Demand Profiling Principles, Process & Practice
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Donald Walker, Global Supply Planning Director at Life Technologies spoke at the SCL Event UK 2013
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Demand Profiling Principles, Process & Practice
- 1. Donald Walker Supply Chain Director Demand Profiling
- 2. Agenda Agenda Introductions Introductions Planning in Life Technologies Planning in Life Technologies Demand profiling ––principles, process & practice Demand profiling principles, process & practice Q&A Q&A
- 3. The first point to consider: The first point to consider: ALWAYS aagood thing to do first. ALWAYS good thing to do first. Even planning professionals Even planning professionals need aareminder sometimes…. need reminder sometimes….
- 4. Donald Walker Donald Walker Biologist & Biomaterials Scientist Biologist & Biomaterials Scientist Worked for ––Vascutek, Johnson & Johnson Medical, Allied Distillers, Amazon & Worked for Vascutek, Johnson & Johnson Medical, Allied Distillers, Amazon & Invitrogen (Life Technologies) Invitrogen (Life Technologies) Worked in --R&D, Technical & Process Development, Manufacturing, Project Worked in R&D, Technical & Process Development, Manufacturing, Project Management, Quality, Continuous Improvement, Supply Chain (Demand Planning, Management, Quality, Continuous Improvement, Supply Chain (Demand Planning, Supply Planning and Procurement) Supply Planning and Procurement) April 2006 ––“Why don’t you give materials management aago?” April 2006 “Why don’t you give materials management go?”
- 5. Life Technologies Life Technologies Headquartered in Carlsbad, California Headquartered in Carlsbad, California Recent merger between Invitrogen and Applied BioSystems Recent merger between Invitrogen and Applied BioSystems Life Sciences company Life Sciences company --Biotech Tools Biotech Tools --Diagnostics Diagnostics --Laboratory instrumentation including Genetic Sequencing Laboratory instrumentation including Genetic Sequencing --Moving into applied markets ––Food Safety, Animal Health and others Moving into applied markets Food Safety, Animal Health and others Life Technologies by the numbers.. Life Technologies by the numbers.. 10,000 employees 10,000 employees ~$4B Revenue ~$4B Revenue 23 Manufacturing sites 23 Manufacturing sites 50,000 products 50,000 products
- 6. A complex supply chain A complex supply chain -Products shipped in nanogram vials to standard pallets -Products shipped in nanogram vials to standard pallets -Temperature sensitivity -Temperature sensitivity -Hazardous products & permit requirements aagrowing feature -Hazardous products & permit requirements growing feature -Cross branch planning and inventory cascading -Cross branch planning and inventory cascading --50,000 products 50,000 products -Varied customer base; large Pharma, Universities, Govt Agencies -Varied customer base; large Pharma, Universities, Govt Agencies --22ERP systems & Demand Solutions ERP systems & Demand Solutions -Statistical forecasting and ReOrder Point management -Statistical forecasting and ReOrder Point management --Matrix Management ––Division, Region, Function & Network Matrix Management Division, Region, Function & Network
- 7. Product Examples Product Examples Cell Culture Media Cell Culture Media Nucleic Acid Purification Nucleic Acid Purification Genetic Analysis Genetic Analysis
- 8. Upstream Control Downstream Forgiveness Demand planning Supply Plan Capacity management Order management Inventory policies Forecast phasing Hedging orders Revenue Forecast Short Term Plan Regional Stocking Strategy Supply Production Schedule Plan Plan Standardised order of production Long Term Plan Manufacture Utilisation Plan Inventory Policy DRP Distribute Scrap Liability SVOP Plan
- 9. Demand Profiling Demand Profiling Customer or demand segmentation Customer or demand segmentation Runners, Repeaters and Strangers characterisation Runners, Repeaters and Strangers characterisation --based on frequency & predictability of ordering or volume based on frequency & predictability of ordering or volume Demand profiling is based on purchasing pattern Demand profiling is based on purchasing pattern --Frequency of orders Frequency of orders --Order, Line and Unit comparisons Order, Line and Unit comparisons --Customer location & lead time Customer location & lead time --Analysed in time series Analysed in time series --Group and manage products based on their demand behaviour Group and manage products based on their demand behaviour Supported by basic statistics and basic, internally-developed tools Supported by basic statistics and basic, internally-developed tools
- 10. All progress comes from aa All progress comes from willingness to change… willingness to change… Data can change “a view” Data can change “a view” into aareal conversation. into real conversation. Demand profiling supports aa Demand profiling supports healthy conversation. healthy conversation. “Pay me now…. Or “Pay me now…. Or Pay me later. Pay me later.
