In the hype surrounding the Industry 4.0 (I 4), one tends to lose sight of the serious effects it can have on teamwork. The Covid-19 pandemic sorely tested this age-old concept, which has kept organisations improving efficiencies over the last more than sixty years at least.

Work-from-home compelled team members to operate from remote locations, as well as locations from where they could not meet in person frequently, as they were used to. This adversely affected the ‘peer connectivity’.

Organisations depend on collective working for synergised operations. The value chain of the entire organisation is fully dependent on the various value chains actively working in the organisation to serve its customers, viz, Operations Value Chain, Supply Chain, Financial Value Chain, etc.

If anything, to successfully run JIT (Just in Time) type of operations, the organisation needs to co-opt ‘outsiders’, who will work along. In fact, over the years, the ‘Horizontal Integration’ even co-opts competitors into the value chain, through toll manufacturing and/ or meeting short term capacity augmentation to meet order surges.

So far, before the advent of I 4, all operations have been successfully run using strong teamwork, and team commitments.

In fact, in the X Matrix methodology of organisational goals setting and deploying strategy across the organisation, also known as the ‘Hoshin Kanri’ (or catchball) technique, attention is paid to align all individual KRA’s (Key Result Areas) with the various strategic targets.

If this alignment is missing in an organisation, it leads to ‘tunnel vision effects’ where individuals prioritise the achievement of personal KRA’s in preference to organisational goals.

This same is sought to be achieved by the Balanced Score Cards (BSC) system, which has been adopted by many to most Fortune 500 companies, as well as many large Indian companies.

In Navaratna PSU’s, the company signs an MoU with the concerned Minister in charge of the relevant ministry, which is in the form of a BSC.

All companies using the BSC’s for strategy description and deployment, use tools like the ‘drill down’ of goals to the appropriate functional heads, and thence to the individuals, as KRA’s or KPI’s (Key Performance Index).

In deploying teamwork in organisations, presently, TQM tools like quality circles, 5S circles, small group activities, TPM, etc., are being used. In all these efforts, people work together in teams, and identify targets, goals, and ensure that the strategic goals and targets set in the corporate BSC are achieved.

This system, deployed under the umbrella of Performance Excellence models, such as, the Malcolm Baldrige model of the USA, or the EFQM of Europe and other equivalent models (for example, the CII-EXIM model, the Rajiv Gandhi awards, Golden Peacock awards in India) have enabled organisations to deliver customer satisfaction and delight.

How does this system get affected by the I 4?

A very important question, as the disruptive effects of artificial intelligence (AI), internet-controlled manufacturing, machine learning (ML), and, in general, algorithm driven systems for manufacturing, have a tendency to replace human efforts by machine efforts through embedded software and electronics.

Some processes in the past have already been converted to the I 4 approach.

A great example is the SCADA (Supervisory Control and Data Acquisition) system, which collected data from many machines distributed all over the factory.

From a central console, these data were electronically collected, analysed, and instructions given by computers, which used algorithms to make decisions, which were conveyed to the various machines.

In I 4, such consoles will be used at two or three levels in a hierarchy, to control and deploy distributed systems of manufacturing.

In such systems, several consoles, with embedded AI/ML facilitated algorithms, will control the functioning of the distributed manufacturing centres and machines.

Data will be available, and such ‘Big Data’ will be analysed by cloud connected processing machines with humongous computational power.

These practices, to begin with, will be designed, studied and perfected by human teams, but Data Scientists will be leading such efforts, and not team members who operate the machines.

The function of making the machines work well will be taken over by the Data Scientists progressively, and many machine operators may feel a sense of loss and helplessness, as well as think of themselves more as robots than human beings capable of thinking and acting to improve.

Such a situation will lead to an over emphasis on Data Scientists, and a neglect or downgrading of others, especially the shop floor workmen, who were previously involved fully and rewarded and recognised for their special and specific contributions to the betterment of the organisation as a whole.

The feeling that each and every employee, through his KRA/ KPI, which are aligned to the corporate strategy through the BSC system, has a distinct role to play in the profits of the company will be diluted considerably.

This development is not in the same league as the earlier ones—computerisation, automation, where the new technologies were seen more as enablers and additions, rather than replacers.

I 4 will surely be perceived as a ‘replacer’, especially with the onset of Big Data and the world going the e-commerce way through internet connectivity.

Already, the small shopkeepers are feeling the ill effects of the e-commerce platforms, and are trying to evolve new models for their survival.

Now, this same effect will be felt inside factory floors, where AI and ML will take over the functions of the human brain, or, at least, make many workmen brains redundant. This will certainly lead to demoralisation, and, if not handled correctly, will have very adverse effects on the efficiencies being sought by the introduction of the I 4.

So, what’s the solution?

For one, gradual introduction of I 4 should be done.

Second, training of shop floor workmen in AI, ML should be imparted by Data Scientists.

New systems to practice teamwork and continuous improvement should be put in place. These will have to be evolved.

So far, Quality 4.0, to address I 4, is not yet visible. I am not even sure that any effort has been taken up, as the introduction of I 4 has been rudely disrupted by the pandemic for the last two years.

Add to that, the WFH. And, now, the ‘return to work’ and ‘hybrid’ models will have to be reworked.

There is no doubt that I 4 will arrive, but will it bring with it more troubles than the previous ‘Industrial Revolutions’ like I 2.0 (the age of machines), I 3.0 (the age of computers)? Only time will tell.

All that one can now say is that I 4 is a change of at least one magnitude, and not an incremental step. Careful navigation is called for.

R Jayaraman is Head of Capstone Projects at Bhavan's SPJIMR