Ruchi Chopra

Control is a crucial stage which ensures that the solution deploys sustain. Reason why the improvements or gains fails or slip away Relevant team and stakeholders are not made aware/trained about the new ways of working Lack of updating the standard operating procedure or process manual and people referring the old ways of working Lack of accountability for maintaining the improved status Performance review on the KPI or timely dashboard reviews are not followed or adhered Users resist the change or introduce shortcuts How to ensure adherence for sustainable solution Metric monitoring and reporting to detect any issues Timely updating the SOP and creating training planning for onboarding and calibrating everyone required Real time performance review via live dashboard Build robust system with mistake proof solution and do testing on all scenarios before deploying solution in production. Assign owner for specific for monitoring and governance Performance testing and regular audit to validate process adherence in production

Most of the AI agents need continuous redesign to adapt the new optimized process changes & improvements. however futuristic approach should be that AI learns and adapts the changes themselves and evolves as human drive changes rather than a still component 1. Ensuring AI evolves with process Integrate AI into continuous improvement advise chain- that is treat AI as process agent and assess its performance under new conditions Monitor prediction determine model confidence level 2. Create Model Governance Schedule validation to calibrate and assess whether the AI is performing basis latest process improvements. Change Management: Whenever a process change or new development made, review an impact assessment on performance. 3. Creating “Human-in-the-Loop” (HITL) Feedback mechanism AI should be designed to receive feedback from users correcting AI deliverable . Human can review, compare and validate the AI output delivered and establish whether it was at required benchmark 3. Continuous Learning basis backed up data · The new data can assist AI for the required change. you may use this data for to retrain AI Ensure all AI inputs, and outcomes are logged in structured & defined formats. What Role Can MBBs Play? MBBs play as a bridge for process improvement and AI adoption: 1. CTQ and output Alignment MBB reviews whether delivered AI solution meets customer requirement and critical to quality collaborate with different functions from process owners to development team and assess the performance basis requirement 2. Performance Measurement MBBs can help define AI metrics to assess how well the AI is adapting to process improvements and so can assess its contribution to the overall improvement goals. 3 MBB helps in developing the Data Governance: MBB can ensure the quality of data, its ethical use and privacy as the AI continuously learns from evolving process change

AI has been trained to resolve the issues basis the historical data and symptoms which is solving the issue at the surface level however not solving at the root cause level. Well, it optimized prediction but not prevention. A best example can be forecasting/ predicting employee attrition in an organization AI tool can flag the early leaver basis the historical data and the anticipation basis the tenure, performance rating and engagement level, their survey results and the salary. however no one deep dives into the reason for disengagement and does not solve the actual issues solving the culture and other professional concern related to growth, employers, role etc MBB analyse and help in framing the right problem statement. they use SIPOC, Voice of employee and critical to quality tools to bring into the relevant KPI to solve the problem basis employees’ view MBB utilizes LSS tools like fishbone and 5 whys to get to the root cause MBB can question the past data and ensures the validity of the data and no seasonal data included to influence or provide bias MBB indicate how the process and its achievable result looks like before the AI model is deployed in solution. MBB define the actionable and intervention needed at al level and not just retention tacts only MBB bring in all the cross functional teams and stakeholders to avoid the silo approach and work collaboratively to resolve the problem with engagement Difference AI MBB AI detects and solves issues at surface level MBB deep dive and solves the problem by identifying the underneath root cause of the issue AI provides prediction accuracy basis the historical data & trends MBB ensures the business outcomes meeting the ned user/customer requirement and creating positive impact within customer’s life Generates speedy results via automation Generates values and take risk into account while delivering the outcome Biases basis the historical data Applies accuracy basis the current situation and fairness MBB act as a eyes and ears of the process and ensures that the solution deployed by AI fits in well and resolves the root cause and eliminate the process waste to optimize the process efficiently and effectively

