Performance Management Through Machine Learning

In the proposed paper, we are focussing on Performance management (PM) - is a process of ensuring that set of activities and outputs meets an organization's goals in an effective and efficient manner. Performance management can focus on the performance of an organization, a department, an employee, or the processes in place to manage particular tasks.

“Performance leads to recognition. Recognition brings respect. Respect enhances power. Humility and grace in one’s moments of power enhances dignity of an organization”. Everyone in the world today wants to make an impact, want that people should remember them for their achievements and great contributions. But all these things can be only possible if the people are given chance. Chance to work, chance to show their skills, chance to get their desired project, chance to work or operate in a way they want. And all these chances can be possible if we keep right person on the right job. Here is where Performance management comes in picture. Performance management starts right from the recruitment of an employee or a candidate as we may say or call them for the right job at the right time. It remains in process since candidate walks in joins institution-works inside-achieve the desired goals-get promoted-make addition to companies and his own career. Companies spend a lot of capital in managing its HR capital. As said by Nagavara Ramarao Narayana Murthy 'Our assets walk out of the door each evening. We have to make sure that they come back the next morning.' If we want that our HR should be back to our office, we need to create our policies in a way that they are:

1. Transparent
2. Encouraging
3. Supportive
4. Updated
5. Competitive.

What is Performance Management?

Performance Management process is a systematic process of managing and monitoring the employee’s performance against their key performance parameters or goals. It is regarded as a process for driving the individual and organizational performance management. Often people misconstrue performance management with performance appraisal. However, performance management is quite different then performance appraisal.

The purposes of the performance management system are as follows:

1. Feedback Mechanism: The purpose of performance management system is to develop a systematic feedback mechanism. It creates a pathway through which the employees become aware about their contribution in the organization in terms of performance. It also conveys the employee about the improvement required in the performance to meet the set standards.
2. Development Concern: It addresses the development issues in the organization. It recognizes the skill and knowledge development required in the organization and facilitates the training programs which are appropriate.
3. Documentation Concern: It creates a data base for the organization in which all the information about the employees is collected. The information about the performance level, skills, knowledge, expertise and regular rewards received by the employee is maintained in this data base.
4. Diagnoses of Organizational Problems: The up and down in the performance of the employee is recorded using performance management system. This record helps to diagnosis the organizational problems. It provides idea about where the work is going wrong and what improvements are required to improve the performance status of the organization.
5. Employment Decisions: Based on the performance management records various important decisions are taken by the management. The decision includes arrangement of training and development programs, promotion, increase or decrease in compensation, hiring decisions and many more.

Performance Management Feedback

Performance feedback is the most important part of performance management system. It is used by the organization in the following ways:

• Areas to Improve: On timely basis the management and the supervisor provide the information to the employee about the areas in which they can improve their performance. It includes tips, ways and coaching for performance improvement.
• Game Plan for Improving: Motivation and direction is provided through feedback in order to create a game plan to improve performance.
• Achievements and Accomplishments: In performance management system, feedback includes both positive and negative information about employee performance. Manager can declare the achievements and accomplishment of the team member in public meetings or on the common communication platform to motivate the performing employee. A one-to-one meeting is suggested to convey the negative feedback to the employee.
• Attitudes and Behaviours: The attitudes and behaviours of the employee are also addressed during the performance management. Through performance feedback the managers put forward the favourable behaviour expected from the employee to make a team work success. The upbeat attitude of the employees keeps the organization thriving and inspired.
• Goals for Next Year: In the yearly feedback meetings the managers discuss with the employee about the upcoming challenges and work responsibility. New goal and objectives are set for the employees for next financial year. The standard performance expected for the employee is also conveyed in the performance feedback meeting.

Now as all of us now have a little bit understanding of performance management and how it is helpful for any organization. One can now head straight about a brief understanding of Machine learning or artificial intelligence as they are.

Artificial Intelligence

Refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving. The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal. When most people hear the term artificial intelligence, the first thing they usually think of is robots. That's because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth. But nothing could be further from the truth.

Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the simplest to those that are even more complex. The goals of artificial intelligence include learning, reasoning, and perception. As technology advances, previous benchmarks that defined artificial intelligence become outdated. For example, machines that calculate basic functions or recognize text through optimal character recognition are no longer considered to embody artificial intelligence, since this function is now taken for granted as an inherent computer function. AI is continuously evolving to benefit many different industries. Machines are wired using a cross-disciplinary approach based in mathematics, computer science, linguistics, psychology, and more. Norvig and Russell go on to explore four different approaches that have historically defined the field of AI:

1. Thinking humanly;
2. Thinking rationally;
3. Acting humanly;
4. Acting rationally.

The first two ideas concern thought processes and reasoning, while the others deal with behavior. Norvig and Russell focus particularly on rational agents that act to achieve the best outcome, noting 'all the skills needed for the Turing Test also allow an agent to act rationally.' 'AI is a computer system able to perform tasks that ordinarily require human intelligence... Many of these artificial intelligence systems are powered by machine learning, some of them are powered by deep learning and some of them are powered by very boring things like rules.'

While using AI an HR manager could collect the information of the employees wherever and whenever required. They don’t have to wait or to take permissions from various heads and authorities in between which can create lag in decision making. Eliminate all the common psychological biases associated with performance reviews – there are many psychological errors that are made in a decision making like:

• Favouritism;
• Bias with logical fallibility;
• Bias with fatigue;
• Unconscious Bias;
• Language Bias.

Reducing gender Parity – AI is a rational decision maker software; it does not have a soft heart for female or strict rule for male or vice versa. It works on data, performance-oriented skill sets, key points which are already fed to the software in the starting of the process. It does not support consideration like gender, race, ethnicity, nationality. It rather considers things like assessing performance, experience, last salary drawn etc.

Cognitive Supporting Decision Making – It can work out and decide that whether vacation request can be acknowledged or not, in places like call centres it can tell about the mood with which a caller is working based on his last calls attended, and is that a proper way or not.

Team Trainings - These kinds of information are helpful for any manager to understand that whether his team is doing good and is on right track or do they need some updating with the project or the process.

Automation of ‘Repetitive, Low-Value Add Tasks’ - It helps by not spending time on things or tasks like Onboarding, providing place or laptop rather doing more strategic things like value adding, mentoring and providing timely feedbacks.

Smarter People Analytics – HR will try and understand how to analyse and find innovative ways to find right candidate for the right job.

Identifying Employees on a way out – It can track and tell if employee is planning to head out by tracking emails, key strokes, surfing etc.

Peer group Assessment - People are assessed not to the set standards but they are compared with work of a fellow employee, which is more or less a biased comparison in more than one way.

Personalized Employee Experience – An AI can help a new joinee in knowing people and can provide suggestions for required or desired trainings sessions.

Conclusion

Only 6% of the organizations think that their performance management process is worthwhile. They have started moving away from their line of assessment technique, as they find them limiting or because the results don’t match up with the choices, they personally have. As the world is changing, organisation have become complex as well as large and even. And even if they are small, they usually are connected with number of other organizations to fulfil the remaining skill set. As the life of any skill set is getting shorter than any other time therefore it is very important that we are always backed by a technology which provide real time answers about where an employee need to work extra. There are various ways in which AI benefits the local HR like collects information seamlessly from multiple sources, enable the managers to extract insights from collated information in real time; therefore, AI helps a lot to managers in this regard, managers can have real time data and too quantitative, without any human intervention so that the decision can be made on actual numbers and with full 360 feedbacks.