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1© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
TOCICO CONFERENCE 2004
Using the 5 Focusing Stepsto Define Local Measurements
Presented By:Presented By: Sanjeev GuptaSanjeev GuptaRealization TechnologiesRealization Technologies
Date:Date: 2626thth October 2004October 2004
2© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
The measurements problemThe measurements problem
• Managers need local measurements− Evaluate local contribution to system performance− Provide alerts for proactive course corrections− Pinpoint improvement needs and focus improvement efforts
• Local measurements can be counterproductive− The moment we introduce local measurements, we risk local
optimization at the expense of global goals
• Examples of bad local optimization− Projects: hidden safeties− Supply Chain: excess inventory− Sales: inflated forecasts, heavy discounts
REMINDERT, I and OEare not local
measurements
3© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
Nothing new to reportNothing new to report
• All the necessary concepts have been defined
• Further development will happen when the solutions is implemented in more companies
4© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
Consideration: variability and uncertaintiesConsideration: variability and uncertainties
• If we had a perfect, non-variable world ...− Customer demand was known years
in advance− Manufacturing technology did not
change− Machines did not break down− Work-processes had zero variability− New technologies could be
developed without trial and error
• … the measurements problem could be solved by optimization software.
1. Create optimized plans with detailed instructions
2. Communicate instructions
3. Ensure that instructions are followed
5© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
1. Identify the constraint
2. Exploit the constraint
3. Subordinate everything to Step 2
4. Elevate the constraint
5. Go back to Step 1 if the constraint has changed
Key to local measurementsKey to local measurements
Subordination LogicConvert exploitation decisions into instructions for front-line managers.
Buffer ManagementMake instructions reflect the effects of uncertainties and insubordination.
Buffer DiagnosticsRecord obstacles to subordination and prioritize based on buffer impact.
6© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
Measuring subordination: productionMeasuring subordination: production
• DBR is assumed for Master Scheduling and Material Release
• Buffer Consumption measures subordination in aggregate− What percent of orders are in the red
zone? Is that number growing?
• Track work-in-process (WIP) inventory for local contribution− WIP can be quantified as Throughput $’s
or Number of Work Orders/ Parts− Can have an advanced metric (WIP x
days of buffer consumed), or simply classify as RED/ YELLOW/ GREEN
− If you use T$’s and days of buffer consumed, it is the same as T$-Days
• Measurement: prevent WIP from accumulating (maintain flow)− As long as materials are released per
DBR, flow is aligned with T & I goals− There might be conflicts between flow
and OE. Use T and OE calculations to resolve such conflicts
Flow GraphFlow Graph
D1D1 D2D2 D3D3 D4D4 D5D5 Time
WIP LegendColor based on buffer consumption
7© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
Identifying/ prioritizing improvement needsIdentifying/ prioritizing improvement needs
• Reason Code is captured when work is put on hold, e.g.:− 01, Quality Problems− 02, Drawings Not Available− 03, Problems with Set-up− …
• Pareto analysis is based on buffer impact/ frequency, e.g.:− Yes, we have problems with set up. But
was that one of the top three causes of buffer consumption?
• Use standard Reason Codes− Makes analysis easy− List of standard Reason Codes should
be continually updated as old systemic problems are fixed and new ones arise
DiagnosticsDiagnostics
R1R1 R2R2 R3R3 R4R4 R5R5 Reason
LegendImpact
Frequency
8© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
Same general solution works in projectsSame general solution works in projects
% BUFFER
% CC
% BUFFER
BUFFER REPORTINGIN PRODUCTION
BUFFER REPORTINGIN PROJECTS
1. BUFFER CALCULATIONS ARE DIFFERENT
2. MEASURING WIP IS TRICKY – Throughput $’s are difficult to quantify– Effort (hours of work) can be gamed most easily– “Number of Tasks” might be the most practical
9© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
Information Technology can help Information Technology can help ……
Subordination Instructions
Buffer Diagnostics
Buffer Management
Data Collection,Data Collection,Processing andProcessing and
DistributionDistribution
10© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
…… but you cannot rely on numbers alonebut you cannot rely on numbers alone
• We have to distinguish non-performance from effects of uncertainties and variability.
• Not all human intuition and judgment can be converted into bits and bytes.
11© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
Key points about local measurementsKey points about local measurements
1. Subordination + BM, not optimization.
2. Flow, not efficiency.3. Computer-aided,
not computerized.
12© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
Overall management process and measurements Overall management process and measurements (for production and projects)(for production and projects)
PLANNINGExploitation decisionsTranslate into instructions for first-line supervisors
IMPROVEMENTPrioritize and
pursue improvementopportunities
EXECUTIONEnforce instructionsKeep instructions current
•• T, I, OET, I, OE•• Safety NetSafety Net
•• Buffer StatusBuffer Status•• FlowFlow
•• ∆∆BufferBuffer•• ∆∆T, T, ∆∆I, I, ∆∆OE?OE?
13© 2004 TOCICO. All rights reserved.
TOCICO 2004 Conference
About Sanjeev GuptaAbout Sanjeev Gupta
• CEO of Realization Technologies, the leading provider of TOC Multi Project Management solutions.
• Prior to Realization, CEO of Thru-Put Technologies, a TOC Production Management solutions provider.
• Founded Thru-Put after working at Xerox for 5 years in various management roles, the last of which resulted in dramatic improvements in one of their plants using DBR.
• Education− M.S. in Public Management & Policy from Carnegie Mellon.
− M.S. in Mech. Engineering from Virginia Tech.
− B.S. in Mech. Engineering from Indian Institute of Technology, Delhi.
• Married, with two children.
e-mail: [email protected]