Dynamic inventory management parameter configuration concept

Transcription

1 Dynamic inventory parameter configuration concept Ari Happonen Lappeenranta University of Technology, Faculty of Technology Management, Lappeenranta, Finland

2 Background The original problem area was in manufacturing industries. The concept is mostly based on the know how and research work done within this industry area Could be applied to any industry with similar inventory challenges The basic idea of concept: Keep enough inventory to keep number of exceptions on assembly / manufacturing down, but still try to avoid overstocking

3 Why? Manual inventory parameter handling is time consuming task In case of big inventories, changing the parameters in fast cycles is not feasible On another hand, ICT based solutions can be used to automate part of the parameter handling task Allows more efficient resource (time) allocation Can cut down number of exceptions on manufacturing

4 Old problem! More items on stock => longer it takes to balance the inventory parameters compared to the demand The basic reason for the problem The nature of the demand Roughly it can be said that demand is never steady / stable On another words, steady demand is abnormal demand Some Solution used by many practitioners Overstock Years old inventory parameters are updated only when problems arise Average demand calculation + some buffer E.G. some sort of excel sheath models Usually problematic to get correct as demand (in general) is not constant. Demand has changes in many dimensions, which makes the demand look uncertainty

5 Demand changes / Uncertainty Uncertainty of the demand => stock vs. demand problems (failure in synchronization) Kambil [1] defined 6 main reasons for synchronization failures Uncertainty, ambiguity, complexity, volatility, urgency and differing Reasons for the uncertainty - Changes in demand - Could be a result of changes, e.g. pricing policy change of the competitors - Changes on the markets (new product, new working method etc.) - Possible ICT based solutions to reactively handle these changes - Demand analysis (the profile of the item / module demand) - Periodical change analysis - Automatical adjustment to changes [1] Kambil, A. (2008) Strategy crossroads. Synchronization: moving beyond re-engineering. Journal of Business Strategy, Vol. 29, No. 3, pp

6 Demand changes / Uncertainty Uncertainty of the demand => stock vs. demand problems (failure in synchronization) Kambil [1] defined 6 main reasons for synchronization failures Uncertainty, ambiguity, complexity, volatility, urgency and differing Reasons for the uncertainty - Changes in demand - Could be a result of changes, e.g. pricing policy change of the competitors - Changes on the markets (new product, new working method etc.) - Possible ICT based solutions to reactively handle these changes - Demand analysis (the profile of the item / module demand) - Periodical change analysis - Automatical adjustment to changes [1] Kambil, A. (2008) Strategy crossroads. Synchronization: moving beyond re-engineering. Journal of Business Strategy, Vol. 29, No. 3, pp

7 Dynamic warehouse parameter concept Based on idea off demand and item classification Multiple step process Feasibility check Classification& item selection for automated parameter handling Demand analysis Parameter definition and up keeping phase Utilizes many different methods, but still tries to keep the structure of the method simple enough for fast user learning curve

8 Dynamic warehouse parameter concept Based on idea off demand and item classification Multiple step process Feasibility check Classification& item selection for automated parameter handling Demand analysis Parameter definition and up keeping phase Utilizes many different methods, but still tries to keep the structure of the method simple enough for fast user learning curve

9 Feasibility check = 2 level ABC classification Critical component for manufacturing? Automanic / manual Manual Manual Automatic Automatic Manual 2. Phase classification Easily acquired components VMI etc. Management? Automatic Manual Low value items (C-class) High value items (A-class) Demand / year 1. Phase ABC classification(finanzial aspect)

10 Feasibility check = 2 level ABC classification Critical component for manufacturing? Automanic / manual Manual Manual Automatic Automatic Manual 2. Phase classification Easily acquired components VMI etc. Management? Automatic Manual Low value items (C-class) High value items (A-class) Demand / year 1. Phase ABC classification(finanzial aspect)

11 Item selection for automated parameter handling Is based on feasibility study Industry, markets and product know how highly required Specially item criticality definition (e.g. for assembly etc.) is extremely hard to define by using some software tools => manual work required Item selection for automated parameter adjustment should be made by the people responsibly of the warehouse daily operations No shortcuts! Result => 2 item groups Manually managed items Automatically managed items

12 Item selection for automated parameter handling Is based on feasibility study Industry, markets and product know how highly required Specially item criticality definition (e.g. for assembly etc.) is extremely hard to define by using some software tools => manual work required Item selection for automated parameter adjustment should be made by the people responsibly of the warehouse daily operations No shortcuts! Result => 2 item groups Manually managed items Automatically managed items

13 Defining the parameters Is based on Demand analysis Automatically managed items has already 3 basic subgroups Defined by the 2 different ABC analysis dimensions These groups are further divided to additional subgroups

14 Defining the parameters Demand analysis is made on two dimensions Change in demand amounts between different demand events Changes in time frames between demand items Low changes on both => steady demand => low safety buffers needed Low changes on demand, high on time frame => additional buffer needed to compensate for demand rush High changes on demand, low on time frame => some additional buffers (compared to average) to keep up on longer high demand periods High changes on demand and time frame => too hard demand structure for any software tool? Can be divided on two subgroups Low value => just use high buffers Average / high value => do not use automatic parameters at all?

15 Defining the parameters Demand analysis is made on two dimensions Change in demand amounts between different demand events Changes in time frames between demand items Low changes on both => steady demand => low safety buffers needed Low changes on demand, high on time frame => additional buffer needed to compensate for demand rush High changes on demand, low on time frame => some additional buffers (compared to average) to keep up on longer high demand periods High changes on demand and time frame => too hard demand structure for any software tool? Can be divided on two subgroups Low value => just use high buffers Average / high value => do not use automatic parameters at all?

16 Calculating the actual parameter values Based on demand history data Short time frame (e.g. 2-4 moths) is used to define resent market demand Long time frame (generally 1 year period) is used for seasonal demand pattern analysis This data is combined mathematically to predict short time near future demand DOS (Days of Supply) is used to base point for defining reordering moment

17 Long time period Periodical demand analysis from demand history data

18 Short time period Periodical demand data is adjusted to reflect current market situation

19 Defining the re-order point Based on DOS (Days of Supply): Given inventory level as base point for order decision Near future demand prediction Defines the expected demand Safety buffers are taken account E.g. in case of high variability of the parameters from decision point to another human intervention can be needed Calculate the DOS Compare DOS to defined order point => make the order decision

20 Contact information Ari Happonen Researcher Lappeenranta University of Technology PL 20 FIN Lappeenranta Tel: GSM: