SAS will continue to emphasise industry-specific solutions relevant to India: Kunal Aman

What’s your observation on the adoption of new-age technologies in the manufacturing sector?
Historically, manufacturing has been quite conservative in adoption of technology. There has been considerable hype built up around digital transformation and Industry 4.0 in the past few years, but most manufacturers in India are yet to realise the dream, with many of them struggling to even get started. However, with the world clearly moving towards Industry 4.0, and the industry aiming to boost the contribution of the manufacturing sector from 15 per cent to 25 per cent of GDP, India will have no choice, but to take the leap and move along.

Even the government recognises the need for an impetus to push towards India’s vision of becoming a manufacturing hub. The recent budget proposes to encourage adoption and bridging the skill gap in technologies such as AI, IoT, big data, VR and 3D printing. These technologies are central to the themes of factory automation, PLM and the digital enterprise which form the pillars of Industry 4.0. Similarly, the use of robotics and automation is streamlining the supply chain. Used right, these technologies have the potential to boost production quality, lower costs, improve efficiency and time to market and drive customer satisfaction.

Coupled with the low cost of labour, these technologies have the ability to give Indian manufacturing sector the much-needed shot-in-the-arm to compete with their global peers. However, at present, the industry maturity varies widely with some larger manufacturers, especially in automotive, having made significant strides in technology adoption, are reaping the benefits whereas a majority of the small and medium enterprises are yet to put these digital technologies to work.

The need of the hour is clearly to push-up the levels of tech maturity in the industry – but making this happen calls for a mindset shift and the intent to integrate these technologies across not only within their supply chains, but also into the hearts of their businesses.

How is analytics being a critical component of the digital transformation journey in the manufacturing sector?
In today’s world, data is the lifeblood of every organisation and the premise of digital transformation only accentuates the importance of analytics in leveraging the potential of this data. The emergence of new types of transactions and IoT data means organisations are dealing with data flowing at sub-second latency. This data can be leveraged in various ways to support business outcomes.

For example, with machine sensor data that feeds to analytical models, manufacturers can maximise productivity of their high-capital assets by avoiding unplanned disruptions by anticipating their failure. Status dashboards and automatic alerts notify operations staff and managers of impending failure, so you have time to identify issues and fix them – before they turn into costly problems. Manufacturers also struggle with identification of source of defects in manufacturing process and that’s where our advanced analytics and predictive data mining capabilities drive continuous quality improvement and can dramatically reduce scrap or rework.

Demand management is another area where the use of analytics can be vital to ensure supply plans are aligned and inventory is optimised to match fluctuating customer needs in near real time. Analytics can be effectively leveraged to translate demand signals – like seasonality, price and promotions into a more effective, market-driven response.

With the rise of connected factories, to benefit from the promise of IIoT (Industrial internet of things), data, manufacturers can now shift from batch analyses in traditional data centers to real-time analytics embedded in the stream of data itself.

Similarly, smart cars and connected vehicles are gaining traction. The fusion of analytics with sensor data is allowing manufacturers to bring new digitally delivered services and conveniences to consumers, while enabling unprecedented levels of vehicle quality and reliability.

Digital transformation, for me, mean two things – its unlocking value in your business processes and secondly, creating new experiences for customers’ and data and analytics is very much at the core of both these aspects. This is one of the reasons, customers look at SAS to help them create an analytical centre of excellence.

How is SAS constantly innovating to cater to the industry’s needs? Please elaborate on some of your key offerings.
With over 40 years of analytics innovation, SAS is a trusted analytics powerhouse for organisations seeking immediate value from their data. We regularly invest over 25 per cent of our revenues back into R&D to ensure our technologies stay ahead of the curve. We have a deep bench of analytics solutions and broad industry knowledge that we put to work for our clients.

The SAS Platform enables our customers to orchestrate their entire analytics journey – from data to tangible results. SAS Viya, which is part of the SAS Platform, enables everyone – data scientists, business analysts, developers and executives alike – to collaborate and realise innovative results faster. It is a scalable, cloud-ready and open platform that supports programming not only in SAS, but also in other languages like Python, R, Java and Lua which has been a big shift for us.

