Sanat Kumar

Feature Creep in general means adding more feature to existing features, which might add complexity to the product use.
 
In general every product has a product life-cycle, where post maturity it tends to follow decline. But to extend the maturity phase normally new features are added. Eg- Smart Phones where on a regular basis new features are added to ensure that maturity phase could be extended
 
 
At times addition of multiple features in the product which make is non-user friendly and complex which is termed as “Feature Creep”. The focus of the product owner should be on Quality and user friendliness of the product rather than Quantity.
 
Disadvantages of Features Creep:
1)      Its misuse or waste of money and resources of the organization (as time is spend on development, testing, launch so on)
2)      Makes product complex and difficult to use
3)      If features are not properly thought through consumers will not appreciate it, and might lead to dis-satisfaction rather delighter
4)      At times increased features might boost initial sales but later customer lead to customer dis-satisfaction
5)      Non user friendly
Reason for Features Creep:
1)      Competitors have the feature which the product might not have, or competitor might simplified the features
2)      Customer requirement might not have been clear with development team
3)      Pressure from competition to add more and more features
 
At times Organization or Product owner should understand when to put a halt on adding more features and focus on Quality of the product. Steps which R&D team should take to reduce/eliminate Feature Creep are:
 
1)      Clear understanding of customer requirements (which can be collected via customer feedback, or primary research)
2)      Create a strategy for the product- stay focused invested on the key priorities
3)      Invest time and resources on to key priorities
4)      Frequently analyze customer feedback
5)      Focus more on Future gains then short term gains
6)      Analyze competitors product (or market leader- if the Organization is not market leader)
7)      Do rigorous  testing of Alpha and Beta testing
8)      Be proactive in analyzing un-necessary feature and scrap it

Business Process - set of sequential steps followed to obtain a desired result. Whereas Business Process Re-engineering - steps taken to de-design the current process in order to meet Organization’s goal and objective (cost, quality, service, speed so on). This concept is adopted in early 1990.
 
  
BPR is a 4 step methodology:
  
 
 
Step 1 is to identify process
One of the toughest questions is to identify the process. There are several processes in an organization which can be categorized as “Core and Support process”. BPR concepts should be applied on Core process for the better results.
Core processes are those which are related to vision of the organization. Core process (es) provides organization competitive advantage, creates value for customer and are aligned to organization vision
 
Eg- In Banks core process is providing financial services. For a food processing company any process related to production, packaging and shipment of food are core processes. For a back office completing the transaction on time and with minimal error are the core processes. All the other process could be termed as Support process
 
Step 2 Review and Analyze
In step 2 “As-is” core processes is reviewed and if required perform some process improvement and see if the output is improving. Even after the changes if the output (desired result) is not impacted much analyze the reason for the low output. Use tool like 5Why analysis to analyze the root cause of the As is processs
 
Step 3-Design To be
As part of this step “Design To be process” which might require changes in People/Processes/Technologies. Tools used here to design new process as “Benchmarking” the process which best in class within same industry or different industries
 
Step 4 -Test and Implement
Once “To be” process is defined, next step is pilot testing (the new concept is tested on a very small area or in controlled environment). Once the pilot testing is successful, implement the “To-be process in one go (if process identified is small) or in phased manner (if the process is lengthy). Post successful implementation start from Step 1 for the new process re-engineering.
In case of failure of pilot test (means that either analysis or the “To-be” process is not right, hence it is re-commended to start from the beginning)
 
DMADV-(Define, Measure, Analyze, Design and Validate)
Since BPR focuses on re-think and re-design the process hence traditional Six Sigma DMADV would be on line with the concept. Integration DMADV will enhance the BPR study as Six Sigma focus on the variation reduction and is a customer/business centric approach.
 
Once the core process is identified in Step 1 of BPR its advantageous to introduce DMADV which will help in:
1)      Introduction of DMADV will help business to view the process end-to-end from business and customer value point. Hence focus will be more than cost reduction
2)      DMADV is a structure approach and is a robust methodology, which also emphasize on cross –functional groups and better stake holder management
3)      DMADV will be more focused towards the area where the solution are unknown
4)      It’s a metric driven approach hence post improvement using Six Sigma concepts will help in analyzing the actual benefit in terms of metric movement
5)      Apart from the as a practice in Six Sigma – it also focuses on sustenance of the improvement
 
Hence DMADV will complement BPR and will result in better yield to the vision of the Organization.

In parametric statistics, when we have to compare means of two samples there are several test where 2 samples are dependent and independent
 
2 Sample T Test are used to compare the means of 2 sample which are not dependent on each other and have equal variance (determined by F test) which is normally distributed.
Example:
If we want to compare performance of two team (sales performance) Comparing the runs scored by two different team Outcome of a drug testing on 2 independent groups  Wherein Paired Sample T test is performed to compare means of 2 samples which are dependent (paired) which is normally distributed. Two means could be :
Comparison  pre and post-performance different times Comparison performance due to change in conditions  so on Examples:
Comparing the sales pre and post advertisement Comparing performance of employee per and post refresher training Person’s health before and after a treatment  
Benefits of using Paired T test
Paired T test is a powerful tool due to the below reasons:
1)      Since the sample used before and after are the same hence eliminated variation between the samples
Same set of employee before and after training Same bike before and after servicing Same product before and after a marketing campaign 2)      Its best tool to measure the effectiveness of some factor on a sample, industries where it could be best in use are:
Service Sector – measure performance of people before and after a training Sales – Effectiveness of awareness program/advertisement (pre and post sales value and volume) Pharma- effectiveness of medicine on patient’s health Automobile – Efficiency of automobile pre and post changing fuel efficiency So, we can find its utility in all fields where ever comparative study is required on a paired
Sample 
3)      Increase in the degree of freedom, in 2 sample T-Test df is “n1+n1-2 : as there are two different samples”, But in Paired it n-1 as the sample are same (decrease in df required high t power)
4)      Time and cost is minimized as the sample size remains the same (unlike 2 sample T test wherein 2 independent samples are collated
5)      The outcome of the two groups are co-related

In Analyze phase of DMAIC, Xs’ (or causes) are identified basis different methodology of which Brainstorming is widely used.
Post identification of X’s prioritization of X’s are done, where impact of X’s are studied over Y (effect). Prioritization could be performed by 2 ways “Data door or Process Door”
 
Data door- For all the X’s where data is quantitative in nature (which can be measured). Data door method is taken. Commonly used tool for Data door approach are:
Graphical Analysis: Trend Chart, Run Chats, Control Chats, Histogram etc
Hypothesis Testing: Annova, Regression, Multiple Regression, Chi Sq etc
For eg: if Low Accuracy is the Y for the project then potential Xs’ qualified for data door could be: “Accuracy score between employees, Volume arriving pattern vs Accuracy, Transactions type with respect to accuracy”
 
Process door- At time there are X’s for which data is more of qualitative in nature (knowledge based upon Process experience) Process Door method is adopted.
Commonly used tools are “Process Maps, Fish bone Diagram, RCA etc”
For eg: if Low Accuracy is the Y for the project then potential Xs’ qualified for Process door could be: “Learning Curve of Employee, Work Environment impact on Accuracy etc”