The Inherent Necessity of Big Data as a Strategic Factor
By Esteban Remecz, CIO, Asia Pacific, ZF Group
Evermore we hear about Big Data in today’s technology publications; in many cases it may sound like another buzz word or yet another marketing initiative from technology solution providers. In fact, in many cases it simply is. However as a result of new technology disruptions, Big Data is gaining an ever increasing strategic relevance.
Today however, the biggest differentiator, Big Data Analytics lies in the industry where companies are focusing on deriving, intelligence by means of optimization or efficiencies and competitive advantage. The added complexity and ever increasing ubiquity with its defining factor ,IoT, and the ecosystem in which the IoT anchor, makes Big Data Analytics as a necessity for business as a value adding differentiator either as a mean to obtain insights and thus actuate on optimizing or improving internally with e.g. employee experience or supply chain, or externally with increased market penetration or improved customer relationships always with the focus on adding efficiencies and revenue by its impact on business.
How Big is Big ?
Whereas by definition Big Data refers to the necessity of evaluating and actuating on the analysis of large amounts of data, there are many practical examples that don’t necessarily need to reach the “Weather Forecast” modeling size to deliver significant and actable insights for cost effective applications. This is the case for the Retail and Manufacturing industries. In these cases; most of the time the association made for Big Data Analytics is in regards to Customer Behavior and Marketing initiatives. However the quickest Big Data benefits may come from inside their own operations which may deliver results before it’s necessary to look for the benefits from sources outside their door.
Quick wins may be made by simplifying and optimizing processes in the logistics and supply chains and at the same time evaluating the production and maximizing their output. By collecting and evaluating structured and unstructured data from the existing internal databases and data warehouses or by collecting logs on specific events, relatively simple analytics can then give insights to conduct predictive maintenance to minimize downtime, optimize warehouses as well as capacity and service planning.
In Today’s World There Is Virtually No Industry or Service Which Could Not Derive a Benefit from Big Data Analytics
In fact in most of these cases Big Data Analytics is nothing else than the next step of the evolution in redressing of BI associated with the requirements of the exponential growth of Data generated by i4.0 and IoT. These disruptors in the Industry make it now necessary to address the aggregation of the data in a way that it translates into aggregated value.
Big Data in the New Automotive Industry of the connected vehicle.
Already before the race of Autonomous Driving had started inside the Automotive OEMs and definitely inside the successful OEM supplier, Big Data was already playing a key role in defining their success.
With the disruption through the megatrends of the Connected Vehicle and Autonomous Driving, the whole automotive industry and not just OEMs is now facing the challenge of appealing to consumers on how to deliver new products, new services based on new technologies all of which at the core, are digital and that generate data at scales that we have never seen before. At the same time the automotive industry is additionally being disrupted by the entering of new players, who in many cases belong to and are top players of digitally native industries. All of which will combine with required infrastructures and ecosystems that will drive the V2X connectivity required to enable the interaction, of the new digitally enabled automotive ecosystems. Based on this factors and requirements, the connected Car Ecosystem Report Forecasts estimated that Big Data and Analytics technology investments in the automotive sector would reach $5 Billion by 2020. This is an estimate that as we progress in time and approach the deadline, could easily be overshadowed if additional factors such as government legislation or other service industries which will be derived from the new technologies become part of the equation.
In this context and compared to the previous examples, Big Data and Big Data Analytics completely takes on new meanings. It is also for this reason that it is no surprise that with the introduction of AI, connected vehicle finds its way as a key player and core element in the evaluation and actuation on the Big Data Analytics value chain. In fact in many cases it will be only through AI and its enhanced analytical, data processing and learning capabilities, that self-driving vehicles will be able to efficiently interact with their surroundings whilst simultaneously making sense of all the data sets continuously being streamed from the vehicle’s on-board sensors.
The shape of their success however will in many ways be linked to how well they are able to manage process, actuate and realize value out of the enormous amount of data. For this a much more robust and mature Big Data Ecosystem will be determinant.
In today’s world there is virtually no industry or service which could not derive a benefit from Big Data Analytics, the key is to make data work with dependable, actable and value adding insights. In the automotive industry the ability of master data and its hidden treasures is now becoming a determinant in the differentiation in the ever increasingly complex competitive industry.
Be it in supply chain, logistics or production optimization, enhanced market intelligence and customer interaction or delivering more efficient and dynamic models for the automotive industry trend disruptors, Big Data is more and more playing an instrumental role as a value adding differentiator.
A key element to succeed with Big Data is to begin with an early adoption sustained with a roadmap reflecting all necessary strategic and budgeting initiatives to deliver the business cases.