A robust control framework/guardrail is required in any process driven organization to sustain the process, create accountability for process owners, transparency, fairness and compliance with regulation. It integrates lawful and ethical considerations, ensure compliance, and operational guidelines to ensure that AI systems are developed and utilized with responsibility. Elements of AI governance framework · Align initiatives with organizational goals · Stakeholder engagement from the beginning and two way communication · There should be fairness, accountability and transparency establish · There should be Risk management strategies. that is, assess and mitigate risks for the process data including all scenarios and impact assessment before deployment · Embed AI taking overall process into consideration, ie core business workflows · SOP to be updated for the new process and procedure and all scenarios · Train team about the process changes and provide clear communication · Performance monitoring and evaluation Who should be included Role Responsibility Executive Sponsors/senior leadership They are there to set the vision and provide direction for AI initiatives. Culture embedment and collaboration are promoted by them Legal and compliance teams They establish the policy and ensure legal and compliance guidelines followed. They conduct the implemented AI monitoring. Business Process Owners Define SLA, test and validate the AI developed solution. Data Scientists / AI Engineers Build and maintain AI solution and ensure the best practices followed IT / Infrastructure Teams Ensure scalability and secure deployment of solution. MBBs / Process Excellence Leaders Ensure alignment with Lean/Six Sigma principles and eliminate the process waste In order to maintain both Agility and Control, we can integrate prioritization framework and for agility there can be cross functional squads working in sprints. we should define SLA for performance review and monitoring and light weight governance for minimum viable product. there should be performance dashboard as control and for agility there should be feedback loops from users

Key performance indicator helps to evaluate business performance on various metric. We have been using Efficiency gain, cycle time reduction, first time right, average handling time, on time delivery, cost reduction and many more. With the evolving time and AI introduction to business processes, some of the old metric will loose its significance and so there is a need to introduce some metrics which can do justice to track the real performance and value delivered in the business KPI that should be excluded is average handling time as AI may reduce the average time per ticket which is time to close a ticket to user with response however this can lead to redispute from a customer if a complicated query is not answered correctly and will also lead to low customer satisfaction and will get some detractors and criticism KPI that should be included is the AI decision and confidence rate which will determine & measure the acceptance of AI solution by human users and indicate confidence level of AI solution this will indicate how much the AI solution and its response is reliable to users

An MBB act as intermediary between the business requirement and AI capability. they act as a translator between the customer need and technology capability to deliver the same. MBBs role is important to ensure that applied AI solution is not just technically well but operationally apt as well and based on customer’s verbatim and requirement and strategically aligned. They understand the business problem statement, articulate it well. They validate that developed AI solution fulfil user’s requirement and apt for their usage and not only technical They help in getting adoption of the new solution and ensure the AI solution is aligned with existing standards They take care of risk assessment and plan risk mitigation for the developed new solution. they ensure to deploy the relevant control plan for the sustainable solution and do not introduce any new risk in the process In order to ensure that AI initiatives are aligned with process excellence, customer and company’s priorities, MBB should follow below mentioned points:- 1. It should start with process and it’s core problem. the project that donot target the business problem improvement should be challenged and questioned 2. Include process owner and AI technology folks and end users from the beginning to incorporate all view points and calibrations. 3. Use these lean six sigma method to carve the structure for AI project by reflecting the clear problem statement, accuracy in measurement of KPI, root cause analysis and sustainable control plan 4. Reflect AI solution as an ongoing and continuous improvement enabler and not as one time invention. Reflect the progress in daily calls/huddles and dashboard

One of the processes that was optimized using Lean six sigma tools in finance was month end activity of reconciliation. Lean six sigma projects helped in optimizing the processing time by reducing manual working for reconciliation process by creating standardized format for reconciliation, reducing the manual journey entries and reducing number of approvals Now this process can be optimized further by applying the AI and below mentioned are the points that AI may help with · by finding real time differences (probably by data entry or interface issues) · by implementing rule-based logic and reconciling transactions among different systems · by integrating Copilot to assist professionals in drafting adjustment entries and validating balance and providing summary of the performance · by applying OCR or NLP to read or extract the backup documentation

