Industry 4.0 revolution calls for enterprise analytics
By : Pravin Vijay
Vice President-Marketing
We are at the verge of a technological revolution that will fundamentally change the way we live, work and interact with one another. The scope and complexity of this transformation is such that its impact is felt upon all stakeholders of the global polity, from the public and private enterprises to academia and civil society.
The Fourth Industrial Revolution – Industry 4.0
The First Industrial evolution gave birth to the modern factory, with the mechanization of textile industry, which used water and steam power to mechanize production. The Second Revolution used moving assembly line that ushered in mass production using electricity. The Third industrial revolution, was digital – applied electronics and information technology to automate production.
Fourth Industrial Revolution or Industry4.0 is conceptualised as an upgrade of the Third revolution. While the Third Industry Revolution focused on the automation of single machines and processes, Industry4.0 focuses on the end-to-end digitisation of all physical assets and is characterized by seamless integration of all entities – machines, systems, people, and so on.
What will change – on consumer side and on enterprise side?
The digitalisation, and digitisation as part of industry 4.0 create new ways of serving customer requirements and many enterprises see it as significant disruption of existing industry value chains.
Tectonic shifts are already visible in consumer behavior and needs as they move towards the digital world. This will force enterprises to change the way they design, market, and deliver products and services.
Industry 4.0 impacts enterprises in four main areas—namely customer expectations, product enhancement, collaborative innovation, and organizational forms. Customers are at the epicentre of the business with focus on improving how customers are served. Physical products and services, can now be enhanced with digital capabilities that increase their value. The digital economy is going to be driven by products that are created leveraging the information asset. New technologies will make such assets more durable and resilient, while data and analytics will transform how they are maintained and used. The need for enterprises to stay relevant and differentiate on customer experience will demand new forms of collaboration for business.
How enterprises are gearing up for digital transformation?
Most of the enterprises are digitising essential functions within their internal operations, as well as with their horizontal partners along the value chain. In addition, they are enhancing their product portfolio with digital functionalities and introducing innovative, data-driven services.
Data fuels Industry4.0 revolution; hence the capability to do data analytics is the prerequisite for enterprises to thrive in digital economy. Enterprises are building processes and adopting technologies to use data analytics in their decision-making not only at a strategic level, but more importantly on an operational level. Many enterprises have established dedicated data analytics functions, either on a corporate level or on a business unit level to remain close to the operational business.
Both the developed and the developing markets are striving to gain through Industry4.0, however approaches vary. In countries like Japan and Germany, enterprises focus more on digitising internal operations and partnering across the horizontal value chain. With high investment in technology and employee training, they view their digital transformation primarily in terms of gains in operational efficiency, cost reduction and quality assurance. Enterprises in the United States of America invest more heavily in developing disruptive business models, with focus on rapidly digitising their product and service portfolios. The labour intensive countries like China are more interested in automating and digitising manufacturing and production processes. Across these approaches, what lies common is the customer-centricity.
Why analytics is a key enabler for enterprises in their transformation journey?
As customers become centre of the digital business and ecosystem, there arise an increased need to understand customers more holistically in order to serve them better, and more importantly, in a given context. Customer experience in digital age is now a sum total of all those contextual experiences. This is why enterprises need to think beyond historical data based Business Intelligence. They need to have capabilities for advanced analytics to derive deeper insights and accurate foresights as well as real-time decisioning to act upon them quickly.
Huge amount of data that is generated with end-to-end digitisation and integration, brings little value without the right use of analytics techniques to provide insights at the point of decisioning itself. It will in turn enable companies to create personalised and more contextually relevant products and services, which usually generate significantly higher margins than generic offerings.
Enterprises use data to drive decisions so as to control and improve their overall business planning and operations. To succeed, enterprises will need to use data in predictive, forward-looking ways that make sense of market developments and customer behaviour to improve products and develop new products and services.
Differentiating new age analytics vs traditional analytics
Traditionally analytics was conceived as a tool that could produce and capture a larger quantity of historical data to discern patterns for improving internal business decisions.
Sophisticated modelling capabilities, and functionalities like simulation and optimisation make advanced analytics more of a trouble shooter tool than a reporting tool. The techniques used by advanced analytics are more future oriented. For example, a predictive model can help to predict which customers are going to churn.
The fundamental difference between traditional and advanced analytics, is in the process followed to design and solve a business problem. In traditional analytics, the analysis is typically built to be repeatable. The types of information analysed and the format in which the information is presented is predefined. The advanced analytics techniques uses a set of analysis and data mining to gain business insight. It is more proactive and adhoc as compared to traditional analytics.
Data used in traditional analytics is more structured. Reports based on historical data is used by enterprises to understand operational performance. Advanced analytics on the other hand helps enterprises to capture unique behaviour of each customer enabling personalisation of marketing activities and improved marketing ROI. Also advanced analytics has the capability to use unstructured data such as those from social media providing enterprises with access to real-time information. Thus organisations can monitor market sentiments and effectiveness of marketing campaign and also improve their product design by analysing social comments.
Enterprise analytics: Leads to business agility and transformational benefits
Things happen at the blink of an eye in the digital world. Enterprises who are agile in responding to the dynamic market and customer needs are going to have a decisive edge over the others. Hence for digital enterprises, the ability to instantly digest data, derive insights and put them into decision making frameworks and workflows is what will make an enterprise analytics infrastructure stand apart from the current tools and technologies. Having right insights at the right time help enterprises to not only identify, but also make use of possible avenues for enhancing customer experience, operational efficiency and even business and product innovation.
An analytics platform that can not only accelerate data to value but also do it most efficiently is one of the critical technology elements that will drive enterprises forward through this demanding industry4.0 revolution phase to gain transformational benefits.