effective operations Action Allow each site to develop own / use 3rd party ERP, SCM & MES systems Not updating ERP ERP inaccurate Don’t trust ERP Use Legacy / 3rd Party Viscious Cycle of D’: IF 3rd Party or Off-line systems are used for planning & Execution mgt and these are not integrated with ERP and operations people are time constrained, THEN it means ERP is not always (and in some cases never) updated which means ERP data is inaccurate causing people to distrust ERP system giving more justification for using 3rd Party or in-house developed spreadsheets & databases

The Operations dilemma in supporting ABB’s global “One-Simple-ABB” objective?
The “One-Simple-ABB” Solution for Operations Need Efficient and fully integrated Finance, HR & OPS business processes across ABB Direction of win-win solution: Get agreement that TOC can provide “one-solution-fits-all” Find a way to Modify SAP R3 to support TOC (TOC Planning, Execution & POOGI rules). ABB to launch a “TOC in SAP” initiative to validate above hypothesis Objective Create long term competitive edge in our industry Need Action Continuously Improve customer service and sales through efficient & effective operations Yes, BUT… Q1: Would it really be possible to define a TOC “One-solution-fits-all”? Q2: Would it really be possible to modify SAP to support this solution?

“TOC in SAP” Project at ABB Getting Agreement & testing TOC Solution Design & SAP functionality
Project Start “TOC in SAP” Intro W/Shop In Zurich SAP Development & Test Collaboration of ABB, TOC & SAP Experts TOC Solution Validation & Pilot Selection Web-call with Dr. Eli Goldratt Roll-out & Validation Cont. To validate robustness & results TOC Solution Design “Go-Live” At Pilot Site In Brno SAP Blueprint Experts convert Solution Design into Functional Reqs W/Shops In Brno to specify the solution W/Shop in Krakow reviews ABB diversity Jan 2007 March 2007 Jun 2007 Aug 2007 Oct 2007 Nov 2007 Ongoing So, what was the process we used to find and test a “SIMPLE & ROBUST” solution... ...introducing Goldratt’s Strategy & Tactic Tree

Finding a simple & robust SCM solution for ABB that is generic enough to be used by all factories
Using Goldratt’s Strategy & Tactic tree method to find a simple & robust Planning, Execution & Cont. Improvement solution… 1 ABB Goal: Profitable Growth 2.1 Reliability/Availability Competitive Edge 2.2 Rapid Response Competitive Edge 3.1.1 Remarkable Due Date Perf & Availability 3.1.2 Selling Reliability/Availability Selling as Comp. Edge 3.1.3 Coping with Sales Growth 3.2.1 Remarkable Rapid Response 3.2.2 Protective Capacity for RR orders 3.2.3 Selling Rapid Response as Comp. Edge 3.2.4 Expanding RR Client Base “The best solutions start with the right questions…”

1 ABB Goal: Profitable Growth 2.1 Reliability/Availability Competitive Edge 2.2 Rapid Response Competitive Edge 3.1.1 Remarkable Due Date Perf & Availability 3.1.2 Selling Reliability/Availability Selling as Comp. Edge 3.1.3 Coping with Sales Growth 3.2.1 Remarkable Rapid Response 3.2.2 Protective Capacity for RR orders 3.2.3 Selling Rapid Response as Comp. Edge 3.2.4 Expanding RR Client Base Other “Hidden” Disruptions to Flow Potential Performance What really causes low Tput, poor DDP / Availability & Long LT? Unsynchronized Priorities in Operations Releasing Too much / Too early Materials / Purchased Parts not available Over- / Under-committing Capacity Current Performance

1 ABB Goal: Profitable Growth 2.1 Reliability/Availability Competitive Edge 2.2 Rapid Response Competitive Edge 3.1.1 Remarkable Due Date Perf & Availability 3.1.2 Selling Reliability/Availability Selling as Comp. Edge 3.1.3 Coping with Sales Growth 3.2.1 Remarkable Rapid Response 3.2.2 Protective Capacity for RR orders 3.2.3 Selling Rapid Response as Comp. Edge 3.2.4 Expanding RR Client Base Sales How to QUOTE reliable due dates with internal Constraint? i.e. Not over-/under-commit Procurement How do we maintain High RM Availability with Low Inventory? Planning How do we control release of ETO, MTO & MTS WO’s for Low WIP/high CCR utilization? Execution How do we maintain right priority of ALL WO’s on shop floor? Ongoing Improvement How do we continuously Improve flow by identifying & removing local optima & other “hidden” disruptions/ CCRs to improve flow?

1 ABB Goal: Profitable Growth 2.1 Reliability/Availability Competitive Edge 2.2 Rapid Response Competitive Edge 3.1.1 Remarkable Due Date Perf & Availability 3.1.2 Selling Reliability/Availability Selling as Comp. Edge 3.1.3 Coping with Sales Growth 3.2.1 Remarkable Rapid Response 3.2.2 Protective Capacity for RR orders 3.2.3 Selling Rapid Response as Comp. Edge 3.2.4 Expanding RR Client Base (Sales) TOC’s PLANNED LOAD (PL) for Quoting Safe Due Dates (Buying) TOC’s DYNAMIC BUFFER MGT (DBM) & TOC Replenishment (TOCR) for Inventory Mgt (Planning) TOC’s RELEASE CONTRO (S-DBR) to control WIP and improve Flow (Execution) TOC’s SINGLE PRIORITY SYSTEM Buffer Mgt (BM) to keep priorities synchronized (Improve) TOC’s BUFFER ANALYSIS to Focus Process Improvements & Capacity Elevation

