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What is the High-Performance Process Improvement Way of Understanding What Issues Need Most Attention if the Improvement Setting is Very Large to Huge?

Visualization of an improvement setting HPPI deals with. AI generated picture.
Visualization of an improvement setting HPPI deals with. AI generated picture.

Many companies face transformational challenges as markets change more rapidly than the companies can actually deal with. Here new ways of collecting correct and needed data, cultivating the data into correct and needed information (analysis) and furthermore cultivating the information into correct and needed knowledge play a vital role in assuring both the improvement effectiveness and efficiency, in a cost-effectively and timely manner. This is the very essence of high-performance process improvement (HPPI).


HPPI is simply put the contemporary paradigm for efforts running at a high process improvement yield (PIY), cost-effectively and swiftly, using dedicated and verified solutions to reach and maintain that improvement mode. Legacy improvement approaches like e.g. lean, six sigma, Theory of Constraints (TOC) and agile, or a hybrid of these, fail in one or more dimensions regarding the improvement performance (time, quality [PIY] and costs).


To increase the improvement performance further, the VISTALIZER improvement technology is constantly subject to revisions and improvements of the underlying end-to-end improvement process that delivers the process improvement yield to the improvement setting, in the specified time. In total, the HPPI concept contains three different ways (solutions) of assuring that the improvement work is on par with the requirements of HPPI: analysis and synthesis at the network and company level (VISTALIZER for Networks), analysis and synthesis on the process level (VISTALIZER Report), and the implementation Plan phase (PDCA-logic, part of the app VISTALIZER for Enterprises + services). Besides these there is also a fourth method safeguarding the improvement performance and the shared understanding of how things are in the company and what should be done to assure a better future state.


This fourth method is the Rate My Company feature that is part of the app VISTALIZER for Enterprises (iOS / iPad / Android). This feature provides added-value in smaller settings, but especially in larger settings it provides analysis momentum that is otherwise hard to obtain. Basically, the feature provides a visualization how the own company manages or scores in 27 crucial issues or areas related to organizational and process improvement. The app's user can easily generate a code (a sequence) stating what he or she thinks is the level of performance of a specific issue or area (graded red [bad], yellow/orange [satisfactory], green [good], and white [I don't know]). In smaller companies it is possible to discuss together how the own company scores and what should be done, but in any larger setting with hundreds, thousands or even tens of thousands of employees the correct picture is harder to get. It is also harder to depict when things start to deteriorate and having this VISTALIZER integration in place, assures that early signals are properly captured and dealt with. This is especially important in the AI era where organizational issues and challenges need to be properly addressed.


With the modular design of the VISTALIZER technology, it is easy to make use of a logic that collects the input based on how the employees rate the areas in the Car Analogy and based on this presents the output. The employee has just to do the rating of the 1-27 Car Analogy issues, and then send the generated code (the sequence) to a predefined e-mail address. The required technical integration is set-up easily according to the requirements and specific company needs. Also, the utilization logic and user policy can be exactly defined. Here, different parts of the organization can be easily reviewed for deeper insights how e.g. cultural aspects are in line with expectations, or if the staff feels that the strategy deployment and execution could be better. The data collection takes about 5-30 minutes depending on the user, and if the rating is made for the first time or if the rating is an update to a previous one. The output is generated continuously (automatically), each quarter, or when needed, and simply passed to the Car Analogy using the Submit Code function. It is up to the management to decide how the output is shared and communicated, but the generated sequence can be shared with the staff for transparency, better organizational understanding and learning, and boosted steering momentum.


For a user's guide how to set up the integration for your organization, and an example phyton script, please see the Integrations page.

 
 
 

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