Industrial Automation Magazine India

Too much data without knowing how to use it is detrimental

Published on : Friday 01-07-2022

Dr Pradeep Chatterjee, Head – Digital Transformation, TML Business Services Limited.

The pandemic is nearly behind us, but the effects on industry will last longer. What are three digitalisation strategies that companies are working on based on lessons of the last two years?
Definitely the pandemic has taught us several lessons, which helped in expediting adoption of digital technologies by organisations. Organisations are focussing on the following:
(a) Supply and demand forecasting
(b) Adopting collaborative platforms for hybrid form of working, i.e., combination of working from home and office, and
(c) Automating processes with Industry 4.0 and now Industry 5.0 technologies to reduce human dependencies.

For so many Indian companies who are not fully into Industrial Revolution 3.0, is there any urgency to move towards digitalisation?
Industrial revolution 3.0 is mostly about automation with CNC and PLC controls. Though Industry 4.0 looks like next in sequence but in reality there is no dependency to follow this in sequence. Industry 4.0 deals with capturing data, which is required for analysis and taking decisions. If industry 3.0 is implemented, much of the data points can get captured from the CNC or PLC controllers already deployed. Alternatively they have to put required sensors to capture data for industry 4.0. But having digitalisation can help in better analysis and prediction, which has become need of the hour in such dynamic business conditions. Moreover, personalisation and experience enhancement of customers is driving the market, which is not possible without digitalisation. Thus all organisations should move towards it.

For many companies, the challenge is in moving from pilots to deployment at scale. What is the way forward?
I think the challenge for deployment at scale comes on account of speculations if a particular digital solution will give the desired benefits. Else if it is clear on return on investments (RoI) within acceptable time limit, there will be no hesitation to implement same. So choosing the right pilot becomes important and critical to the success. The pilot should be chosen as such which should have clear RoI demonstrable, which is convincing. Then deployment at scale will be smooth flow.

There is so much work going on in the area of Data Analytics. What about the effort to get real time data directly from machines?
Too much data without knowing how to use it is detrimental – so all data analytics might not require real time data from machines. Lot of analytics can be done through edge computing when you need not put in efforts to collect all machine data in real time to a server. Getting data in real time is expensive and hence segregation of what is required real time and what can be collated in batches is important. Also getting data in real time has challenge in terms of connectivity of the shop-floor machine to servers. So while intents are there it involves lot of investments and efforts to make it happen. So organisations look for compelling RoI to make such investments. However if the problem statement is addressed through edge computing all data is not required to be brought to server either in real-time or in batches.

Many niche and custom solutions are being attempted for connecting legacy machines, what about long term serviceability?
It will be difficult to find a single solution to connect all legacy machines and hence custom and niche solutions will be required. However, from long term serviceability each organisation needs to define certain technical standards, which act as guide-rails for development of custom solutions.

Is it too early to talk about standards and regulatory guidelines for collection, storage and access to data?
As I mentioned in my previous response, certain standards can be set by organisations for collection, storage and access to data. Developing standards and regulatory guidelines might be desirable but difficult to achieve at this stage.

Digital transformation is deemed to be necessary for companies to become part of the big global supply chains. Are there already such requirements by big buyers as a condition to become their suppliers?
There are mostly guidelines and pre-requisites given by big buyers to get enrolled as suppliers which includes IT platforms and system integration requirements. Some part of the transactions also needs to be performed in the buyers’ system either through manual transactions or through integrations for seamless flow of information.

How could Digital Transformation help companies to cope with the supply constraints of recent origin – for example electronic chips, for example other shortages arising out of political events in Europe?
Digital transformation can support organisations in such situations in the following ways:
(a) Prediction of such an event likely to happen to take corrective action in time
(b) Identifying potential suppliers globally, and
(c) Optimisation of supply sources and routes in times of crisis which will ensure supply in best possible time as well as keep some control over cost.
 
Dr Pradeep Chatterjee is Head – Digital Transformation & Experience Management Business, at TML Business Services Limited. He has worked in technology innovation, strategy development and deployment, business relationship management and translating concepts to innovation and business opportunity through forecasting technology trends. 

(The views expressed in interviews are personal, not necessarily of the organisations represented)