Defining, communicating & validating the proposed ERP changes using S&T structure
1 ABB Goal: Profitable Growth TOC’s PLANNED LOAD DETAILS Why is the change needed? Necessary Assumption What is the objective of the change? Strategy Why will the change achieve the objective? Parallel Assumptions How will the change be implemented? Tactic 4.11.1 Quoting Safe Due Dates using CCR(s) Planned Load 2.1 Reliability/Availability Competitive Edge When Sales/Planning accept an order due date which the factory cannot achieve, it jeopardize ABB’s Reliability CE. Even if the constraint is in the market, fluctuations in demand or supply can cause specific resources (CCRs) to be overloaded. Under such circumstances, quoting fixed lead times is very likely to result in missed due dates resulting in poor DDP. Due-dates given by the sales force/planning are (almost) always met even during periods of capacity overloads (Target: 99% DDP) 3.1.1 Remarkable Due Date Perf & Availability It is relatively easy to meet all due-dates when the commitments are given based on actual planned loads on the CCR(s) and S-DBR and BM are in place to control release & align priorities. The ERP systems can be modified to provide (within mins) a safe due date based on CCR(s) planned load + ½ Production Time Buffer (if CCR is about in middle of flow) (Sales) TOC’s PLANNED LOAD (PL) for Quoting Safe Due Dates Safe Due-date are given according to first available slot on CCR(s) + ½ Production Time Buffer The ERP system is modified to provide Safe Due Date based on CCR Planned Load + ½ PTB within minutes and Sales/Planning is trained to use it.

Supply Time Buffer (STB)
4.11.1 Quoting Safe Orders Due Dates using CCR(s) Planned Load Tactic 1. Safe Due-date are given according to first available slot on CCR(s) + ½ Production Time Buffer CCR Back Orders Overdue Material Order Date Material Release Date Safe Due Date Supply Time Buffer (STB) ½ PTB ½ PTB Production Time Buffer (PTB) Quote this “safe” due date to customer WO #112 WO #132 WO #114 WO #111 WO #131 WO #15 WO #116 WO #117 WO #120 WO #118 WO #119 WO #122 WO #123 WO #113 WO #124 WO #125 WO #126 WO #127 WO #128 WO #130 WO #129 WO #133 WO #134 WO #135 WO #136 WO #137 WO #138 WO #139 WO #140 WO #141 WO #142 MAINTENANCE PLANNED NEW ORDER Total Load in Time on CCR

Identify Next Avail slot on CCR
4.11.1 Quoting Safe Orders Due Dates using CCR(s) Planned Load Tactic 2. The ERP system is modified to provide Safe Due Date based on CCR Planned Load + ½ PTB within minutes and Sales/Planning is trained to use it. Identify CCR Overload Identify Next Avail slot on CCR

Defining, communicating & validating the proposed ERP change using S&T structure
1 ABB Goal: Profitable Growth TOC REPLENISMENT & DBM DETAILS Why is the change needed? Necessary Assumption What is the objective of the change? Strategy Why will the change achieve the objective? Parallel Assumptions How will the change be implemented? Tactic 4.11.2 Maintaining Optimum RM & PP Inventory Levels 2.1 Reliability/Availability Competitive Edge Having too much Raw Material (RM) and or Purchased Parts (PP) in the stores or ordering too early can easily drain the company’s cash /WH space. Having too little RM, PP can and most frequently do cause delays that can cause lost production and potentially missed due dates (jeopardizing building of a “Reliability” Comp. Edge) . The target levels of RM & PP inventories held are continuously monitored and when needed are suitably modified (not too much/too little) 3.1.1 Remarkable Due Date Perf & Availability TOC;s Dynamic Buffer Management & Replenishment of RM & PP Inventory, is a robust mechanism that enables setting, replenishing & adjustment of inventory targets, according to the actual level of demand & supply ensuring low levels of inventory& high availability. Most ERP systems do not provide a mechanism for auto resizing inventory target levels based on actual changes in demand/supply (Buying) TOC’s DYNAMIC BUFFER MGT (DBM) & TOC Replenishment (TOCR) for Inv Mgt Target Levels are sized based on Max Demand within Reliable Replenishment time (Rt=OLT + SLT) Inventory levels are maintained by replenishing on actual consumption & resizing on buffer penetration The ERP system is modified to enable DBM & TOCR functionality

TOC Replenishment & Dynamic Buffer Management Rules
4.11.2 Maintaining Optimum RM & PP Inventory Levels with DBM / TOCR Tactic Target Levels are sized based on Max Demand within Reliable Replenishment time (Rt=OLT + SLT) Inventory levels maintained by replenishing on actual consumption & resizing on buffer penetration TOC Replenishment & Dynamic Buffer Management Rules What are the New TOC Planning, Execution & Feedback Rules… Stock in Pipeline Stock on Hand TOC Planning Rule: Size Buffer Target Level based on “Peak Demand within Reliable Replenishment Time” TOC Execution Rule: Order daily & Replenish up to Target Level frequently (e.g. daily) on actual demand TOC Feedback Rule: Re-size buffers based on red-zone penetration Auto Up-size Buffer based on level of Red-zone penetration Auto Down-size Buffer based on no Yellow Zone penetration 400 300 200 100 Actual Demand Month 1 Month 2 Month 3

