Sundeep Kailwoo

ICUKU (Impact, Control, Known, Unknown, Uncontrollable) is a 9-square Matrix tool that can be deployed for Categorizing the possible solutions on an Impact Vs Implementation grid. On the "X" axis we Impact categories (Low, medium, High) and on the Y-axis we have Controllable ( further subcategorized as Known and Unknown ) and Uncontrollable factors.
 
This Matrix will help us to first categorize and then prioritize the factors/solutions ( Vital "Xs" , independent variables ).
 
The Solutions that have been identified by the teams through various various RCA techniques can then be placed in either of the 9 cells basis the impact that the action may yield on the proposed change and the ease of implementation basis the factors that the team can also attribute the controllable , uncontrollable scope of those known and unknown solutions.
 

 
Its becomes very critical that while constructing the ICUKU matrix , the team is realistic and exercises pragmatic approach when placing the solutions in the matrix cells, the success or the failure of achieving the desired results will depend upon the solutions we have identified and then categorized then as accurately as possible.
 
Resources are limited and cost optimization along with maximum yield in shortest duration of time is what all want to achieve and this exercise will help to deliver to those expectations to an extent if done correctly.
 
So the Solutions that exist in the HK , MK , HUK, MUK will be our scope of priority in deploying the Actions , to maximize the output.
 
The Example below for an AHT Improvement project showcases the actions that can be deployed ,where ICUKU will be able to help us in planning our actions for best possible results.
 

 
So the Actions in the cells identified as per the first Matrix , should help us identify the actions that are in our control to implement and will yield immediate results compared to rest of the actions identified.
 

RPA practice has become a very important lever to deliver high-cost savings and reducing the dependency on humans for unskilled and repetitive tasks. RPA is successful when deployed at the appropriate process and scale. In achieving the desired outcome from RPA, Process Mining has gained a lot of relevance and has become an integral part of the RPA.
 
RPA concerns with the automation of business processes, enabling companies to strengthen cost effectiveness and quality improvements. The most critical stages of a RPA project is to pick the intended business process to be automated. However, RPA isn't the means to all or any ends and may be deployed randomly across the processes. The intended automated process must be selected carefully to profit the foremost from RPA. This is often where the critical question must be answered, where and the way do we chose the eligible process for a feasible RPA Deployment. Often the business process that's most eligible for RPA has activities that are repetitive, standardized and transactional. But how do we validate exactly which business process is that or one qualifies the minimum requirement for an RPA. Although most of the business owners and operators would have a good idea how the daily operation works, the important deal is to travel beyond a good understanding to the key stroke level details. This is often where Process Mining comes in. Use Process Mining techniques to construct the AS-IS processes by using event logs, identify and choose the processes that benefit the foremost from automation!
 
Advantage of Process Mining
Over the past few years, Business process optimization practitioners constructed the AS-IS process using qualitative methods. With Process Mining's ability to get data and supply insights into the method inputs, flow and output. We now have access to quantitative data points and trends to analyze the simplest fit process. Because the tactic model is made by data its objective and more reliable than as-is process constructed by qualitative methods. The info is extracted from IT-systems that store data and make event logs. The events range from online transactions from an e-commerce website, a business’s offering various discounts and finance schemes to adopt prepaid payment methods over post-delivery methods made through their platform. After the as-is process is made it are often extended with perspectives that are relevant to the business case or the question that possesses to be answered. Process Mining will generate data and help us to identify the frequency of repetitive activities, significance costs or resource use, slowdown time as well as waiting time, process bottlenecks, waste and barriers for a smooth process.
 
Integration of  RPA and Process Mining
Now that  we have recognize what RPA and Process Mining are, the next step it to integrate how  RPA-project can leverage Process Mining. Processes and RPA executioners simply don't only need to use Process Mining as an area of a RPA-project, it's also valuable before or after a RPA-project.
 
