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Benchmark Six Sigma Expert View by Venugopal R John Paul Kotter, thought leader in business leadership and change management is known for his '8 steps of change management', as listed below: 1. Increase urgency 2. Build a guiding team 3. Get the vision right 4. Communicate for buy-in 5. Empower action 6. Create short term wins 7. Don't let up 8. Make change stick Any continuous improvement program in an organization is a 'Change Management Process'. However let's map each one of Kotter's eight steps with the methods and terms popularized by Lean Six Sigma methodologies and terminologies. 1. Increase Urgency One of the key concerns expressed by some Lean Six Sigma practitioners is that although they initiate a project, they fail to obtain sustained support and patronage from their leadership team. The LSS tool that helps to project the urgency is the 'Business Case' is the 'Project Charter'. One of the questions that we need to ask while formulating the business case is "Why is this project required now? What will happen if this project is NOT done NOW?". Defining a good business case and getting the project charter signed off with the sponsor is much emphasized for the very purpose of 'Increasing urgency'. It shouldn't be a ritualistic 'sign-off' but a genuine commitment to reflect the priority, importance and urgency. 2. Building a Guiding Team The spirit of Lean Six Sigma included 'team work'. LSS offers a very structured hierarchy for building a team. Promoting Cross Functional Teams and building 'Process orientation' across the organization are essential expectations of a good LSS movement. The various portfolios defined in the LSS team, viz. Sponsor, Champion, Master Black Belt, Black Belt, Green Belt, SME help to evolve a network of guided teams with multiple levels of authority, knowledge, responsibilities and guidance. 3. Getting the Vision Right The LSS approach for Project identification begins from the Strategic Goals of the organization. A structured policy deployment using proven tools such as 'Balanced Score Card' is done to derive the projects and the CTQs. The projects thus derived will have to be inter connected and ultimately lead towards to the overall strategic goal of the organization. This implies setting the vision right at the strategic level and for each and every project. There are well defined methods for drilling down objectives to specific project goals. Every project is supported by well structured objective, goal and scope statements. All these enable getting the vision right for the organization and for each and every project as well. 4. Communicate for Buy-In Every stage of a LSS project has defined documentation and communication requirements. Though the stakeholder 'buy-in' is an important aspect at each stage of the project, the two key stages during a project execution are the buy-in required while launching a project and while implementing the solution. Methods to perform 'stakeholder analysis', overcoming stakeholder resistances are key considerations during the Pre-Define phase of a project as well as during the solution implementation. There are detailed orientation for leaders using programs such as 'Change Acceleration Process' and 'Champions Programs' that help in preparing mindsets of decision makers to be adaptable and open for considering varied change propositions. The 'Pilot testing' which is an integral part of the 'Improve phase' provides another opportunity for practical communication of the proposed solution (change) and to facilitate 'buy-in'. 5. Empower Action Well defined, structured and objective methodologies for Project selection, Fact based management, Causal analysis, Solution identification, Implementation and Handing Over foster participative leadership. For each portfolio of the LSS team, the responsibilities and authorities are defined and they may be further customized by respective organizations. Empowerments in terms of authority to lead projects, to perform trials and experimentations are built-in features of an LSS program. The various certifications reflect stages of authorities and empowerment to be entrusted with the individuals. A full fledged LSS program will have levels of empowerment viz. Enterprise wide projects, Functional projects and Kaizens at process levels. 6. Create short term wins As part of the Define phase, LSS projects look for 'Quick wins'. Even when alternate solutions are identified in the 'Improve phase' using an "Effort vs Pay-off" matrix. Actions that can be done with low efforts though not resulting in high 'pay off' are classified as "Low Hanging Fruits". We can see the application of 'Short term wins' in yet another approach. It is quite common to have a Black-belt project, that could have sub-objectives deployed as smaller projects, viz. Green Belts and Yellow Belts. The success of such smaller projects are recognized as 'Short term wins' while the overall Blackbelt project may take longer time to be fully executed. 7. Don't let up During the 'Analyze' phase, the set of 'potential causes' are identified and tools like the Fishbone diagrams, Affinity diagrams are used to capture and stratify such causes. Then we narrow down to critical causes by applying appropriate evaluations, which may include statistical tests. However, if we still do not identify the critical or root causes, we are not giving up, but we would move back to the list of potential causes and pick up other causes. If necessary we would add further to the list of potential causes. Another approach would be that if we do not find a strong relationship between a factor (X) and the objective (Y), we would look for a multiple regression type of relationship. The set of tools for identifying and focusing on ultimate root causes provide adequate opportunities to explore in breadth. 8. Make changes stick It is a very conscious decision to include the 'Control Phase' as part of the 'DMAIC' approach in LSS. One of the pre-requisites of implementing an improvement action is to ensure that the necessary control measures are in place to ensure that we sustain the gains. As part of the LSS way of thinking, we often refer to the equation Y = F(X). The entire pursuit of the project is to identify and quantify the Y and the X. While we set an improvement target for the "Y", identifying the appropriate X and establishing the relationship between Y and X is a key part of the project success. In order to make the changes stick or in other words the improvement to sustain, we need to monitor the Y and control the X factors. The concept of Poka-yoke is encouraged to try for mistake proven solutions. However the 'Control Plan' as part of the Control phase is a tool to ensure that the requisite controls are ensured for the objective to retain its improved status. The above narrations are an effort to illustrate how the Lean Six Sigma program has inbuilt features that support all the 'Change Management' steps defined by John Kotter, just as expected for any successful CI program.