4.11.2 Maintaining Optimum RM & PP Inventory Levels with DBM / TOCR
Tactic The ERP system is modified to enable DBM & TOCR functionality SAP TOC DBM & Repl. GUI 2. Graph showing resizing of Stock Buffers TOC DBM & Replenishment 3. List of Buffers requiring Resizing (proposals to purchaser, not automated until validated)

1 ABB Goal: Profitable Growth TOC RELEASE CONTOL (S-DBR) DETAILS Why is the change needed? Necessary Assumption What is the objective of the change? Strategy Why will the change achieve the objective? Parallel Assumptions How will the change be implemented? Tactic 4.11.3 TOC Release Control to prevent Over-production 2.1 Reliability/Availability Competitive Edge Having too many orders on the shop floor masks priorities, promotes local optima behavior and therefore prolongs the lead-time and significantly disrupts due-date-performance (DDP). Having too little orders on the shop floor will cause starvation of CCRs and cause lost production and potentially missed due dates (jeopardizing building of a “Reliability” Comp. Edge) . The shop floor is populated ONLY with orders that have to be filled within a predefined horizon. 3.1.1 Remarkable Due Date Perf & Availability In traditionally run plants touch time is a very small fraction (<10%) of the lead time. Vast experience shows that, in traditionally run plants, restricting the release of materials, to be just half the current lead time before the corresponding due date, leads only to good results and to no negative ramifications* (lead time shrinks to less than half, DDP improves considerably, throughput goes up and excess capacity is revealed). These results are achieved irrespective of whether or not a bottleneck exists. * Except for environments which are dominated by heavily dependent set-up matrixes. Those environments have to be dealt in a different way. (Planning) TOC’s RELEASE CONTROL (S-DBR) to control WIP and improve T, DDP & LT For each group of products currently having similar lead times, a buffer time is set to be equal to 50% of the current avg lead-time. Orders are released to the floor only a buffer time before their committed due-date, and if all materials are available. (WIP frozen until its time arrives). The ERP system usage is modified to support S-DBR release control and automatic material availability check.

S-DBR Planning (Release Control) Solution
4.11.3 Controlling the Release in Manufacturing (MTO/ATO) Tactic Target Levels are sized based on Max Demand within Reliable Replenishment time (Rt=OLT + SLT) Inventory levels maintained by replenishing on actual consumption & resizing on buffer penetration S-DBR Planning (Release Control) Solution Shipping Buffer for MTO GREEN ZONE RED ZONE YELLOW ZONE 1. Raw Materials for Stock Manuf Parts Release based on “Replenish Frequently on Actual Consumption Shipping Buffer for ATO 2. Raw Material for Non-Stock Manuf Parts Release = DD – MTO Shipping Buffer GREEN ZONE RED ZONE YELLOW ZONE Manuf Parts Release Date = Due Date – ATO Shipping Buffer RAW MATRL RELEASE (ROPE) Part # Qty OD DD Buffer Type P /2 04/ % Time P /2 07/ % Stock MANUF PARTS RELEASE Part # Qty OD DD Buffer Type M /2 04/ % ATO M /2 07/ % Cust MPS = DRUM = ORDERS Part # Qty Due Date Buffer FG / % FG / % Stock Manuf (Common) Parts RM1 1.1 1.2 MP1 MP1 RM1 Part sales to customers “Customer” Orders Quote LT’s on Planned CCR Load RM2 RM2 2.1 2.2 2.3 2.4 4.1 CCR 5.1 5.2 FG SHIPPING Non-Stock (Unique) Manuf Parts 3.1 3.2 3.3 RM3 GREEN ZONE RED ZONE YELLOW ZONE Definitions Buffer Status = (Buffer Time – Remaining Duration) / Buffer Time Red Zone = Time req’d for expediting a medium-sized order PP1 PP1 PP2 PP2

1 ABB Goal: Profitable Growth TOC SINGLE PRIORITY SYSTEM DETAILS Why is the change needed? Necessary Assumption What is the objective of the change? Strategy Why will the change achieve the objective? Parallel Assumptions How will the change be implemented? Tactic 4.11.4 Single Priority System to Synchronize Execution 2.1 Reliability/Availability Competitive Edge Hectic priorities (hot, red-hot and do-it-NOW) cause chaos on the floor Even when material release is properly choked, not having a priority system can cause some orders to still be late.. The shop floor is governed by a simple, yet robust, priority system 3.1.1 Remarkable Due Date Perf & Availability Vast experience has shown that when work is released according to set time buffers, excellent results are obtained by using a crude priority system that is based solely on the time lapsed since the release. Buffer Management (BM) is setting priorities only according to the degree the buffer-time is consumed (four color code system - green: less than one third of the buffer time passed is lowest priority and black: more than the time buffer passed is the highest). (Execution) TOC’s Buffer Mgt (BM) as synchronized SINGLE PRIORITY SYSTEM TOC Buffer Management is the ONLY priority system used on the shop floor. The ERP system (and MES/RFID systems) are modified to ensure the Purchase Order List, “Work-to-List” and Distribution Shipment List are prioritized based on buffer status (1st Black, 2nd Red, 3rd Yellow, 4th Green)