Here are some examples:
 
Pre RPA Deployment
Process Mining was performed before automation to optimize a business process.
Process Mining allows for locating the business process where redundancies and process inefficiencies are exposed. This is often beneficial for RPA, as for RPA to be most successful the variation within the business process should be minimized. Before RPA it's better to standardize the processes variation to make high volumes per process variation. This helps in RPA to be used as efficiently as possible.
 
During RPA Deployment
Conduct Process Mining as a sub activity of a RPA-project to supply an objective overview of business processes. It help in making the particular process transparent by a data-driven perspective whereby repetitive activities, bottlenecks and process loops are shown. By doing so we'll identify the sole processes to be automated next.
 
Post RPA Deployment
The data generated by automation enables continuous improvement in terms of further optimizing the algorithms making the tactic add the backend. Use the info for Process Mining techniques to research the tactic and determining the specified outcome, effectiveness of the automation and subsequent improvements

In Business Excellence domain Improvement Kata refers to a Practice of conscious decision making, that's developed over a period of time through consistent practice, deployment, experimentation, and working towards a guided target and not just try storming on a trial and error basis to find a feasible solution. Improvement Kata when applied within the Lean principles aims to deploy continuous improvement for achieving business excellence functional strategic goals. The mindset of deploying Improvement kata is to make sure the practice a daily activity so that habit becomes autonomic in nature.
 
A normal Process Step phase in deploying improvement kata is :
Step 1: Understand the Challenge or Direction that we want to address
Step 2: Grasp/Analyze the Current condition
Step 3: Identify and Establish the next target condition
Step 4: Experiment towards the target condition
Step 5: Repeat the pattern
 
 
Coaching Kata refers to how the Improvement kata steps and the process shared by the experts and the mangers to their teams and the cycle of constant learning and feedback that should follow to track the progress and the improvements made during the Improvement Kata stage.
 
Some of the Questions that Coaching kata practice should address are :
 
Apart from the 5 Step process that Improvement kata consists of , Coaching kata will try to know ,
1: What did you plan as your last Step?
2: What results did you expect ?
3: What Actually happened?
4: What did you learn?
 
These feedback inputs will feed into the Improvement kata loop.
 
 
Some of the Improvement Kata and Coaching Kata Industry Application Examples :
 
Aerospace: Companies Like SpaceX, Blue Origin, Virgin Galactic have set their focused target on Outer Space travel. SpaceX already launched its Working prototypes and Production Rockets and is working towards reusable fuel and Payload rockets to make them cost-effective. Even though some of the recent unsuccessful vertical landing attempts continue to address the current challenge, analyze what's going wrong, setting the corrective target conditions, and working to achieve the optimal output, and will keep on repeating until successful. The feedback loop from the experts and the data generated will help to formulate the coaching kata process , where the change and it outcome is shared and tracked with the teams for next steps in Improvement Kata loop.
 
Production/ Manufacturing : Product Manufacturing industries operate in a highly competitive market and the rapid pace to evolvement of the products or its features keep the market leaders and the challengers on tenterhooks all the time. Improvement Kaka is an ideal tool where the competitor moves / enhancements / innovations  become the direction to score the change in the product to be market relevant , match or exceed the functionality , set the processes towards the goal and extend the product lifecycle through functional and utility improvements in the products and services .
 
Pharmaceutical Industry : An Industry that is working towards developing medicines for the existing non curable and curable diseases and for un-foresighted scenarios like Covid-19. They are constantly moving towards a shifting goal posts basis the results their experiments and trail results.

Cherry Picking a task or a project may yield quick results but most often taking too narrow a view strategy in a larger scheme of things. Also, the level at which the decision is made to invest, and take up a project in an organization or CI as a function is relatively dependent on the hierarchy at which the decision making is taking place. A cherry-picking exercise done at the higher hierarchy level may not be the same for a decision-maker who lies at a lower level of the hierarchy pyramid.
 
