Loading presentation...

Present Remotely

Send the link below via email or IM

Copy

Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.

DeleteCancel

Make your likes visible on Facebook?

Connect your Facebook account to Prezi and let your likes appear on your timeline.
You can change this under Settings & Account at any time.

No, thanks

MSc Management (Ops Man overview)

Paradigm shift developments
by

Roy Stratton

on 20 October 2012

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of MSc Management (Ops Man overview)

Practice and theory Operations Management Cost/
efficiency Reducing
variation Flow and managing
variation Law of quality Theory of performance frontiers Law of focus Theory of Constraints Shifting paradigms supply chains and flow Integrated CI and alignment strategies Lean and agile supply Buffering mechanisms (Capacity; Inventory and Time) Generic Strategies Reduce variation
Buffer variation for flow
Separate / postpone Fisher's model The past solutions are no answer!
On-going innovation is necessary What do you see? "As we advance deeper into the knowledge economy, the basic assumption underlying much of what is taught and practiced in the name of management are hopelessly out of date...
Yet most of our assumptions about business, technology and organization are at least 50 years old. They have outlived their time. As a result we are preaching, teaching and practicing policies that are increasingly at odds with reality and therefore counterproductive.…
These assumptions that determine what we pay attention to and what we ignore are usually held subconsciously by the scholars, the writers, the teachers, the practitioners in the field. Thus, they are rarely analyzed, rarely studied...rarely challenged - indeed rarely even made explicit."


Peter Drucker Law of scientific management
Law of quality
Law of variation
Law of cumulative capabilities
Law of trade-offs
Law of factory focus
Law of variation buffering
Law of bottlenecks ‘Laws’ to be considered Phenomenon (e.g. variation) for which explanation is sought should be clearly defined.
The description of the phenomenon will centre on some observed regularities, derived either logically or empirically (e.g. variation degrades performance)
There should be one or more precise statements of these regularities (e.g. law of variation).
The theory should explain the mechanism or tell a story of why the laws work as they do and how to clarify their limits. Special terms or concepts will be used to aid the explanation.
The more powerful the theory, the more likely it will unify various laws and generate predictions that can be tested. (e.g. Theory of Constraints) Theory in Operations Theory of Swift Even Flow
Theory of Performance Frontiers
Deming’s System of Profound Knowledge
Theory of Constraints

Is there a unifying theory? Theories to be considered The more swift and even the flow of materials through a process, the more productive that process is. Thus, productivity for any process rises with the speed by which materials flow through the process and it falls with increases in the variability associated with the flow, be that variability associated with demand on the process or the steps in the process itself. Theory of Swift, Even Flow
(Schmenner and Swink, 1998) Video ‘White Heat’ Law of Scientific Management Modern times Dinner rush Batch Drive for cost
reduction &
automation Drive for
customisation Line Project
Jobbing Variation Volume Project/Jobbing
Special (one-off)
Empowered workforce
Decentralised control
Batch
Repeat orders
Commonly functionally organised
Line
Highly standardised
Dedicated delivery system
Centralised control Delivery systems choice Review the service delivery system. How does this meet the needs of the business?
Review the recent changes in the business. What has been their impact?
What buffering changes have been necessary? Case study McDonald’s Corporation A Process of ongoing improvement 5 If the constraint is broken, go back to step 1 but
do not let inertia become a system’s constraint 4 Elevate the system’s constraint(s) 2 Decide how to exploit the systems constraint(s)