4.11.4 Single Priority System to Maintain Execution Synchronization Tactic Target Levels are sized based on Max Demand within Reliable Replenishment time (Rt=OLT + SLT) Inventory levels maintained by replenishing on actual consumption & resizing on buffer penetration SAP Customer Production Orders do have “Due Dates” Sample Screen for showing Buffer status (Priority) of each order and enabling capturing of reason codes for “black” and “red” orders Stock Replenishment Orders do not have “Due Dates”

1 ABB Goal: Profitable Growth TOC BUFFER ANALYSIS (POOGI) DETAILS Why is the change needed? Necessary Assumption What is the objective of the change? Strategy Why will the change achieve the objective? Parallel Assumptions How will the change be implemented? Tactic 4.11.5 Focusing Mechanism for Process Improvement/Elevation 2.1 Reliability/Availability Competitive Edge Most local improvement initiatives in manufacturing, which use good tools (Root Cause analysis, Lean and Six Sigma techniques) do improve the local performance but, many times, those local improvements do not translate into global improvements Not having sufficient protective capacity results in long LT & poor DDP All local improvements initiatives in manufacturing do contribute meaningfully to the global performance and there is enough protective capacity for high DDP 3.1.1 Remarkable Due Date Perf & Availability If a CCR exists, work-in-process piles up in front of it. When materials release is restricted, the only work centers that have work-in-process piling up in front of them are the real CCRs. CCRs can be identified also by recording “what black & red orders were waiting for?” In most of the cases additional capacity can be exposed by better EXPLOITATION like: - Ensuring that CCRs do not take lunch or shift change breaks, - Offloading work from the CCRs to less “effective” work centers that have ample excess capacity, - Using LEAN /Six Sigma techniques to shrink the set-up time/reduce variation on the CCRs, - ELEVATING capacity with overtime or capex approval for the CCRs, etc. (Improve) TOC’s BUFFER ANALYSIS to Focus Improvements & Capacity Elevation For all Red & Black Orders and Stock Buffers, Production Supervisors/workers/purchasers record “what was black/red order waiting for?” CCRs are identified and effectively removed through focused process improvement / elevation to the extent that most loaded resource has at least 20% protective capacity. The ERP (and MES) systems are modified for POOGI.

4.11.5 Focusing Mechanism for Process Improvement/Elevation Tactic
For all Red & Black Orders an Stock Buffers, Production Supervisors record “what was black/red order waiting for?” CCRs are identified and effectively removed through focused process improvement / elevation to the extent that most loaded resource has at least 20% protective capacity.

TOC in SAP at ABB “TOC in SAP” solution design: Order Processing Part I

TOC in SAP at ABB “TOC in SAP” solution design: Order Processing Part II

TOC in SAP at ABB “TOC in SAP” solution design: Determination of Earliest Due Date

TOC in SAP at ABB Results from Brno (Czech Republic) and Vaasa (Finland)
“After analyzing SAP recommendations and data from nearly 2 months, we are confident that the the TOC rules were implemented correctly and that we are now confident that we can switch of our Off-line & 3rd Party systems. The new Dynamic Buffer Management Functionality enables us to react quickly to changes in inventory values, which was not possible earlier, as we didn’t have time to monitor values manually. We are very happy, are continuing to use the functionality and will be expanding it to other product lines” Operations Managers Factories in Brno and Vaasa

TOC in SAP at ABB Next Steps
Implemented "TOC and SAP” now in 8 factories: in Brno, Czech Republic in Chonan, Korea, 2 factories in Vaasa, Finland, 2 factories in Baroda, India in Przasnysz, Poland, 2 factories And planning the implementations (in the work queue) In Vaasa, Finland, 3rd factory in Dalmine, Italy in Ratingen, Germany. Has “SDBR in MES” in Xiamen and Beijing China in Skien, Norway. …until all 300+ factories are reached… Stefan Forsmark, Operations Excellence Manager for ABB:s Power Product Division Thomas W. Schmidt, IS Manager for the Power Products Division Karol Kaczmarek, Operational Excellence coordinator, BU Transformers Erich Beeler,IS Manager, BU Transformers, Engineering IS Katja Rajaniemi, Global Process Improvement Manager, BU Medium Voltage Products Bill Vick, Operational Excellence coordinator, BU Medium Voltage Products May-Jing Li, Project Manager, Group Function IS, 'One Simple ABB' and SAP R/3 Miroslaw Bistron, Manufacturing IS coordinator, Power Products Division Krzysztof Sowa-Pieklo, Project Manager, Power Products Division, Software Factory Martin Korthaus, SCM II Consulting, SAP Fredrik Nordstrom GF Q&O / ODG Alan Barnard, CEO, Goldratt Research Labs Eli Schragenheim, Principal, Goldratt Schools

Research Conclusion The “TOC in SAP” initiative, showed that the ambitious goal of “One-Simple-ABB” can be achieved even in the management of operations (Planning & Execution and Continuous Improvement) in complex and different operational conditions. The partnership between ABB and Goldratt Research Labs made it possible to: Define a ROBUST enough TOC Planning, Execution and Continuous Improvement solution that could cope with all the variations and complexities of 300+ factories Define a SIMPLE enough TOC Solution which could be supported with relatively small modifications within a standard ERP system such as SAP. Break new ground by using the Strategy & Tactic Tree to define, communicate and get buy-in for the new TOC solution in a way that focused and accelerated the achievement of consensus and development of the required SAP functionality…which is also accelerating all new SAP implementations Deliver this project and its associated results in a record time for SAP solution design, development and testing in less than 9 months….