But if we base the decisions to take projects basis the Effort Vs result Matrix as shown in the attached image irrespective of the position the decision-maker is at, invariably the projects, tasks that fall in the 1st Quadrant can be identified as easy pickings, cherry-picking when it comes to selecting a project. Low Effort Low Result (Impact), the projects that lie in this space are invariably replications ( Small Automations eg. Macros, Formulas, etc. driven ), easy process fixes ( E-Bay(Enhancement Bay, Power hours, Cheat Sheets, etc.,) low investment relatively high Return or positive ROI projects.
 
Some of these quick fixes may become redundant when a strategic solution is implemented to address a larger cross-functional, cross-process improvement. Hence it becomes important that the break-even to realize the proposed objectives are monetized in a short span of time.
 
Some of the Pros of Cherry-picking when it comes to selecting Continuous Improvement projects :
 
1. Low Cost - Most of the issues addressed by such CI projects are the basis to the process where the improvements are being implemented . The change proposed wouldn't need too much tech cost and manpower cost and can be done parallelly to the core functions that if being performed by the Project team currently. Eg.- Developing a VBA Macro by a Team member or an IT resource within the account to automate the file merge process, where the team is supposed to manually merge different files to start working on the actual value add work. The cost to develop and deploy such automation will be very low but the Cost Savings in Man hours saved could be high and also mistake-proofing can be achieved through this change.
 
2. Less Disruption - Such Projects don't alter the nature of the work too drastically and the improvement can be implemented while doing the process without much disruption / deviating from the current flow. Eg: Team struggling to follow call flow and the basis Troubling shooting process, a Cheat sheet with Call Flow and appropriate probing questions in each Flow Step can be shared with the team for Quick reference.
 
3. Team Engagement in Process improvements -Not all improvement ideas may come from the CI team but invariably its the people who are doing the job on the floor to identify the improvement opportunities, sometimes big, most often small but significant, that impacts the tasks that they are performing. It's very important that the core team that is carrying out the core operations of the process feel empowered and involved in not just performing their tasks but also feel that their inputs, suggestions, and ideas matter, and Feedback is actioned upon. This is where the Cherry Picking exercise will yield results, where small yet effective improvements can be accepted for implementation and the Employees are recognized for their efforts and innovation.
 
Some of the Cons of Cherry-picking when it comes to selecting Continuous Improvement projects :
 
1. Fails the Test of Time / Stability - At times the quick fixes achieved through cherry-picking improvement opportunities may become irrelevant in case of a small process change . The improvements deployed today may become useless due to uncontrollable factors like , Client Process Change, Input Change, Output Change, etc. Eg. - A Macro deployed to address a File Compilation process works only when the input is in the form of an Excel file, but of the Input now changes to word or PDF file input, the automation will fail to operate for what it was built for. The same is the case even if the input remains constant, but the output expectations change, the Improvement deployed will be rendered useless.
 
2. May not integrate with Strategic Direction of the Organization / Function -  Some of the Improvements that may be deployed over time may become isolated and ultimately redundant if the function or organization plans to deploy a strategic solution to address overall functional needs. So the investments and time spent to onboard the changes that were selected through cherry-picking will be discarded. Eg.- A team deploys a process change how they are integrating different data sources manually to produce functional Metric Dashboards, that require tech investment and human involvement, this tactical solution for the team will be out of use once the Strategic solution for a Function wise CRM is implemented.
 
3.Lower ROI - Cherry Picked projects may yield a positive ROI but when compared to other Functions and another ROI impact, the cumulative ROI of such projects may not be as significant as other strategic solutions and Projects. Cherry Picking may result in Quantity of the Improvement projects but will fail in terms of the Bottom Line or Top Line impact of an Organization.
 

