SKSri Krishnan: We are a core Engineering organization with deep Automotive domain knowledge. We have expertise in all the Automotive fields like Engine management, Automotive safety systems like Anitlock Breaking, Electronic Stability, Airbag, Driver assistance systems, Infotainment ,Telematics systems and Automotive Diagnostics. Leveraging the competencies that we have built over years as the Engineering Offshore Development Centre of Bosch, our approach is to focus on “Engineering Analytics”. We have identified this as a niche area, since we see huge benefits that Engineering analytics can bring in. We are applying analytics in house and with Automotive OEMs for engineering and manufacturing. Though we started with focus only on Engineering Analytics, we find that many use cases require end to end analysis of the value chain. In the context of the technology trend IoT (Internet of Things), where everything will be connected; we envisage more and more end-to-end solutions. Analytics will be part of the solution offering, rather than seen as a separate service. We are building such systems already.
AIM: What is your approach to face the challenge of meeting the needs of so many clients across vast geographies with limited resources?
SK: We do not see it as a major challenge, since we leverage the presence of Bosch in all geographies for customer engagement and interface. We have collaboration with Bosch Corporate research teams in Germany and USA. We are able to scale up the Analytics team in India supported by right domain skill.
AIM: What are the key differentiators in your analytical solutions?
SK: About data and algorithms, all problems could be grouped into few classical solutions. It is the domain knowledge that differentiates real insights that add business value. As mentioned, we have profound domain knowledge which makes the difference. For example JD Power Initial Quality Study 2013 report says that majority of problems experienced by owners with their new vehicle in the first 90 days of ownership are design-related rather than manufacturing defects. We could validate this with social media analytics and connect with engineering design. We are able to narrow down customer sentiments to feature and function level. We are able to trace field quality issues to a specific slice in the product life cycle.
We see analytics as part of a system solution. We have in house expertise and develop complete products with Electrical hardware, mechanical engineering teams and manufacturing. We have IT and ITES teams who provide elegant solutions for Engineering and manufacturing organizations. We are able to offer end-to-end integrated solutions from sensor network, M2M systems to aggregate, Data collection, validation and Integrated Analytics with existing IT systems. This is a unique combination compared to typical Analytics solution providers, whose heritage is IT systems.
AIM: Please brief us about the size of your analytics division and what is hierarchal alignment, both depth and breadth.
SK: The core Analytics team consists of about 40 people, and additionally solutions team as a matrix team consists of about 100 people. We cover all the major verticals.
AIM: What is the next steps/ road ahead for analytics at your organizations?
SK: We plan to expand further in to other domains, for example Healthcare and Energy. Already we have acquired domain experts on these topics and started with few use cases. We will continue with automotive sector and reach out to more customers. We see Analytics as an integral part of any offering that we make in future.
AIM: What are a few things that organizations should be doing with their analytics efforts that most don’t do today?
SK: The importance of domain expertise is undermined by many Analytics alone teams. We find that many of the customers do not appreciate the value of analytics, without a concrete use case that makes real business sense to them. This holds good even for in house solutions. To understand the customer problems and make value proposition, Organizations should focus on building up analytics teams backed with domain knowledge.
AIM: What are the most significant challenges you face being in the forefront of analytics space?
SK: One of the major challenges is to convince middle and lower management that Analytics helps them. Many of them are either skeptical due to deep conviction of their own established spreadsheet based methods or they see a threat of being seen as not effective, in case big improvements happen as a result of analytics.
Coming out with good use cases is a team work. It involves collaboration between the analytics team, domain experts, actual users and management. Even if one of the stakeholders is not engaged, it could affect the speed or the extent of potential benefit itself.
AIM: How did you establish Analytics Business area?
SK: We had seen the technology megatrend of Analytics picking up momentum. We could clearly see the benefits that Analytics can bring to large MNC like Bosch and also what we could offer to others. Being an offshore Engineering centre of Bosch, located in India we have the benefit of leveraging on the in house domain expertise and eco system to scale up. We started a small group with the culture of “Startup” within our offshore centre. To get the right level of focus and attention, the team directly reports to me, one of the Business Unit Heads. Significant investments have gone in the last two years to build up a competent team, infrastructure and proof of concepts. We are able to see the results in terms of real business benefits.
AIM: What do you suggest to new graduates aspiring to get into analytics space?
SK: Do not jump in to the bandwagon just because reports show that there are so many thousands of jobs in the analytics space. Understand the field; check if you are really passionate about it. Develop practical experience in any of the domains first along with specializing in Analytics. Without such understanding, pure analytics knowledge will be a limitation.
AIM: What kind of knowledge worker do you recruit and what is the selection methodology? What skill sets do you look at while recruiting in analytics?
SK: We recruit at various levels from relatively newbie to expert. We look at the level of understanding and system knowledge on the problems that they have worked. We evaluate the candidate’s ability to comprehend and get an overview of any new problem and look for Analytics oriented solutions. The approach to the problem and ability to think of alternatives is vital.
AIM: How do you see Analytics evolving today in the industry as a whole? What are the most important contemporary trends that you see emerging in the Analytics space across the globe?
SK: The industry is evolving. Lot of interesting use cases, visualizations and business benefits are published. There is lot of expectation on Big data along with IoT (Internet of Things). Open source adoption is gaining momentum. But strategy roadmap and systematic adoption in large organizations is still lacking. Overall it is an opportunity space.
AIM: Anything else you wish to add?
SK: As a country, India has got great minds. We are well known for our inclination to Mathematics and specially statistics. But in the global scenario, our thought leadership is not visible enough. If we take Analytics space, it would be worth pondering how many papers from India get published in reputed international journals and get citations. We cannot be satisfied with the volume of the workforce and revenue generated, but value created in advancement of technology.
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