We have flexible licensing and pricing options to accommodate our customers’ current and future needs. A lot on the cloud front is changing; we are bringing in a comprehensive range of cloud offerings and deployment patterns in public or private clouds. We also work with major cloud providers such as Amazon, Microsoft, Google and others today to streamline SAS deployments in public clouds.

We recently announced that we would be investing US$ 1 billion in artificial intelligence in the next three years. This commitment builds on our already strong AI foundation, which includes advanced analytics, machine learning, deep learning, NLP and computer vision and we have specific products such as Visual Data Mining and Machine Learning, Visual Text analytics that address each of these areas. Our clear intent is to marry human creativity with our investments in AI to unlock new possibilities.

We are seeing a strong uptake on our solutions for IoT – our edge to enterprise platform manages diverse data – whether it is in motion, on the edge or at rest. Connecting with customers through IoT mean new opportunities and service offerings – whether it is early warning signals, service parts optimisation, suspicious claims or warranty analytics.

How do you see the Indian manufacturing market, as compared to the global market? Do you see any similarities or differences?
While the Indian manufacturing sector has been improving steadily, along with the government push with initiatives such as Make in India have strengthened our position as a global manufacturing leader in recent years, the fact remains that Indian manufacturers still lag their global peers by a big margin. The gap remains across infrastructure, automation, technology adoption and most importantly in mind-sets.

Our large number of small manufacturing firms also create hurdles to productivity as enterprises are unable to raise capital to invest in much needed machinery. Similarly, upgrading skills and know-how is difficult for such firms. These are some of the reasons, among many, India’s annual manufacturing labour productivity stands at US$ 6,000 per employee, while China’s is over US$ 60,000. So at this point, it’s probably easier to point differences than similarities.

There are steps being taken both by industry bodies as well as the government to bridge this gap. However, the solution to these challenges are neither easy nor quick, so the progress will be slow. It will require the government to continuously work on creating a favourable investor climate, industry bodies to work with the sector and government to create upskilling opportunities and the larger, more mature manufacturers to lead the way in these transformations for India to begin exploiting its potential.

Could you share some of your customer success stories?
Asian Paints is using SAS to make the right product available just when the customer needs it, and transforming demand strategy at Asian Paints to reshape its consumer focus. The key objective at Asian Paints was to leverage forecasting and optimisation analytics to enhance its processes and achieve greater accuracy in demand planning. Streamlining supply with demand work stream was made possible because of the embedded layer of analytics in the planning ecosystem.

Honda uses SAS Analytics to turn service repair data into cost savings, and the company has improved warranty claims and forecast usage for parts and services. The objective here was two-fold: To develop stronger bonds with customers by ensuring dealers have in-demand parts available for customer repairs as well as enable the claims group and field personnel with the ability to quickly and accurately identify claims that were incomplete, inaccurate or non-compliant.

Lockheed Martin is revolutionising aircraft maintenance with the SAS Platform. The company uses AI, IoT and advanced analytics to predict when parts will fail, keeping more aircraft airborne for vital missions worldwide.

How do you plan to further leverage the opportunities in India?
With digitisation finding a place, both on the government as well as corporate agendas, the rate at which data is getting generated is just exponential. All this data is a potential goldmine for organisations and government agencies alike. In addition, with mobility becoming all pervasive, India’s AI and analytics market presents an interesting opportunity for organisations. Consequently, we see a strong market potential in India.

SAS India is uniquely positioned to help organisations turn large amounts of data they are churning out into knowledge they can use. SAS will continue to emphasise industry-specific solutions relevant to India, building on SAS’ strong foundation of AI, analytics and data management technologies. For example, helping supply chain optimisation, asset performance, omni-channel marketing, quality analytics or demand forecasting in manufacturing.

Our aim is to simply help customers transform their data into intelligence and make better, faster business decisions.