Six Sigma projects is done to solve a problem, which will lead to bringing changes in the system to improve the current situation. Changes often leads to disturbance among the employees as it is disrupting the existing way of work. So it is very important to have a very strong change management system in place. Kotter's change management model suggests steps to follow to have a strong change management system in pace. Following are the steps and what Six Sigma project leaders can do based on each step recommendation. 1. Create urgency - Show the strong reasons for the change by showing the negative impacts if the changes are not done like falling profit margin, falling market share, etc. 2. Build a guiding coalition - Select team who is for the change and ensure that all are aligned to the change objectives. This will ensure a strong bonding among the team members. 3. Form a strategic vision - Collect all objectives to achieve and make a vision statement, which is acceptable to all team members and easy to understand and relate. This ensures that all work towards reaching that vision. 4. Communicate the vision - It is very important to communicate properly the vision to all affected parties clearly so that all are having the same understanding. This step cannot be taken lightly by making easy ways of communication. We have to check all kinds of communication and select and implement the right way of communication. 5. Enable action by removing barriers - Identify all aspects of the organization which are acting as barriers and remove them. Examples are as follows - Right job description, right performance management, right reward system, talking and sorting with people who are resisting the changes. 6. Create short term wins - It is important to keep all affected parties of the change motivated. For this the project leads can create some short term goals and achieving them. By this, we can showcase short term wins. 7. Sustain acceleration - Six Sigma project leads need to ensure that the team keeping building upon the change already brought in so that people don't remain stagnant at a point. 8. Institute change - Embed the changes brought in into the company's vision, mission, values, beliefs and assumptions.

The two leaders in the BI market according to the Gartner 2021 report are Power BI and Tableau. Tableau has been around since 2003 and Power BI was launched in 2011 and added to the Office 365 suite in 2013. Power BI Power BI is a Business Intelligence software, that was added to the Microsoft family as a SaaS model. It is very closely related to Excel. It consists of a group of applications and services that are on the cloud. The main apps amongst others are Power Query, View, Pivot, Map, and Q&A. With its integration with Excel, it is very easy to create dashboards and reports, hence, it is the go-to tool for inexperienced BI users. Microsoft has added Power BI to its Power Platform which includes the Power Virtual Agents, Power Automate, Power Apps, etc. Its disadvantages are that it offers less functionality than Tableau. Also, in order to get its full functionality, you need to install the SQL server and the Report Service. Tableau Tableau was introduced as a BI software in 2003. It is more powerful than Power BI. It is one of the go-to software for Data Visualization. Tableau has a strong user community and has an end-to-end solution that begins from collaboration, moves on to analytics, the discovery of content, preparation of data, access of data, and deployment. Tableau is more flexible than Power BI. The desktop version of Tableau can be installed without the installation of the SQL Server. Its disadvantages are that it is much more expensive than Power BI and its learning curve is steeper than Power BI since it needs you to build your own data warehouse. Further, the Tableau licenses have incremental costs, and connecting to third-party service providers adds to the cost. Similarities between Power BI and Tableau. Both Power BI and Tableau can create a variety of Data Visualizations such as bar, line, pie charts, tree, geographical maps. The visualizations are interactive on both the software with them having features such as filtering, creating dashboards, etc. Both the software can be connected to various data sources, are user-friendly and require no coding. Differences between Power BI and Tableau Power BI works only with MS-Windows and can be easily integrated with Microsoft, however since Tableau has been acquired by Salesforce, its integration with Salesforce is easy. R and Data Visualization R is free software that was initially used for statistics and graphics. The R Core team and R Foundation for Statistical computing support its development. It has been under development since the early 1990s and is available under the GNU General Public License. It is available for various operating systems. Besides the command line interface, it can also be integrated with third-party GUI such as RStudio and various IDE such as Jupyter. Since R is open source, it is extensible through functions, and packages. The R community is constantly contributing and improving its functionalities. Besides great libraries for Data Visualization, it has numerous libraries for statistics, linear and non-linear modelling, spatial, time series, machine learning, and artificial packages for classification, clustering, computer vision, etc. Comparing R to Power BI and Tableau. As an open source, R is free, it is being developed by a vast community of R Programmers and has the latest packages in most of the domains. Even though the learning curve is steep, its data visualization package is comparable to both Power BI and Tableau. Besides this it has great packages for Simulation, Machine Learning, Artificial Intelligence, etc. References https://spreadsheeto.com/power-bi-vs-tableau/ https://www.datacamp.com/community/blog/power-bi-vs-tableau https://en.wikipedia.org/wiki/R_(programming_language)