Hype Cycle was conceptualized by Jackie Fenn in 1995, while working for Gartner as an Analyst and Gartner subsequently after years insisting and lobbying with the industry started with the annual Hype cycle visualization for new and emerging technologies and branded the tool as Hype Cycle. Hype Cycle is technology life cycle stages Graphical demonstration passing through Conception to Maturity to Widespread adoption.
There are pre dominantly 5 stages in a Hype cycle but then we can build sub stages as well within those broad stages of a technology lifecycle. Mostly used by marketing and technology business decision making, businesses can choose the level of risk and comfort for each stage in the Hype Cycle and at what stage of the life cycle the product or service is currently at.
 
 
The hype cycle classifies five overlapping technology lifecycle stages:
 
1.   Technology Trigger: This is the stage where an Idea for a product, service or new technology is envisaged, a prototype may exist but not in functioning state and no market data, study exists as such on these new technologies, products or services but the prospective enhancement / change / innovation that they may cause will impact the how the media and market reacts and this could be supported by the proof of concept demonstrations as well.
Technologies / Products are this Hype Cycle Stage: Unsupervised Learning in AI, Supervised learning where Manual Intervention is required and limited data sets can be tagged and mapped and need a lot of effort and time. Unsupervised Learning where the Model / algorithm doesn’t needs manual tagging or Intervention. The Model works independently and learns on its own to tag future data in shape of images and Videos. The technology is still being explored and is conceptualized to be deployed in working environment.
 
2.   Peak of Inflated Expectations: The Tech Life cycle stage in Hype Cycle where the functional prototype / technology is implemented by early adopters , creators , inventors , is called the Peak of Inflated Expectations .At this stage a lot of publicity on successful or unsuccessful implementations may be attached with the outcomes.
Technologies / Products are this Hype Cycle Stage: Launch and Stick landings (Vertical landings) for Space Shuttles like SpaceX Starship SN10 rocket. The technology intends to reuse the Payload carrier and the Fueling rocket, thus reducing the cost and timelines for subsequent travels into Space for Mankind and delivering payload. Both SpaceX, Blue origin, Virgin Galactic are some of the pioneering organizations leading the race to Mankind Space Tourism.
 
3.   Trough of Disillusionment: At this stage the shortcomings and not meeting the expected results leading to failures may lead to disappointment in the product/ technology and will see a fall through of some early adopters, inventors and investors. The other may still continue with further refining the functionality and the adaptability of the product / technology while addressing the existing problems successfully. Also new investments and market sentiment will also depend upon the future state of the technology.
Technologies / Products are this Hype Cycle Stage:  Google was very enthused in its launch of the giant Balloon internet services, “Loon”. The experiment was to delivery low cost wide high speed internet services in tough terrain areas across the world. The Project is being scrapped as it could meet the desired objectives of cost optimization for a long term sustainable business.
 
4.   Slope of Enlightenment: The stage of the Hype cycle where product / technology Beta and early versions start showing potential expected outcomes and are accepted by the industry and gets adopted by the companies, peers OR gets tested in control environment .At this stage the inventors, producers will start working on the next gen version of the products / technologies, where it can be integrated with existing services and platforms.
Technologies / Products are this Hype Cycle Stage:    Hydrophobic Farming is one such example, when using acres of lands producing food feed on pesticides , Organic or Inorganic will become unsustainable , Urban Farming , utilizing less space , more energy and resource efficient is the answer in Agritech industry . The industry is expected to grow from $9.7 Billion in 2019 to $17 Billion by 2025 with almost 14% CAGR.
 
5.   Plateau of Productivity: The Hype Cycle phase where the successful and effective implementation is adopted on a large scale across industry spectrum, its differentiation yet adaptability becomes widely implemented. Standards are build up around the frame work of the technology for a sustained, standard understanding of the market and market players around this practice / technology.
Technologies / Products are this Hype Cycle Stage:  Mobile Internet, the technology is past 4G and most of the Developed countries have started rolling out 5G interest services that aim to provide data transfer speed of 20 Gbps at peak and 100Mbps at average. This is almost 100 times faster than 4G, which is the predominant cellular phone broadband network speed.