Workplace Productivity has been a good way to measure the human endeavour for continuously sweating the asset. Productivity was measured in different terms, e.g. output as % of input, Turnover or EBIT as no of times of cost, TAT, volume of products or services sold as no of times of cost, etc. The cost could be just manpower cost for calculating manpower productivity or cost of operations.  In TQM parlance workplace productivity is also seen in  terms of cleanliness, orderliness, and safety. In Total Productive Maintenance (TPM) the workplace productivity was measured in terms of overall equipment effectiveness (OEE). Whatever unit of measurement we considered, numerator drove the top line and denominator drove the bottom line.  From a leadership competency standpoint the Numerator management needs a lot of agility, boldness, experimentation, innovation, and scale orientation. Whereas denominator management needs process discipline, risk analysis, frugality, and waste reduction.

In the past companies used TPM, COPQ (cost of poor quality), business process reengineering, Six Sigma methods, Gemba Kaizen, and product & process innovation to improve workplace productivity. The numerator related productivity goals would be appropriately deployed to sales, marketing, product management, business development and strategy teams to drive the top-line. Whereas denominator related productivity goals would be deployed to production/ operations, procurement/ commercial, and business excellence teams. However, since people were the sole driver of all the above initiatives, their safety, motivation, training & development, interpersonal relation, and recognition were key factors for driving the productivity. 

The third industrial revolution or digital revolution started in the second half of 20th century and kept proliferating till today through digital computers and digital record keeping. With the availability of digitised data, advent of machine learning and Artificial Intelligence (AI) the workplace productivity has transformed in an exponential manner. AI, with the help of machine learning and deep learning, aims at producing smart computer systems that can solve complex human problems faster than humans can do.  AI has not only reduced cost of retrieval and analysis of data but also improved decision making with speed and precision.

AI has the ability to analyse tons and tons of both structured and unstructured data in a very intelligent manner and recommend next actions with the help of chatbots to create a wonderful customer experience. Amazon, Facebook, Netflix all use AI for analysing the customer’s preference and recommending customers their precise products. AI engages customers by asking their feedback and keeps creating the reinforcing loop. Uber, Ola, Airbnb all use AI as their core for ensuring customers’ safety and aligning with their specific needs. AI has the ability to understand the customer journey end to end and keep refining customer’s experience and suggesting ideas for new products and services. The automated customer service has created a virtuous cycle for more and more digitalisation and adoption of AI.  The Indian used car industry, for example, is on its digital spree by creating more and more digital products and services for end consumers and various stakeholders of the ecosystem. These products and services, like price engine, recommendation engine for right cars and dealers, auction platform, finance, insurance, residual value etc have revolutionised the industry and transformed customer experience. All these productivity enhancements have led to investors’ confidence and flooding of funds.

AI can help improve workplace productivity by fostering communication and collaboration among different employees, who may be digital native and newly entering Gen Z, nomadic geeks, women remotely pursuing their second career and expert freelancers. AI helps lessen the search time for retrieving information, creating insights and optimisation of processes. AI has the ability to lessen the preparation for meetings on a real time basis. An executive waiting at the airport lounge can in no time prepare oneself with the necessary information and insights for an internal meeting or a meeting with a customer.  

AI is far more productive than any human being in collection and analysis of data and recommendation of actions. It is gradually replacing the needs of deployment of people who are engaged in any sort of repetitive work. It is also replacing the need for middle management, doing coordination and supervision of jobs. However, human beings will still remain the empowered consumer and creative & emotive contributor to customer experience. With fast changing customer needs & expectations and growing platformization of businesses the nature of employment will keep shifting from permanent to temporary and the skills requirement will keep changing.  So, from a people productivity standpoint continuous training & development and physical & psychological safety  will become ever important.