Acknowledgments to Project Team Contributions
Stefan Forsmark, Operations Manager for ABB’s Power Products Division/BU Transformers. Thomas W. Schmidt, IS Manager for ABB’s Power Products Division Goethe Wallin, Operations Manager for ABB’s Power Products Division/BU Medium Voltage Karol Kaczmarek, Global Project Manager Operational Excellence, ABB BU Transformers Erich Beeler, IS Manager, ABB BU Transformers, Engineering IS Dr Katja Rajaniemi, Global Process Improvement Manager, ABB BU Medium Voltage Bill Vick, Global Operations Improvement Manager, ABB BU Medium Voltage Miroslaw Bistron, Leader of Manufacturing IS program, ABB’s Power Products Division Lukasz Krupa, Leader of Manufacturing IS program, ABB’s Power Products Division Fredrik Nordstrom, ABB GF Q&O / ODG Vesa Enestam, Eliaps Oy, SAP SCM Consulting May-Jing Li, Project Manager, ABB Group Function IS, 'One Simple ABB' and SAP R/3 Martin Korthaus, SCM II Consulting, SAP John Trip, Goldratt-TOC Ltd Dr Alan Barnard, CEO, Goldratt Research Labs Eli Schragenheim, Principal, Goldratt Schools Dr Eli Goldratt, Chairman, Goldratt Group

CASE STUDY 2 Finding & Testing a solution to SHORTAGES & SURPLUSES within Book Publishing
Presented By: Dr. Alan Barnard (CEO Goldratt Research Labs, TOCICO Chairman ) Date: 27th August 2009

Presentation Outline Generic Research Problem
Extent and Consequences of Shortages & Surpluses Cause(s) & Direction of Solution Case Study: Random House Publishing Publishing Industry Background Random House Company Overview Phase 1: Quantifying the Extent, Consequences & Causes Phase 2: Finding a Solution Phase 3: Testing the Solution Research Findings Future Research

Research Problem Extent & Consequences of SHORTAGES
How many of YOU frequently don’t find what you want at a SHOP? *Either because the retailer was “Out-of-Stock” (OOS) or it decided not to carry the item you wanted? What is YOUR (consumer) response to this SHORTAGE? Come back later to same retailer to buy same product? Buy a similar product from same retailer and same supplier? Buy a similar product from same retailer but different supplier? Go to other retailer to buy same product? Do not buy anything? What is the consequences of this SHORTAGE on: SHOP BANK CONSUMER SUPPLIER

Consequences of SHORTAGES on Profitability
For Book Publisher and Retailer… Quantifying impact of 1% Lower Sales Volume on Net Profit INSIGHT: 1% Lost Sales = 10% reduction in Profits BELIEF: Lost Sales is not significant (2 – 3%) since today, consumers that want our products can in most cases find it somewhere. FEAR: Is it really worth it to invest in trying to further reduce Shortages? CHECK: How do we know shortages (out-of-stock) is really “only” 2-3%? Does it match our experience as Consumers?

INDUSTRY RESEARCH: Extent, Consequences & Consumer Response to SHORTAGES
Results from International GMA Research Study (2002) Title: “Retail Out-of-Stocks: A Worldwide Examination of Extent, Causes and Consumer Responses” Scope: 661 Retail Outlets, 32 Product Categories, 71,000 Consumers Interviewed, 29 Countries Impact on Lost Sales & Profitability Retailers Lost Sales 8 to 9% OOS x (9+31=40%) Consumer Response = 3 to 4% Supplier Lost Sales 8 to 9% OOS x (9+26=35%) Consumer Response = 3 to 4% But at 1:10 Leverage, 3 – 4% Lost Sales = Lost Profitability of 30 to 40% What about SURPLUSES?

Research Problem Extent & Consequences of SURPLUSES
How many of YOU have recently gone into a SHOP and bought something you did not really want / need simply because the shop offered a BIG discount? How frequently does this happen to YOU? Once a year? Once a month? Once a week? What is the consequence of this SURPLUSES on: SHOP CONSUMER ? SUPPLIER BANK

Consequences of SURPLUSES on Profitability
For Book Publisher and Retailer… Quantifying impact of 1% Discount (Lower Price) on Net Profit INSIGHT: 1% Discount in Price = 20% reduction in Profits BELIEF: Consumers are VERY sensitive to pricing...and discounts is necessary since lower prices = more sales FEAR: Reducing discount / increase in price WILL reduce sales much more CHECK: Are consumers REALLY that sensitive to Price? Is it not possible to significantly reduce SURPLUSES (that lead to discounts)?

Research Problem Another important consequence of SURPLUSES
Where is the real Constraint in the Consumer Goods Supply Chain (e.g. for printed books)? Number of Customers willing to buy (books)… …and what limits customers to buy more of the available books (OR what prevent retailers to sell more books)? Shortages (Out-of-Stocks) OR Shelf Space available in Book Shops to display all available books that would sell if they were available to buy... What is the consequences of SURPLUSES on “Exploiting” the Retailer’s shelf space? Surpluses is like having BRICKS on the Shelf… …and BRICKS = LOST SALES of non-stock items selling elsewhere

Research Problem Previous attempts to solve the problem
More Sophisticated (and expensive) Forecasting Systems to predict consumer Demand…and more Collaboration efforts to share forecasts and supply problems Implementing Central & Regional Distribution Centers (CDC / RDC) to improve availability and responsiveness Bar Coding, High Tech Materials Handling & EDI What was the result? Significant improvements in availability at CDC and RDC’s (95 – 98%) and in responsiveness (daily deliveries)… But…did it really improve Shortages and Surpluses at Retail level and if not, WHY?