3 Subordinate everything else to the above decision
1 Identify the system’s constraint(s) The Five Steps of Focusing (Agile?) (Lean?) Fig. 4 Matching Supply Chains with Products
(Source: Fisher, 1997, p109 modified) Efficient Supply
chain Responsive supply
chain Functional Products Innovative Products Match Match Mismatch Mismatch 08 October 2012 Goldratt Performance
Trade-off Strategic alignment Paradigms Flow Process
Variation Quality Continuous Improvement TPS Six Sigma Lean OM Laws OM and SC Theory Law of variability buffering Law of Trade-offs Law of variation "Increased variability always degrades the performance of a production system". (Hopp and Spearman, 2007) Flow and
variation reduction Henry Ford flow line Ohno Shingo Law of variability Law of cumulative capability Deming Toyota Production System Lean thinking Lean / Six Sigma Law of scientific management Theory of Swift and Even Flow "Law (Variability Buffering): Variability in a production system will be buffered by some combination of Inventory, Capacity and Time." (Hopp and Spearman, 2007) Theory of Performance Frontiers Thinking globally Goldratt case Strategic alignment What to expect of a theory? (Schmenner & Swink, 1998) (Schmenner and Swink, 1998; Hopp and Spearman, 2007) Shewhart Acceptable
Quality
Level 0% 100% Conformance
quality costs Cost of quality
assurance Total costs Cost Quality Traditional Economic Quality Cost Model ‘The central problem of management in
all its aspects, including planning procurement,
manufacturing, research, sales, personnel,
accounting and law, is to understand better
the meaning of variation and to extract the
information contained in variation.’ Variation has wide consequences! Operation costs down High quality puts costs down and revenue up Revenue up Sales volume up Scale economies up Image up Service costs down Rework and scrap costs down Capital costs down Inventory down Processing time down The Quality Cost Trade-off 0% 100% Conformance
quality costs Cost of quality
assurance Total costs Cost Quality Continuous improvement lower specification limit (LSL)
upper specification limit (USL) LSL USL LSL USL LSL USL Process variation and Six Sigma 6 sigma process variation
= 3.4 defects per million opportunities 5 sigma process variation
= 230 defects per million opportunities 4 sigma process variation
= 6200 defects per million opportunities 3 sigma process variation
= 66800 defects per million opportunities Process variation Process variation Process variation Process variation LSL USL Certain predetermined patterns inside the control limits also indicate special causes SPECIAL CAUSE AREA SPECIAL CAUSE AREA Centre Line (CL) LCL UCL Basic Parts of a Control Chart Deming, 1986, p20 Operation costs down High quality puts costs down and revenue up Revenue up Sales volume up Price competition down Scale economies up Image up Service costs down Productivity up Inspection and test costs down Rework and scrap costs down Complaint and warranty costs down Capital costs down Inventory down Processing time down Profits up Quality up Six sigma PDSA - continual improvement Deming - prophet unheard EBQ Cost Batch size The Traditional Batching Cost Model Total cost Inventory holding cost Set-up cost Continuous Improvement Cost Batch / Order Size The Lean (JIT) challenge to the batching cost model 08 October 2012 Set-up cost Inventory holding cost Just in Time Days Upper and Lower limits narrowed
Common cause variation minimised 08 October 2012 Days Upper and Lower limits narrowed
Common cause variation minimised Evidence of common cause variation improvement due to system change 08 October 2012 (c) Roy Stratton, NTU System of profound knowledge Appreciation for a system
A network of dependent components with a common aim.
Knowledge about variation
Life is variation. A process not in statistical control has not a definable capability: its performance is not predictable.
Theory of knowledge
Management in any form is prediction.
Psychology
Understand people and their interactions with each other and circumstances. (Intrinsic and extrinsic motivation) System of Profound Knowledge (Deming, 1994) A common sense approach to viewing and focusing the improvement of a business system. In operations management this involves improving flow through adopting better management rules. These rules exploit the opportunity to manage the inherent system variation by aggregating the variation using buffer management that is then used to target the reduction of variation.
The TOC applications therefore suit more complex environments
MTO - Drum Buffer Rope; Projects - CCPM; Distribution; MTA Theory of Constraints
(Goldratt 1988 - ) sd: standard deviation Performance Cost Asset Frontier Theory of Performance Frontiers Operating Frontier the weak link in the chain squeeze as much out of it. align all decisions to that focus add additional resources. :
holds that variation and uncertainty within a supply chain, whether this arises through external demand or internal processes, drives the need for buffering and the buffering choices determine the performance trade-off. It follows that there are three fundamental buffer choices and three generic strategies that may be used to reduce or manage the buffer requirements in line with strategic priorities. 10 October 2012 The theory of variation and uncertainty buffering (VUB) y m Loss caused
By deviation
Of y from m Cost of
products
disposal or
rework Value of functional characteristic Quality
Loss Taguchi Loss Function ‘We in America have worried about specifications:
meet the specifications. In contrast, the Japanese have worried about uniformity, working for less and less variation about the nominal value – e.g., diameter 10mm.’ (J Betti, Ford Motor Co.)
(Deming, 1994, p225) What do you worry about? Toyota Production System 1950-
Deming and quality systems 1950-
Total quality control 1960-
Just-in-Time.1970-
Lean Manufacturing1990-
(Machine that Changed the World)
Lean Thinking 2003
The Toyota Way, 2004 Lean Developments Enable the material to flow by eliminating system variation:
waste (muda)
inconsistency (mura)
unreasonableness (muri)
(Ohno, 1978) Toyota Production System 13 October 2012 Key attitudes
Operational stability (level scheduling)
Quality at the source (built in conformance)
Enforced problem solving (expose the waste)
Kaizen (Standardisation and continuous
against 7 categories of waste)
(Concern-Cause-Countermeasure) Lean/JIT/TPS Exercise
Deming’s Red Bead Experiment Leanness means developing a value stream to eliminate all waste, including time, and to enable a level schedule.

Agility means using market knowledge and a responsive supply network to exploit profitable opportunities in a volatile mark
(Nailor et al., 1999)


Production is lean if it is accomplished with minimal waste due to unneeded operations, inefficient operations, or excessive buffering in operations

Production is agile if it efficiently changes operating states in response to uncertain and changing demands placed upon it.
(Narasimhan et al., 2006) Lean and Agile Lean and Agile Supply Distinguishing attributes Lean supply Agile supply
Typical product Commodities Fashion goods
Market place demand Stable Unstable
Product variety Low High
Product life cycle Long Short
Mfg task Low cost Delivery Speed
Delivery penalties Long term contractual Loss of order
Purchasing policy Product specific Assign capacity
Information enrichment Desirable Important Performance Cost Asset Frontier Theory of Performance Frontiers Operating Frontier Performance objectives Cost
Quality
Delivery reliability
Delivery speed
Flexibility (Slack et al., 2012) Throughput TOC Trade-off models Cost sub- optimisation (Schmenner and Swink, 1997)
Full transcript