Best data-driven decisions made with irrefutable analytics: Persistent Systems

Persistent Systems is a global solutions company delivering digital business acceleration and enterprise modernization for businesses across industries and geographies. It provides digital platforms and solutions, and software product engineering.

Akshay Chitlangia, Principal Technology and Solution Consultant – Data and Analytics, Persistent Systems Ltd, tells us more. Excerpts from an interview:

DQ: How can Make in India be embraced with the use of data analytics?

Akshay Chitlangia: First, as the pandemic has shown the world, relying any one country – particularly those that aren’t open societies – is ill advised. We’re seeing industries in countries around the world fundamentally rethink their supply chains.  Make in India has brought about a focus on industries such as Defence, Aviation, Banking, Insurance, Pharma, Medical Devices, Telecom/ Broadcasting. Each one of these industries is highly information-intensive in nature, both while developing and manufacturing a product/ service as well as while it is in use.

Basic analysis can start with identifying the various hundreds of components/ sub-assemblies being imported, tracking them back to their origin and validating the subcomponents. One can then explore the feasibility of moving the production of each of these into various State Industrial Parks that may have the right kind of tooling as well as economic incentives to support a technology transfer and manufacturing. At a large scale, such decisions are best data-driven and made with the support of irrefutable analytics.

During the prototyping phase, virtual ideation and testing can be done, reducing the time to conclude on a feasible design, and ensure the defined objectives of cost, performance, production scalability etc. are achieved. During the manufacturing phase, monitoring of operations, defect testing, and feedback integration for further optimization can be done. Analytics can further help an organization identify a job schedule for the highest utilization and lowest cost, to make them more competitive in the global scenario.

Beyond this, analytics can help in out-reach towards customers and enabling them on purchase and usage of the goods/ services. Finally, user feedback on the performance of goods and services can be incorporated back into the decision-making process, allowing for more improvements.

DQ: How can analytics streamline operations and improve processes for Make in India?

Akshay Chitlangia: The operational analytics is very well known today in India, as we do a lot of this for several enterprise organizations across the world. This involves the complete process of data collection, data cleansing, data mining, analytics towards process and operational KPIs and creating reports and dashboards. What is emerging today is the use of Artificial Intelligence to find patterns, aberrations, etc., to provide inputs for decision making. These can be reactive and descriptive analytics for existing decisions, proactive analytics that can be prescriptive and predictive for upcoming decisions.

The top areas where such work is currently being attempted are Machine Behaviour and Maintenance, Quality Control, Supply Chain Optimization, Health & Safety Improvement etc. Just think of Analytics as the enabler to answer the various regular questions business leaders may have while Making in India. The only limiting factor is the vision and availability of digital data.

DQ: When it comes to improve internal processes, how can data analytics play a major role?

Akshay Chitlangia: There are several types of internal processes for a business, such as sales andmarketing, finance and accounting, IT, quality excellence and service delivery, HR, etc. All organizations that seek to Make in India will have these processes at some scale aligned with their business. These processes are highly technology-enabled at present with cloud-based services available for consumption.

Further, each process can follow generalised best practices, however, for maximum efficiency, the business should adopt the best practice to their needs. Analytics can play a crucial role in this adaptation and optimization by tracking, predicting KPIs, using machine learning to automate non-critical tasks and provide suggested options for critical tasks. In summary, consider Analytics as something that can support operational resilience and operational excellence.

DQ: What is the importance of interoperability as the value and volume of data continues to grow during this pandemic?

Akshay Chitlangia: In an ideal world, every IT system would be interoperable with another. However, many systems have their proprietary standards and schemas to lock-in customers and make it difficult for them to move to another platform or even exchange data. During this pandemic, this issue continues to exist. One small example is the way our government is monitoring Covid-19 cases across the various testing centres. Some provide information over emails, some over excel sheets, yet others through web forms.

A pre-decided standard for one-way exchange of this information would have automated a lot of the reporting around Covid-19 statistics country-wide. Yet, if you see the data minutely, you will observe certain centres/ municipalities report with a 1-2-day lag, and the analysis at a macro scale gets held back till all the information is available in entirety.

Another simple example is salary disbursement systems, that depend on employee payment data being shared in fixed formats. Either having a well-defined standard or having an AI system that can automatically match data points between systems can tremendously help here, by reducing the quantum of manual workload. New technologies such as Virtual Reality and Augmented Reality await a proper take-off due to the lack of interoperability in the variety of systems in use in the industrial sector.

Thus, the more complicated a scenario, and the more numerous the systems being adopted, the higher are the potential benefits from having interoperability.

DQ: Data and facts have become essential to see and understand situations. How can we get a clear directive to inform on next steps?

Akshay Chitlangia: When you have data, that you can treat as facts, you can consider deriving Insights from them. If there is a repository of digital information available, either as an organization, or an industry, AI can be used to generate a variety of Insights. Some examples can be trying to predict an upcoming defect/ failure event, optimizing a production schedule, optimizing the route and timings of a delivery person, etc.

Different situations require different approaches, and this is an evolving space in the areas of AI and insight generation. At present, most of the insights are delivered via reports or graphical dashboards. Businesses depend on Leaders to interpret such insights on their own and take actions. In the coming months, we will see emergence of solutions that provide curated insights, along with recommendations on next action that the individual may consider performing. These solutions come under the umbrella of actionable insights.

Akshay Chitlangia, Principal Technology and Solution Consultant – Data and Analytics, Persistent Systems Ltd.