Robert Bosch Engineering and Business Solutions (RBEI) is putting a lot of focus on leveraging the power of data and so is working on data analytics tools. Sri Krishnan, Vice President, RBEI tells that its data analytics offering has an entire range of solutions from data gathering, modeling, validating and deployment in the real world environment. With the advent of Internet-of-Things, data analytics has become an integral part of any connected eco-system. Its team is actively creating such end-to-end IoT solutions for business domains like mobility, industry 4.0, smart homes, healthcare, agriculture, and energy, etc. Excerpts:
What are the different projects you are handing at RBEI?
Big data is one of the key forces that has launched Bosch as a strong player in the connected world. After all, data is the new oil of the global economy. We identified the megatrend and incubated a Data Analytics team early enough to prepare ourselves for this wave. Initial pilots were done on the internal projects in manufacturing and engineering. Since then, some of the business cases we have worked on include reduction in claims by processing warranty and quality data, predicting remaining useful life of vehicle components, real time detection of anomalies on production line, preventive maintenance of enterprise assets, sentiment analysis on social media data, to name a few.
Advancement of machine learning helps to solve many more complex problems. This has created a thrust in adoption of data science in all business areas across Bosch worldwide.
What is RBEI’s expertise in data analytics? Do you have any examples?
Our expertise in offering valuable solutions using data analytics comes from the vast domain knowledge in the business areas that we already operate in. Our key areas of expertise lie in understanding the business context of big data generated from sensors, machines, vehicle ECUs, diagnostic tools, social media platforms etc. The aata analytics offering has an entire range of solutions from data gathering, modeling, validating and deployment in the real world environment. With the advent of Internet-of-Things, data analytics has become an integral part of any connected eco-system. Our team is actively creating such end-to-end IoT solutions for business domains like mobility, industry 4.0, smart homes, healthcare, agriculture, and energy etc.
What are the most significant challenges you face being in the forefront of data analytics space?
One of the key challenges is changing to the big data approach of working across boundaries. Creating valuable use cases involves collaboration between Analytics team, domain experts, actual users and management. Even if one stakeholder is not engaged effectively, it impacts the speed or the extent of potential benefit. We address this issue by top management sponsorship, orientation programs to create awareness, annual events to showcase state-of-the-art data analytics, reward programs etc.
Another challenge is that the Data, though available in huge volumes, is not standardized across domains and use cases. We are working on standardizing the data collection methods for various classes of problems. Also the data maturity is not uniform across the value chain e.g. Field data, Point of Sales, Manufacturing, Design, Supply chain etc. to derive deeper insights. We systematically establish data culture across the organization to solve this.
Additionally, data ownership for either protection of data for privacy or competitive advantage, limits the potential of the solutions. More value can be generated if the data is shared across industry like in the open source community.
What are the key differentiators in solutions offered by RBEI?
We have ventured into aata analytics with a vast domain knowledge in mobility, industrial technology, consumer goods and energy verticals. Valuable insights can only be derived when there is domain knowledge in addition to access to data and competency in data analytics. For example JD Power Initial Quality Study 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 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.
Automobiles are evolving into connected mobility solutions, manufacturing plants are getting smarter and automated, and social media is disrupting business models. The boundaries between the embedded systems and IT systems are fading. We have vast experience leading this digital transformation. That gives us an edge over a typical Analytics solution providers whose heritage is IT systems.
How will this trend impact future of businesses?
It is estimated that the world’s digital data doubles every couple of years, while the cost of storage is coming down. With increasing computational power we are able to build better machine learning models and deploy it in real time systems.
Every organization need to define digital transformation strategy. Big data analytics will evolve further through Machine Learning and Artificial Intelligence to create larger business impact.
All Bosch products will be connected to leverage aspects of analytics, machine learning and artificial intelligence. We see similar trends in any industry.
The ones quick to embrace the algorithm economy will survive and stay relevant for future.