- 11. Two populations of SKUs Two populations of SKUs Significant change in buying Significant change in buying behaviour from November behaviour from November Change in unit demand, not Change in unit demand, not necessarily order or line counts necessarily order or line counts
- 12. Two populations of SKUs Two populations of SKUs One population exhibits One population exhibits significant spike in June and significant spike in June and September (quarter end) September (quarter end) Change in unit demand, not Change in unit demand, not necessarily order or line counts necessarily order or line counts Specific to one customer? Specific to one customer? Self inflicted? Self inflicted?
- 13. Sample Data ––understanding buying behaviour… Sample Data understanding buying behaviour… Avg. Avg. StDev Weekly % Change in Weekly Weekly Avg. Weekly Avg. Sales Sales Avg. Sales Weekly Sales Unique Unique Unique Units Units Relative Sales Orders Order Units Orders (52- Order Units Orders (26 Wks Customers Customers Customers SKU Region Total (26 Wks) (26 Wks) StDev (26 Wks) (26 Wks) 27 Wks) (52-27 Wks) vs. Prev. 26 Wks) (26 Wks) (52 Wks) (52-27 Wks) 4389758 All 484 1.08 2.77 257% 0.46 2.33 0.69 1.56 -33.33% 11 21 15 4389760 All 550 1.50 2.86 191% 0.65 2.29 1.27 1.18 -48.48% 14 30 23 4389762 All 158 0.69 2.00 288% 0.27 2.57 0.12 6.00 133.33% 7 10 3 4389764 All 441 5.38 4.49 83% 2.85 1.89 2.69 2.00 5.71% 64 111 61 Basic statistics: Basic statistics: Mean, SD, RSD, Mean : :Median ratio, Modal qty, Correlation Mean, SD, RSD, Mean Median ratio, Modal qty, Correlation Not an exact science (non normal data) but useful for filtering Not an exact science (non normal data) but useful for filtering
- 14. First and last purchase ––New customers and lost customers First and last purchase New customers and lost customers One off purchases and stable buying One off purchases and stable buying Irregular buying but consistent qty: Irregular buying but consistent qty: Modal qty is very useful in avoiding problems with arithmetic ROP values. Modal qty is very useful in avoiding problems with arithmetic ROP values.
- 15. This is a one off order for the SKU from this Ship To This is the first time* that this Ship To ordered this SKU KEY Ship to: 111659 This Ship To has and will order this SKU w/Demand* This is the last time* that this Ship To ordered this SKU Region: (Leave Blank for Global) This Ship To has and will order this SKU no Demand* * within the data set Total Units 201050 201051 201053 201103 201105 201107 201109 201110 201112 201114 201116 201118 201120 201122 201126 201128 201129 201130 201135 201137 201139 201141 201143 201049 201052 201102 201104 201106 201108 201111 201113 201115 201117 201119 201121 201123 201124 201125 201127 201131 201132 201133 201134 201136 201138 201140 201142 SKU Sold To 4415129 2 2 4463027 12 2 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4464531 31 4 0 0 0 0 0 0 0 0 0 0 0 0 0 6 4453237 2 1 0 0 0 0 0 1 4459193 13 2 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4463012 17 2 0 0 0 0 0 0 0 0 0 0 0 0 0 4 Detailed data ––provides aacustomer-based view of purchase history Detailed data provides customer-based view of purchase history
- 16. Diverging behaviour driven change in buying behaviour Diverging behaviour driven change in buying behaviour Analysis led to change in stocking strategy and revised forecast Analysis led to change in stocking strategy and revised forecast phasing for production planning from Q1 2011. Monitored phasing for production planning from Q1 2011. Monitored weekly. weekly.
- 17. Turning data into information Turning data into information --Identify customer & Account Manager Identify customer & Account Manager --Discuss factors in demand behaviour Discuss factors in demand behaviour --Determine whether we can influence buying pattern Determine whether we can influence buying pattern --Can we plan around it? Can we plan around it? --Change regional inventory Change regional inventory --Hedge inventory “just in time” Hedge inventory “just in time” --Rely on cross branch cascade Rely on cross branch cascade --Change forecast phasing Change forecast phasing --Capacity management Capacity management
- 18. Results ––Example of improved availability from one EU manufacturing site Results Example of improved availability from one EU manufacturing site Demand profiling was critical in understanding what & how to improve Demand profiling was critical in understanding what & how to improve
- 19. Results ––Example of product group from one European manufacturing site Results Example of product group from one European manufacturing site Great progress in EMEA where most issues are related to abnormal demand orders. Great progress in EMEA where most issues are related to abnormal demand orders. Room for improvement in APAC ––high growth area for these products in Q4 Room for improvement in APAC high growth area for these products in Q4 Low order count (misses have aahigh % impact) Low order count (misses have high % impact)
- 20. Final thought…. Final thought…. Customer Experience Customer Experience Really? Really? Demand profiling Demand profiling establishes information establishes information about buying behaviour about buying behaviour We can ask “why” and, We can ask “why” and, sometimes, change the sometimes, change the behaviour. behaviour.
- 21. Thank you Thank you Questions and comments? Questions and comments?