Best ideas to fix process Ideation techniques can be used to generate the idea to fix a process with in the teams. There should be free flow of ideas to think divergently and come up with as many ideas as you can . All ideas should be taken seriously and looked into with pros and cons. From the given ideas, selection of best solution can be made using statistical tools and cost benefit analysis. Towards end, the solution effectiveness should be reviewed to ensure measurable improvements in the process. the solution which serves effectively with better score should be considered based on the requirements and criteria. When we talk about a software company, creating software requires code which involves solving new problems and inventing things. Testing tool is rule based which follow steps to check if the software works properly. Coding requires specific skillset and creativity to create innovative solution while testing via testing tools require more of cost. Testing can only reflect the defects however coder is the one who will make the right amendment to fix the bugs. We need to strike the balance to bring the best of both the worlds, where in the coder who create new inventions and testing tools who help in identifying the issue to fix because without coder the testing tools cannot correct the issue. Steps to approach change without change resistance Change happens when the capability is adopted or when new process is created. Change is tough in any situation. People resist change due to distrust. · Include and inform everyone involved and impacted to keep the clear and open and two-way communications · Take impacted stakeholder’s point of view and get them involved from planning. this will also create ownership for them from very beginning · Reflects what’s is it for them · Check the nature of change and impact · Make early adopters as your brand ambassadors who will help create the detractors to neutral and neutral to promoter · Senior leadership should always be onboarded for the change from the beginning. They play crucial role in translating the policy into action and can be influential in implementing the change · Impacted personnel should be trained on the new changed process

Leveraging Voice of Employee Employees voice is a feedback or view point based on their experience working in an organization. They work, day in and day out very closely in the business and so they understand the process shortcomings and the areas of opportunity or possibility of failure at a granular level. They identify workplace issues and know what they need best to succeed. When an employee feels heard, they feel more valued and more likely to become brand ambassador By embracing their perceptive, companies access knowledge for custom enhancements. Engagement and satisfaction increase of a heard employee. Tailoring improvements in response to voice of employee cultivates psychological safety and care among the staff members. A supported staff translates to optimized operations and outcomes. With multiple different perspectives, organization become more insightful and better equipped to plan strategically and future-proof organisation with new, efficient and innovative solutions. Neglecting employees’ input risks disengagement, turnover, and productivity/profitability impacts. on contrary, leveraging voice of the employee fosters an aligned, invested team contributing to the organizational goals. There are various methods to take Voice of employees. Organization can send surveys, put the suggestion box in office premises, create helpdesk, there can be skip meeting and HR connects to know employees view point, there can be focus group or team wise ambassador to gather voice of employee and their view point, open forums in townhalls to address queries and take feedback/suggestions. Challenges that might hinder gathering actionable employee insights and how to overcome them 1. Unsurety of suggestion taken positively – Employee might feel that there can be a push back or rejection for his suggestion. he might feel that his idea might not be taken up seriously or might be criticised. to overcome this challenge the employee and employer relation needs to be healthy so that employee feels respected and supported to share this view point. he should not fear the consequence of sharing his viewpoint and there should not be any fear or humiliation. Managers also need to provide response to employee politely with honest feedback gracefully 2. Hierarchy/designation impact- Employees may feel that they have little or no influence over the decisions that affect their work and well-being, and that their voice is ignored by their superiors who take the final decision. Managers/superiors may feel that they have the authority and expertise to make the best and final decisions for the organization. they do not feel a necessity to involve their sub ordinates. To overcome this challenge, companies need to adopt a participative approach, where employees are involved in identifying, analysing, and solving problems that impact their work. Managers also need delegating work, and support their subordinates to make them self-sufficient to empower their employees. Acknowledging and timely appreciating the contribution make them feel valued and recognized in their work area 3. Lack of clear two-way Communication Employees may not know ways to share their views or opinions or they may not have the confidence to do it effectively. Managers may not listen to, understand, or acknowledge the employee feedback, or they may not communicate the outcomes or actions taken as a result of it. To overcome this challenge, organizations need to establish clear and accessible channels and mechanisms for employee voice, such as surveys, focus groups, suggestion boxes, or forums. Managers also need to improve their communication skills by asking questions, listening actively, summarizing key points, providing feedback, and following up on employee input.\ 4. Diversity and inclusion Another challenge is the diversity and inclusion of employees in the workplace. Employees may have different backgrounds, experiences, perspectives, and preferences that influence their voice and how they express it. Managers may have biases, stereotypes, or assumptions that affect how they perceive and respond to employee feedback. To overcome this challenge, organizations need to foster a culture of diversity and inclusion, where employees are valued for their uniqueness and differences, and where they have equal opportunities and access to voice their views. Managers also need to be aware of their own biases and prejudices, and to seek out and appreciate diverse voices in the organization. An example where a project was identified using Voice of Employee Employee’s biggest requirement is to upskill themselves to sustain and grow in their career. Companies usually expect their employees to work from 40 to 48 hours a week. this is core BAU activities delivery from employees. However, their learning, training and development is a core part for them to deliver better. One of the observations & feedback received from employee in an organization was on learning and development. though company do provide certain specific instructor led trainings. however, the opportunity is availed basis the planned training date and time. Also, there is capping to the participants in session in such sessions. Also, during as there as regular or frequent practice to devote the learning and development time, sometimes when the opportunity via an IJP the employee ends up missing to elevate his role and grade due to lack of such skills Survey was done to collate VOE and it was identified that a regular opportunity and dedicated time is needed for the employees to upgrade their skill set on the regular basis. Second there should be more open platform for the employees to participant and indulge in same to enhance their learnings. Basis the above challenges and identified opportunities, company partnered with Linked in for employees to opt for more and free learning opportunities. Second, every employee’s calendar was blocked for 2 hours per week for training and development which gives them sufficient opportunity to pick one course from linked in and go through it to enhance their learnings. Lastly, learning and development was included as an annual goal for every employee and minimum 30 hours of annual learning was compulsory for every employee so that they can learn, elevate their skill in different areas and scale up to different grades and roles

