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Minimum Viable Product (MVP): MVP is a concept that originated in the lean startup methodology introduced by Eric Ries in 2011. A minimum viable product is the version of a new product which allows a team the maximum amount of validated learning about customers with the least effort. Minimum Viable Product is a strategy used for fast and quantitative market testing of a product or product features. MVP is a version of a product that allows the team to collect as much feedback from customers for the product with the least effort. Visionary customers can fill in the gaps on missing features, if product solves a real problem. MVP allows you to validate your product idea without having to invest time and money in building the complete product. MVP is a prototype to test the core of your idea or the biggest assumption in your business model. Usually it does not cost much money and it is easy to apply. The MVP approach stipulates step by step product evolution keeping in mind user feedback. It also corresponds to the philosophy of ‘ship early, repair later’. We can define MVP as a release of some features to be validated within the market. It bring the core value for early adopters. The goal of the MVP is to build the smallest feature set. Some of the benefits of MVP are – · Early customer acquisition · Resource optimization · Value proposition focus · Saving time and money · Verifying market trends · Building a user base . Attracting investment The purposes of the MVP are as follows – · Brand building quickly · It helps manufacturers decide what methods would be best used to make it · It gives an idea of costs and pricing · To test a new idea/feature · To understand product market fit · Demo to investors · Get a promotion at work The core principles which decides features in a MVP are minimize friction, think scarcity, focus on closing the loop for the user, refine with user feedback and usage data, less is more in MVP, be prepared to pivot if it’s not working. Some of the examples of popular products that were launched using MVP but enhanced later are – Twitter Spotify Uber Facebook Dropbox Amazon Airbnb Instagram Whatsapp Groupon Pebble Product Hunt iPhone Adwords Express Buffer Etsy Foursquare BDRThermea Second Market Zalando Zappos Cruise Automation Microsoft Excel Zynga Product Hunt Angel list Kickstarter Pinterest KPIs Special Events

Before we dwelve upon explaining the inferences of these Cp, Cpk values, let us quickly revisit Cp, Cpk definition. Cp, Cpk are Process Capability Indices. Process Capability is an inherent variability of a given characteristic in a stable process. It represents process performance over a period of stable operations . A capable process is one in which the output always adheres to the customer specifications. Let us see the definition of Cp. Cp is the ratio of the specification limits (of a characteristic) to the natural process variation of a process (under a state of statistical control). In other words, Cp = Voice of the Customer/Voice of the Process = (USL-LSL)/(6*SD) where SD= Standard Deviation and denoted by 'Sigma' symbol. A Cp value of >= 1, indicates that process is technically capable. A Cp value of 2 represents that process performs at 6 sigma level. A Cp value of < 1 indicates that the process is poor. If Cp portrays the capability to meet the customer specification limits, then why do we need Cpk. The answer is that Cp does not consider how well the output is centred on the target value. Cpk addresses the proximity of the centring of a process related to the spec. limits. Cpk splits the Cp into 2 parts, Cpkl and Cpku. Cpk takes the lesser of the two values. The formulas related to this are Cpku=(USL-XBAR)/(3*SD); Cpkl=(XBAR-LSL)/(3*SD) where SD is Standard Deviation and is actually denoted by 'Sigma' symbol. Taking the lesser of the two values, the Cpk value would be Min(Cpku,Cpkl). To explain the concept of Cp, Cpk more - let us take a couple of imaginary examples mimicking real time sports. Example 1: Imagine a football team practising penalty kicks. Assuming the goal posts on both the ends to be the specification(spec) limits. The players think that putting the ball in between the posts is a goal (which it is). But the coach would like his/her wards to be highly consistent. He/she would expect his/her wards to consistently hit a target within the goal post. Imagine the coach wants the football to be hit on topmost of the centre of the goal posts (or any other part)? Why ? Because goalkeepers normally try to distract the kickers(football players) and makes a pre-meditated move. Therefore , it is imperative that players hit their practice-penalty goals consistently at the same target position as much as possible. While Cp talks about slotting of goals , Cpk talks about how much variation or drift is there in hitting the goals at topmost of the centre of the posts. When Cp/Cpk would be high : Example 2: Imagine a practice session going for a shooting competition which is bound to happen in a week. A team of 5 is trying its luck , keeping in mind the competition would be stiffer in the actual competition. The team is aiming a point of 9.8 (out of 10), which could a potential medal winning score ,as per the team. The Qualifying range for the competition is 9.3 and above. If the team is consistently shooting 9.3 and beyond 9.3 say upto 9.5 , then the Cp value is good(high). But if the team is consistently shooting near say 9.7 or even 9.8, then the Cpk is good or high. Now , let us go to the given statistics for this question: USL=24; LSL=18;Ave=21.5;Standard Deviation = 0.75. As per the given calculator, we get the values of Cp as 1.33 and Cpk as 1.11. What do we infer from this ? 1.Cp value of 1.33 indicates that the process is quite capable. 2.However, Cpk value of 1.11 conveys that the process sigma is 3.33 . Formula for calculating Sigma Level = 3 *Cpk = 3 * 1.11 =3.33 . So if the sigma level is 3.33, then it shows that there is plenty of variation and there are so much defects for a process operating just over 3 sigma.Therefore, the variation needs to be reduced. Thats the reason why we look for Cpk . Remember from CP perspective it looked like good until we found this now !! 3.Ideal value for a Cpk should be either at 1.33 or 1.66(close to 4 or 5 sigma) since there can be space for a process drift either to the left or right of the nominal value (target value). 4. Applying the formulas which we discussed above, for Cpku and Cpkl , we find the values for them as Cpku=(24-21.5)/(3*0.75)= 2.5/2.25=1.1111; Cpkl=(21.5-18)/(3*.75)=1.5555; Cpk=Min(Cpku,Cpkl)=Min(1.11,1.55) = 1.11 Conclusion: From this, we can infer that the process is less capable relative to the upper specification limit. Though the variation in the process is acceptable, in order to improve the process performance, the mean needs to be moved away from the USL or back to the middle of the specification limits.