Arunesh Ramalingam

My understanding is both Measurable (Quantitative) and Immeasurable (Qualitative) data need to be understood and given equal weight for effective management. The qualitative factors would indirectly affect the quantitative measures. It would not be a good idea only to rely on measurable Data to Manage because the circumstances, conditions, method, and assumptions used for the measurement would have a great impact on the measured value. A data set obtained from incorrect measurement would really harm the inference. In some cases, there could be a significant time gap before we can obtain substantial quantitative data to analyze and make decisions. For example, Regional cultural impact on a new business. It might be too late to revive a business if we wait for Quarter to quarter Business data to formulate a strategy. Culture is immeasurable, but we still need to understand and consider the possible impact it could have on the business growth. In my view, what Edward W Deming would have meant by his statement is sometimes we would need to let go of numbers and data and trust the “gut feelings”. One needs to exercise caution in accepting any measured data and raise questions regarding the measurement techniques.

Necessary Condition: Result is TRUE ONLY IF Cause is TRUE. (Or) Result ONLY IF Cause (Or) In Absence of Cause, Result does not occur. Sufficient Condition: IF Cause is TRUE, Then Result is TRUE. (Or) IF Cause THEN Result (Or) Presence of Cause ensures Result. (E.g.) Boiling an Egg cooks it so it is Sufficient Cause but boiling is not necessary cause for cooking because there are others ways of cooking it without boiling. An interesting Statement: Root Cause Analysis is necessary, but not sufficient, to ensure that more effective problem solving practices are implemented. [1] (1) Necessary but not Sufficient (depicted by NnS): It should be investigated what other “necessary but not sufficient” (NnS) causes exist. A number of NnS causes could supplement each other satisfying the Sufficiency requirement for a problem to occur. If even one of the NnS is removed then the occurrence of the result can be prevented. (E.g.[3] for an object to be a square it has 4 NnS conditions – should be plane figure, have 4 sides, all 4 sides should be equal, and 4 right angles. If even one of the 4 NnS conditions is removed the object is not a square any more i.e. result loses its validity.) (2) Sufficient but not Necessary (depicted by SnN): The only option is to remove the sufficient causes so that the occurrence of the result can be prevented. (3) Neither Sufficient nor Necessary (depicted by nSnN): Most of the time these causes can be lived with and can be removed based on the cost involved in working on them. It should be analyzed whether it is really worth to invest cost (Time, Man, Money and Resources to remove this and if the result justifies the invest (ROI Analysis) (4) Both Sufficient and Necessary (depicted by SN) When a condition is termed as “NECESSARY and SUFFICIENT” then there are always some background assumptions made. The assumptions should be validated to ensure the sufficiency condition is always True. If YES then these should be prioritized and removed. Removal of these can also prevent some of the other NnS conditions from becoming sufficient conditions. Causes to Problems can be categorized into 3 types [2]: 1. Physical Causes which are tangible causes e.g. bearing size 2. Human Causes which would trigger a physical Cause. e.g. improper mounting or lubricating the bearing 3. Latent Causes (or Organizational causes): e.g. no system in place to ensure bearing is lubricated when lubricator is on leave. It is hyper critical that an unbiased analysis is done on the 3 categories of Causes to differentiate between the Necessary Vs. Sufficient reasons to identify the root cause for solving the problem. Domain experts are sometimes biased to address causes related to their area of expertise e.g. Reliability Engineers might focus almost exclusively on addressing the Physical Causes of problems, whereas sustainable solutions are those that address the Latent Causes of problems [2]. The experts should be used to analyze the problems in their particular area of expertise. An effective implementation of Root Cause Analysis within organizations can be achieved by [1]: Empowering the workforce to solve problems within their area of operations, Encourage the use of team based problem-solving approaches for more complex problems. It is advisable to involve a skilled facilitator to ensure that sufficient depth of analysis is conducted in an unbiased way. REFERENCES: [1] http://www.plant-maintenance.com/articles/Getting_Root_Cause_Analysis_to_Work_for_You.pdf [2] R J Latino and K C Latino, “Root Cause Analysis – Improving Performance for Bottom Line Results”, CRC Press, pp 87-88 (1999) [3] https://www.khanacademy.org/partner-content/wi-phi/wiphi-critical-thinking/wiphi-fundamentals/v/more-about-necessary-and-sufficient-conditions