A key risk indicator (KRI) is a metric that monitor and manage potential risk of an organization. They provide early warning signs of potential issues and its impact on business performance and helps organization take proactive measures to mitigate or manage the risk well in advance. Yes, KRI can be used to manage a process as it will lay down a preventive control mechanism or proactive risk management. It allows organizations to foresee potential threats and take preventive actions. For instance, rather than responding only after regulatory penalties, a financial institution can use KRIs related to compliance activities to identify trends that might indicate future regulatory risks, allowing the institution to amend the policy or procedure leading to risk in advance Key risk indicator, indicates the potential risk and helps us defines the broad areas of focus. On the other hand, Key performance indicator is a quantifiable measure that evaluates the success of a company in achieving its business goals. It provides an overview of how the business is performing at a certain point in time and thus gives a sense of direction way forward and make well informed decision-making. That is why companies prefer KPI over KRI While KPIs help organizations understand how well they are doing in relation to their strategic plans, KRIs help them understand the risks involved and the likelihood of not delivering good outcomes in the future. This means KRIs is just inverse/oppositive to what KPIs is Benefits & limitation of using KRI Purpose of KRI is to identify potential threats that could negatively impact performance. KRIs do not measure operational success they measure vulnerability, offering early detection of risks that could compromise KPIs. For example, while a KPI might track quarterly revenue growth, a KRI would monitor increasing customer churn rates or declining market demand, highlighting risks that could hinder future revenue performance. By defining success through KPIs and potential hazards through KRIs, businesses can align their growth strategies with risk management, ensuring that success is not achieved at the cost of hidden vulnerabilities. KRIs operate in the background, targeting elements that threaten the achievement of business goals. KRIs deal with risk-prone areas such as compliance breaches, market instability, cybersecurity vulnerabilities, and operational inefficiencies. For instance, while a manufacturing KPI may track the percentage of products delivered on time, a corresponding KRI would monitor supply chain disruptions or chance of equipment failures that could delay production. KRIs, focus on the future, offering predictive insights into potential risks that may materialize. They serve as early warning signals, allowing businesses to anticipate and mitigate threats before they escalate. A rise in employee absenteeism, for instance, could serve as a KRI predicting workforce shortages or declining productivity in the near future. KRIs focus on the factors that influence or jeopardize those outcomes. For instance, a financial KPI might track quarterly profit margins, while a KRI would monitor economic downturn indicators, which could signal potential profit declines in the future. KRIs generally draw from a blend of internal and external data sources. In addition to internal data, KRIs might leverage industry reports, market trend analyses, regulatory changes, and global risk assessments. For example, a banking institution’s KRIs might include geopolitical factors or economic forecasts that could influence market stability. This expanded data pool ensures that KRIs account for broader risk landscapes that internal KPIs might overlook. By utilizing diverse data sources, KRIs provide a richer, more holistic view of potential risks, enabling businesses to remain agile in the face of external uncertainties. Conclusion KPIs drive business performance by tracking progress toward goals, KRIs provide the foresight needed to anticipate and mitigate potential risks that could undermine those efforts. Together, they form a cohesive system that measures and protects success.