COLLEGE OF BUSINESS SCHOOL OF TECHNOLOGYMANAGEMENT AND LOGISTICS (STML) BJMP 3083 OPERATIONSMANAGEMENT SEMINARFIRST SEMESTER SESSION2017/2018 ASSIGNMENT 2: ARTICLEREVIEW AND ANALYSES TITLE: STRATEGIC LEAN MANAGEMENT: INTEGRATION OFOPERATIONAL PERFORMANCE INDICATORS FOR STRATEGIC LEAN MANAGEMENT PREPAREDFOR PROF.
MADYA DR HALIM BINMAD LAZIM PREPARED BY GROUP 5A NAME MATRICS NO HO WEI XIANG 232248 CHIN CHIN LOW 232917 SITI SARAH FATIMAH BINTI ABDUL FATTAH 233860 NOOR ARZALIZA BINTI ARIFIN 234620 DATE OF SUBMISSION30th NOVEMBER2017Journal : Strategic Lean Management: Integration Of Operational PerformanceIndicators For StrategicLean ManagementAuthor : Hector Cortes, Joanna Daaboul, Julien Le Duigou and Benoît Eynard INTRODUCTION This journal of Strategic lean management: integration of operational performance indicatorsfor strategic lean management released in 2016 by Hector Cortes, JoannaDaaboul, Julien Le Duigou and Benoît Eynard. This journal discusses about theimprovement of the traditional lean approach in order to overcome the fourlimits which is nonsufficient number of observations, non-reliable data, a lackof continuous real time data collection and lastly, performance targets are notenough aligned in each manufacturing decision level. On top of that, the new improvementmanage to plug in information systems to collect real time statisticallysufficient and reliable data.CRITIQUE THEAUTHORWe agreed that the result of author studied. Based onthis article, the authors stated that by improving manufacturing systemperformance should take lean indicator or other indicator as the company’sstrategic objective. Because any companies should prepare any occurrence theyfacing and find another alternative to solve it.
However, the authors mentionedthat by only focusing on indicators would not give in many cases for theperformance improvement. The indicators should be analysed at the beginning toensure the insufficient to evaluate the system’s performance. In decisionmaking, only based in numbers, percentages and ratios could give reduced at thelong performance.
Moreover, the authors stressed out that indicators usedto evaluate the level of leanness of manufacturing system. In leannessmeasurement can use benchmarking which used by several researchers (Wan andChen, 2008). Nevertheless, the main limits are difficult to get the appropriatemanufacturing system as the example to get the needed information because it alwaysconfidential which makes this approach did not frequent to use.Additionally, the authors mentioned that to eliminatethe risk in production monitoring could implement the fuzzy approach. Which isthe theory for modelling qualitative and quantitative data.
The theory giveefficiently analyse different production strategies and improvement because itallows measuring separately the performance of each lean indicator. However,any theory have pros and cons which for this theory have directs or indirectimpact on many production parameters. Where this theory did not allow analysisof the effect of improving an indicator on other system. Different company would implement in differentproduction systems for services which the evaluation insufficiently developedwith standardized.
If the company could success implement different leanconcept, nevertheless most of it incapable to measure their performanceimprovementApart from that, the authors stated that the traditionallean implementation did not give improvements on production system because ittakes irregularities and variabilities. It is because the demand and resourcesboth are uneasy to handle which lead to the production failure. Furthermore,lack of evaluation interactions between production system’s components. Goodinteraction give major impact to production which could improve the error insystem.Other than that, the authors tells that lean approachneeds additional tools. The viable system model (VSM) is a model of the organisational structure of any autonomoussystem capable of producing itself which allows distinction of waste andnon-waste process.
This model is easy to analyse the current manufacturingsystem towards lean. Figure1. Lean-Six-Sigma Framework (LSSF) HIGHLIGHT THE KEY LESSONSLEARNEDLean Six-Sigma The authors highlighted thatthe lean six sigma could overcome the traditional lean limits. The lean sixsigma are based on the alignment between operational indicators and thestrategic objectives of a company which as the beginning of the steps. Nextstep, a collection of sufficient data for statistical analysis for performancewhich the integration with MES/ERP. Next, simulation for evaluate the futuresystem performance due to different improvements. Furthermore, the ranking ofproposed improvements.
Other than that, Continuous and monitoring theimprovement’s performance. The last step, being the operational or strategicalignment. PIs/KPIs Measurement KPIs determine the company’sstrategic objectives, and identifying the company’s different impacted levels.
It should be classified according to the main fundamental lean aspects. Thereexists different works developing evaluation and qualification models fordefining and measuring PIs for the evaluation of lean implementation. Pakdiland Leonard (2014) model integrates qualitative and quantitative estimationsand covers the entire production system wastes.
KPIs is important to take asthe consideration of the evaluation due to the market or environment change.Operational or Strategicalignment The operational or strategicalignment step is to ensure the improvements which proposed at step three (leansix sigma) can give an impact not only in operational performance.Nevertheless, Operational performance also get the impact on strategicimprovement in objectives of the company. Figure 2: Alignment methods SUGGESTION ANDRECOMMENDATION In order to get theeffectiveness in production, we suggest that the authors should give methodthat simple and easy to apply. Because the complexity in strategic operationalperformance alignment could take the longer time as they planned. Moreover, theauthors should identifying problems in operational systems and in productionbased on accurate and reliable real-time data such as prioritizing wastes toeliminate which classifying the different improvement or modificationalternatives. Apart from that, forecasting give the impact of differentproposed improvements on the future system’s performance in the production. IF POSSIBLE, BROADEN OREXPAND THEIR KEY POINTS WITH OTHER EXAMPLE To provide a guidefor industry to identify candidate KPIs from existing sources, define newcandidate KPIs, select the most effective KPIs based on KPI criteria, andcompose a final KPI set (Kibira, Brundage, Sheng and Morris, 2017).
Moreover, strategicKPIs could be classified for any type of industry into five categories: Cost,Quality, Flexibility, Stock and lead time (Corbett, 1998). The use of ERP inlean implementation via the integration with different production supportinginformation systems Goddard (2003). The ERP allows production planning, stockmanagement on time scale of one day and scheduling. While MES permits analysingdata and collecting data in order to evaluate the different tasks and theirassociated flows as planned by ERP (Mcclellan, 2001). MES provide the real timeon the production system’s performance which allows better implement a leanapproach and to control the improvements. If the company doapplied lean concept in their production does not mean their company willsuccess. Because their incapability in measuring the resulting performanceimprovement (Bhasin, 2011). In addition, the lean objectives not accuratelydefined and estimated.
Then, there is no unification of all measure in aholistic approach (Elnadi and Shehab, 2014). REFERENCES Bhasin, S. (2011). Measuring the Leanness of an organisation,International Journal of Lean Six Sigma, 2(1), pp. 55-74. Corbett, M.L.
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