Table of contentsKey takeawaysCollaboration platforms are essential to the new way of workingEmployees prefer engati over emailEmployees play a growing part in software purchasing decisionsThe future of work is collaborativeMethodology
Vice President and Chief Evangelist of SAP, Shailendra Kumar joined us on the show to talk about Industry 4.0. We had a conversation about how prepared the world is for Industry 4.0 and how businesses of the future will leverage AI and automation.
Shailendra or Shaily is the Vice President and Chief Evangelist of SAP and is on the Advisory Board of Aegis School of Business, Data Science, Cyber Security, and Telecommunication.
A keynote speaker across Asia and Oceania around Emerging Technologies which are also showcased through #TheShailyShow.
With over a quarter of a century's experience in the field of Emerging Technologies like Artificial Intelligence, Machine Learning, Advanced Analytics and Data Science, Shailendra has built upon extensive knowledge of data-driven analytics strategies for revenue growth, cost reduction, marketing and customer behaviour management to drive business outcomes.
Interview with Shailendra Kumar
This section will contain a summary of our interview with Shailendra Kumar. But, if you'd rather listen to Shailendra, our Spotify Podcast is embedded below.
There are different components to this. It includes data, machine learning, IoT, 5G, analytics, blockchain.
Different countries are at different levels of maturity. Some are fairly advanced and some are really lagging behind.
The fundamental requirement for Industry 4.0 is your infrastructure. It's your network. If there is poor or no infrastructure, you won't be able to do anything.
Data is the key to Industry 4.0, but, if due to a poor network, data doesn't flow properly, then there is a huge challenge.
Rule-driven chatbots may not be smart enough. But the smart ones with machine learning are really smart.
While taking a survey, a customer may not be completely honest about his/her experience. But, a chatbot can read between the lines and note the highs and lows during the experience. It can figure out what works for the customer and what doesn't.
These chatbots are not just following an 'If-then- else' rule while answering questions. Thanks to Natural Language Processing, they're understanding the meaning of these questions.
They're understanding the intent behind them. This makes the conversation feel like you're talking to a human, not a bot.
Shailendra says that even at SAP, their largest focus is to automate and make sure that the processes are intelligent enough on their own. They have Machine Learning at every component, that is trying to understand how the process is running and trying to automate it as much as possible.
Machine Learning has even been used in résumé scanning. It can pick up a job profile, understand it, take a C.V. and understand that too. It doesn't just pick keywords, it actually understands the C.V. and matches it with the profile requirements. This makes recruiting phenomenally easier.
If a company functions across countries, there's always the chance of amendments in laws. In such a scenario, you need to make sure that your contracts comply with these laws.
Now there is software that picks the newly published laws, translates them from the language in which they were published and then makes sure that the contracts comply with these amended laws. There's practically no human intervention involved.
We're creating more and more data now that we're working from home. Consequently, the need for a good data flow has increased.
Especially with Zoom meetings, we're generating a lot of data that can be used in the future for learning purposes. And this data needs to be saved. It needs to be stored. Organizations can use this data to train their employees.
With all the technology that is coming, cybersecurity is becoming increasingly important. As more data we use and more technology comes into play, hackers get more tempted.
Cybersecurity is becoming extremely important in such a situation. We need to protect our data and be proactive about it.
We're creating data continuously. With Machine Learning and analytics, we can take that data and treat our customers better.
It's our responsibility to use this data in a positive way. When we collect so much data from our customers, they expect us to understand them better and treat them in a better manner.