Tableau: Tableau is a data visualization tool used in business intelligence, to simplify the raw data to an user understandable format, involving visualizations in the form of dashboards. Power BI: Power Bi is also a data visualization tool used in business intelligence to convert data form various sources into interactive dashboards and reports . Let us compare the advantage and disadvantages of each against the parameters listed below : Power BI Vs Tableau Comparison parameter Power Bi Tableau Performance Performs better with limited data and performance drops when bulk data is supplied. Able to handle large volume of data quickly and doesn’t limit data points User interface Provides report view ,model view and data view in the user interface ,which very intuitive. Provides cards and shelves, data source page, status bar, toolbar, sideband sheet tabs in the user interface and allows customizable dashboards according to the requirements. User experience Easy to understand and user friendly to operate Customizable dashboards which encourages the user to experiment with data for desired results. Ease of use User interface connects with Microsoft applications provides an edge in ease of use. Misses out on the easiness to interlink between Microsoft applications Suability for organization Suitable for small ,medium and large scale organizations Suitable only for medium and large scale organizations Data source support Limited access to other data sources and servers compared to tableau. Access to various data sources better than power BI in comparison Supported data source examples Microsoft Excel, Text/CSV, Folders, MS SQL Server, Access DB, Oracle Database, IBM DB2, MySQL database, PostgreSQL database, etc Excel, Text File, PDF, JSON, statistical file, Amazon Redshift, Cloudera Hadoop, Google Analytics, drop box, google sheets, google drive and others. Programming support Supports Data analysis expression , M language , R programming R Language ,- C, C++, Java, and Python. Data Visualization Attractive and visually appealing dashboards Customizable dashboards, translating quires to visualizations. Embedding of reports Realtime embedding of report is easy Realtime embedding of report is challenging Machine learning Enables the machine learning solutions using Azure Machine learning, SQL Server based Analysis Services, data streaming in real-time, Supports python machine learning Products available Power BI Desktop Tableau Desktop Power BI Service Tableau Desktop Personal Power BI Data Gateway Tableau Desktop Professional Power BI Report Server Tableau Public Power BI Mobile Apps Tableau Server Tableau Online Tableau Reader Customer support Smaller community to support, considering the application is relatively new. Extensive user base and high online user community groups to support.

Tableau which is now a group company of Salesforce Inc. – Started in 2003, Is an American company specializing in data visualization software development and services. Power BI - It is originally developed by team working on SQL Server system and went on to become Power BI in 2013 as part of Microsoft windows / office 365 with foundation and additional features built on excel. With around one decade more richer presence and pioneer in the data visualization services, Tableau scores very high among data visualization professionals and experts. For Amateurs and users looking for better ease and low-to-medium data complexity and visualization application, Power BI is normally initial choice. Tableau and Power BI can be compared in the below table. Metric / Feature Power BI Tableau Company Microsoft Inc Tableau Software Inc Year of Inception 2011, formally named as Power BI in 2013 2003 Pricing position Costs Less Costs more Data complexity, handling high data loads 4 5 Professional, expertise level 3 5 Usefulness for amateurs, students, basic needs 5 3 Integration with Microsoft Excel High Medium Speed 4 5 Drawing action-oriented insights 4 5 Functionality Limited data source connections Can be connected to numerous data sources Visualization Moderate Visualization – visualization is basic but one can get 3rd party tool into Power BI Advance Visualization – Capability to create advance visualization and there are blogs with complete step by step instructions available over internet to learn Dashboarding Open Dashboarding – It doesn’t have any fixed layout to create dashboard Effective Dashboarding – More number for options available to create layouts and easy to enhance. Can find good examples in tableau public website Data Modelling Strong Data Modelling (Power Query) – Can bring in multiple tables and create data models to connect data Lacks Data Modelling – One can’t produce high sophisticated data model in tableau but can create simple joins and unions. Others Strong Data Manipulation (DAX) – Using Data Analysis Expression one can create relatively complex dashboards Strong Story Building – In a story one can bring 4-5 sheets or dashboards based on need ( to create) Conclusion: Depending up on user and user needs either Tableau , Power BI or other competitive software can be used for Data Visualization PS : Registered Trademarks of relevant companies are acknowledged. This article submitted in Forum is purely for academic purpose only. The comparison is based on limited understanding and insights from various resources available in public domain. No intended purpose to promote or favoring any product / service.