Research Problem Challenges in reducing SHORTAGES & SURPLUSES
What makes reducing Shortages and Surpluses so difficult in Consumer Goods? Large number of “Stock-Keeping-Units (SKUs) Unpredictable and High Variation in Demand and Supply Inter-dependencies between SKUs So, off-course, with this complexities, it is a very difficult decision on what to order, when to order and how much? This decision determines not only the success of retailer, but also the success of the distributor, manufacturer and material supplier. So, who do we leave this critical & complex decision to? …and Are these people really in the best position to decide?

Research Problem Cause(s) of SHORTAGES and SURPLUSES
Order LT Stock Level based on customers ordering large batches typically monthly (based on inaccurate F/Cast) Supply LT Surpluses 100 Order LT Supply LT ROP Actual Demand Stock Level based on customers ordering daily or weekly based on with actual consumption 25 Month 1 Month 2 Month 3 Shortages The KEY to achieve “profitable availability of more SKU’s” is to get each link to ORDER LESS MORE FREQUENTLY (START) ….rather than the traditional practice of ,,,ORDER MORE LESS FREQUENTLY (STOP) Yes, BUT…the Cause and Solution has been known for long time, so why don’t we see MORE Supply Chains adopting this…especially BOOK Publishing 57

Case Study Publishing Industry Background
The publishing industry, due to slow or even declining sales, has been under SEVERE pressure to find ways to improve for many years… The book publishing industry think shortages is low but has experienced very high returns (surpluses) for many years (no-sale-return policy) * A Typical Book Publisher have 30% - 50% returns of all books printed Many Book Publishers & Retailers assumed that high returns was simply the “price you pay” to not lost any sales…but most still considered it as an improvement opportunity * A Typical Book Publisher’s Print & Distrib. Costs is only 30% of Selling Price Pile’em high…. Watch’em fly…”

Case Study Random House Publishing
In February 2008, Goldratt Research Labs was approached by Random House Publishing. They are considered one of the best in managing returns, and still have 28% of every book printed returned to be shredded. There were no reliable data about the level of surpluses (and or shortages within retailers), and it appeared as if the consequences of these were not fully understood. Could Theory of Constraints help to quantify the extent, consequences and causes of the problem… and help to find a solution?

Case Study Random House Key Facts
Market Position: Random House is the world’s largest general-interest book publisher, with ore than 11,000 new books issued a year and 500 million books sold annually Employees: 5,779 (as of December 31, 2008) Revenues: € 1.7 billion (Fiscal Year 2008) Shareholders: Bertelsmann AG (100%) Published Authors include: F. Scott Fitzgerald, Ernest Hemingway, John Gresha, Danielle Steel, Dan Brown and Barack Obama…

Case Study Random House Publishing
The Pressure to improve…. Random House Income Statement in € millions Revenues 1,721 1,837 1,947 1,828 1,791 Operating EBIT EBIT % of Sales 8.0% 9.4% 9.3% 9.1% 7.8% Employees (in absolute numbers) 5,779 5,764 5,804 5,395 5,383 What would be the impact of a significant reduction in Surpluses on profitability …?

IMPACT of Reducing Returns on Profitability For Book Publisher…
Quantifying impact of Reducing Returns from 30% to 15% on Net Profit INSIGHT: 50% reduction in returns = 50% increase in Profits FEAR: But what if Changes to reduce Returns causes Sales Volume to drop? Lets use Theory of Constraints to analyze the situation…

Random House Publishing Research Questions
Is it possible to reduce returns without reducing sales? Is “High Returns” the only “cost” of surpluses at retail level? What is the “real level” of unavailability (shortages) of books at retail level? Is it possible to do much better…? … and if so, what changes would be needed in the way the links in the Book Publishing Supply Chain is managed?

Cost of Avoidable Returns Lost Sales (Non-Stocked)
Impact of Shortages and Surpluses on Publisher and Retailer Profitability PROFITABILITY Potential AVAILABILITY Price lower than PoV Avoidable Discounts Potential Profitability GAP Cost of Avoidable Returns Surpluses Lost Sales (Non-Stocked) Availability GAP Shortages Lost Sales (Stocked) Current Current But how do we quantify the impact of Surpluses / Returns (and Shortages) on Profitability?

What conditions block better exploitation?
Applying TOC’s 5 Focusing Steps to the Book Publishing Supply Chain… Step 1: IDENTIFY the System’s Constraint “Until the consumer has bought, nobody has really sold…” The System Constraint therefore is the No. of Consumers willing to buy Step 2: Decide how to EXPLOIT the System’s Constraint “Exploiting the System Constraint” means “Having the Right Product, at the right place and right time (when consumer is ready to buy). What conditions block better exploitation? Shortages of Products already stocked Unavailability of Products that sell elsewhere but which is not stocked due to shelf-space constraints (occupied by Surpluses). Actually Surpluses in a retail shop is like having bricks on the shelf… Step 3: SUBORDINATE everything to the above decision Change any Policy, Measurement and or Behaviour that contribute to current high level of both Shortages and Surpluses YES, BUT, how to we find these and will it really be a win:win to change these…

Random House Research Projects Project Timeline
Project Start Conference Call to share real damage & extent of Surpluses & Shortages Simulation Develop simulation to validate damage of PUSH and benefits of PULL Test Test impact of “Less more Frequently” with 12 Test Shops and with B&N data TOC Evaluation Share generic TOC analysis & solution to shortages & surpluses Analyse Test Results Analyse Test Results for 12 Test vs. Control Shops and agree on next steps Customized S&T Dr. Goldratt with Exco construct customized S&T and plan Test Feb 2008 March 2008 April 2008 June 2008 July 2008 Nov 2008 So, what was the process we used to find and test a “SIMPLE & ROBUST” solution to the problem of SHORTAGES and SURPLUSES…

Book Publishing Research Challenge #1
Case Study Book Publishing Research Challenge #1 What makes quantifying the Extent, Consequences and Causes of Surpluses & Shortages so difficult? Despite excellent “Point-of-Sale” data available from most retailers, Publishers do not have visibility of actual shortages and surpluses at retails. Retailers can buy directly from Publishers (to get best price) or from Wholesalers (to get best availability and response). Therefore, knowing the availability (or unavailability) at one Publishers and Wholesalers do not give a true picture of unavailability at retail level. Is there a simple way to quantify the likely level of shortages and surpluses at retail level?

Quantifying the Opportunity for reducing SHORTAGES & SURPLUSES
Benefit of “flagging” the stock-outs in red...

Quantifying the Opportunity for reducing SHORTAGES & SURPLUSES
Stock-out Lost Sales = Stock-out Days x Sales Velocity/day = 8% Surpluses Lost Sales = Surplus Days x Replacement Sales Velocity/day = 7%

Typical Book Store – Concentration Analysis
Two major lessons from B&N historical analysis: 1. 25% of RH titles carried had zero sales. These titles should have been replaced MUCH earlier since they occupied space and cash that could have been used to sell RH titles that sell elsewhere. 2. Even a SuperStore like this B&N Santa Monica, never carried about 18,000 of RH titles in a 3 years time period. This shows the potential for surplus replacement. NOTE: Above Data for period of 185 Weeks (1/1/ /18/2008) 10% of Titles generates 65% of Total Sales 95% of Titles sell at less than 1unit/wk 25% of titles had ZERO sales over the 3 year period VERY Large opportunity to replace “SURPLUSES” Where “Surplus” = Zero Sales Titles and Titles with Sales Velocity of <1/month with display of >1unit

Book Publishing Research Challenge #2
Overcoming the challenges to reduce shortages & surpluses in Book Publishing Book Publishing Research Challenge #2 What makes reducing Surpluses & Shortages so difficult? Uncertainty of consumer demand Weak incentives for retailers & distributors to improve returns…due to an industry policy of “No Sales-Return Any time” creates an incentive to rather order too much than too little.. Distributors & retailers create buffers for the same “end-consumer demand. Printing & Binding economies of scale that drive large batches. A strong held belief that “Title visibility in the marketplace drives demand (but there is little research to quantify this relationship) Supply chain constraints like warehouse proximity and limited rush reprint capacity at printers The goal is to print & distribute closer to what sells to the end consumer

Research Problem Cause(s) of SHORTAGES and SURPLUSES
Order LT Stock Level based on customers ordering large batches typically monthly (based on inaccurate F/Cast) Supply LT Surpluses 100 Order LT Supply LT ROP Actual Demand Stock Level based on customers ordering daily or weekly based on with actual consumption 25 Month 1 Month 2 Month 3 Shortages The KEY to achieve “profitable availability of more SKU’s” is to get each link to ORDER LESS MORE FREQUENTLY (START) ….rather than the traditional practice of ,,,ORDER MORE LESS FREQUENTLY (STOP) Yes, BUT…the Cause and Solution has been known for long time, so why don’t we see MORE Supply Chains adopting this…especially BOOK Publishing 72

Change in Inventory Profile in moving from PUSH to PULL (less more frequently)
SKU Target Level = Maximum Demand with Reliable Replenishment Time Where RRt = Order LT + Supply LT) OLT = Daily SLT = 1 to 4 weeks OLT = Daily SLT = 1 to 4 days OLT = Daily SLT = 1 to 2 days PUSH Inventory Profile 1-4wks No. of Days of Inventory in Supply Chain PULL Inventory Profile 1 - 4days PRINTER PUBLISHER CDC PUBLISHER RDCs or RETAILER CDC RETAILERS

4:25 Sizing Stock Buffers with Uncertainty and variability in demand and supply Keeping correct inventory levels Planning Rule: “Be Paranoid but not Hysterical” Target Stock Level for each Title at each Storage Location = Maximum Demand within Reliable Replenishment Time Too little Too much Good Enough Execution Rules: Replenish up to Target level in sequence of buffer status more frequently (e.g. daily) Goal Units Feedback Rules: Adjust Target Level (Buffer Size) based on Level of Buffer Penetration Time / Stock Buffer Auto Upsize Buffer based on level of Red-zone penetration Auto Downsize Buffer based on lack of Yellow zone penetration 400 300 200 100 Actual Demand Month 1 Month 2 Month 3

Testing Robustness of TOC’s Dynamic Buffering regardless of Demand Pattern
Stable Sales Launch Event Special Event Seasonality Events

Results from Past TOC’s Replenish-to-Consumption (RTC) Implementations
In general, Goldratt Research Labs have found that if a company reports formally a 1-3% “Lost Sales” due to unavailability of product, improving availability to close on 100% (to end consumer) typically will result in increase in sales of 10 to 30% The Table below shows the results from actual implementation tests: Industry Official Lost Sales Availability before TOC Availability after TOC Avg Increase in Sales within 1st year of TOC rollout Fruit Supplier 2-5% 85 -90% >98% 30% (worst 5%, best 200%) Bread & Flour Supplier 80-95% >99% 20% (worst 5%, best 300%) Cosmetic Supplier 90-98% 10% (worst 2.5%, best 50%) Sportswear Supplier 10-20% 80 – 85% >97% (Total Inv down 60%) 25% (worst 10%, best 100%) Note: In reality, most “lost sales” are not recorded. The dramatic increase in sales achieved with improved availability verifies this.

Testing the Solution with 12 Test vs. Control Shops
Research Questions: 1. Acceptance Rate? % of Shops accepting the offer for the Publisher to “Replenish Daily on Actual Consumption 2. Difficulty to setup up RTC system? How difficult would it be to set up a system for a shop to share daily sales with the publisher and to receive daily deliveries? 3. Really Win:win (Value = Benefits – Costs)? What will be the impact “Less more Frequently” on Shortages (Out-of-Stock) and Surpluses and on Lost Sales…?

Impact on Shortages (OOS) Typical Control Shop – Before vs. After
Similar level of “Stock-outs” before and after the Launch of Test

Impact on Shortages (OOS) Typical Test Shop – Before vs. After
Zero “Stock-outs” after the Launch of Test !

Results Achieved and Lessons Learned so far?
Importance of knowing how to answer simple question of “By how much has Sales gone up?” due to this change... Very high level of acceptance rate of offer to replenish daily based on actual sales (>80%) “Replenishing Daily on Actual Consumption” can help significantly reduce Shortages & Surpluse: Sales Increase by preventing Shortages around % Sales increase by replacing Surpluses (if done on wide enough scale) can be 5-20%. Implementing Dynamic Buffer Management (with so many SKUs) and frequent bad decisions is expected to increase Sales even more Replacing a BRICKS with any Item that sells will increase Sales (BRICKS = More than Needed / Really Slow Runner) Major leverage opportunities to reduce SURPLUSES & SHORTAGES are the really HIGH Runners and the LOW Runners (1’s, 2’s & 3’s that should be 0’s,1’s & 2’s)… What is the chances on a specific day that a book selling at 1/month will be sold 1/30 = 0.03 What is the chances that on a specific day we will sell TWO books, is 0.03 x 0.03 = What SURPLUSES must be replaced? - Anything for which shop carries more than 1 unit which is NOT on a formal DISPLAY promotion that sell less than 1/month. Eli said he is disappointed RH team did not attend Realization conference where company after company (similar in size) was showing what results is possible on a company level within just 12 months.

Results Achieved and Lessons Learned so far?
RANDOM HOUSE STRATEGY & TACTIC L1-5 Results Achieved and Lessons Learned so far? Achieving Viable Vision BASE GROWTH ENHANCED GROWTH 2:1 High Availability 2:2 The Digital World 2:3 Word-of-Mouth 2:4 Resurrecting Dead Horses 2:5 Sales per Shelf (SPS) 2:6 Editorial Section Strategy; Book titles are always available at the stores in which market demand exists for those titles Tactics: The Co. provides replenishment to daily consumption to the shops it services directly and persuades the intermediate carriers* to provide such services its customers NEXT STEP 3:1: RH Test – Impact on Book Shops 3:1:2 Parallel Test - Impact on B&N 3:1:3 Rollout to directly serviced Shops in CDC area 3:1:4 Spread to all Book Shops 3:1: Change Chains & Wholesalers’ order patterns 3:1:6 Spread to all Non-Bookshop Outlets 3:1:7 Achieving Ongoing Improvement Eli Goldratt : Remember, the real reason for conducting the test mentioned in is to see if there were any mistake in our logic? We need to check whether we we over-estimate or under estimate the expected increase in sales by reducing shortages and replacing surpluses… Unlike other industries, the data from the RH tests and from B&N historical analysis showed that there seems to be MUCH more opportunity for increasing RH and Retailer sales from replacing surpluses than preventing shortages. Why? The real constraint in the Publishing Industry is the Shelf Space at the retailer (and sometimes also the cash available). Carrying Surpluses – books that will never sell or more books than needed to ensure no loss in sales – is a MAJOR waste of CONSTRAINT capacity. What else have we proven with the test? We can achieve significant result (increase in Sales of 5-20%) within short period of time with minimum risk… 4:11:1 Define test sample 4:11:2 Launch Tests 4:11:3 Analyze the results Strategy: RH has good enough* estimate of the resulting benefits from providing better availability (“Good Enough”: The reliability of the estimates enables a clear decision) Tactics: RH carries out a carefully monitored test of “high availability” on a statistically representative sample

“Your FOCUS (or lack of it) will determine your reality…”
Always Remember… “Your FOCUS (or lack of it) will determine your reality…” Thank you! For more information…. visit

Finding & Testing SIMPLE Solutions for COMPLEX Problems

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