Digital transformation could mean different things to different people depending on their context of work and current level of adoption of digital tools. Essentially, it is use of techniques, methodologies and technologies, categorized as digital in nature, that help companies transform their manufacturing, production, business and industrial processes, operations and services - to derive significantly enhanced outcomes for the company, its employees and its customers. Like some experts have already noted, it is the way a company thinks about the future; either to disrupt or survive or make a big impact – by not just changing or tweaking a process(s) here or an activity(s) there, but to think big, innovate and be creative to take a step jump and realize transformational business outcomes. Usually, the step jump is split into a set of logical and sequential mini steps or initiatives for easier execution and tracking.

Conceptually, there are two ways one can think of bringing about a change or transformation: Digitization and Digitalization. Digitization can be thought of as converting manual data collection (or none that exists) to an easier and simpler use of digital tools to gather the data. It could be in the form of a spreadsheet, manual input to an application, instrumentation or automation of tasks and activities. Digitization helps to preserve, share and act upon the data at any point in time. Data is then acted upon in various ways viz, processed, analysed, and corelated with others to elicit information, gather insights, drive actions and help make better or “data” driven decisions. While digitization is applicable to a set of activities at the lower rungs of work hierarchy, the same when applied in a larger or bigger context to a process or procedure involving multiple changes becomes a digitalization example. And using digitalization you aim to achieve one or more business outcomes like increased production, increased process efficiency, reduced costs, reduced manpower, improved workforce productivity, enhanced and simplified user experience, new revenue opportunities, and the list goes on.

From a lifecycle standpoint, digital transformation is just like any other evolving concept or a niche initiative that goes through some standard phases of maturity cycle including discovery/problem statement, definition, evaluation (fit for need), implementation, learnings and feedback, and continuous improvement.

It is very important for a digital transformation initiative in whatever form and scale it is envisaged, to identify the key players in the organization, agree on the need for a transformation, get the financial approvals and other stakeholder buy-in before proceeding with the actual implementation. A crucial part of this exercise is also to look at available resources and expertise both within and outside the organization (IT, subject matter experts and external consultants) who will from the core team and drive the program to a successful completion.

In terms of industries affected that can gain from a digital transformation initiative, there is probably none that will not accrue benefits. There is something in it for everyone depending on how you plan and execute on the key company strategic initiatives. Nonetheless, some of the major industry verticals that are adopting the slew of newer technologies and embarking on a digital transformation journey include manufacturing (both discrete and process), Oil & Gas, Power, Utilities, Transportation, Healthcare, Pharmaceuticals, MMM (Metals, Mining & Materials), BFSI (Banking, Finance and Insurance) and others.

Industry 4.0

While digital transformation is applicable for a broader spectrum of industries and functions, Industry 4.0 began and evolved as an initiative specifically targeted for manufacturing. It has some background in the ISA 95 standard in terms of use of Information and Communication Technologies (ICT) to improve the entire manufacturing process and operations. The implementation of Industry 4.0 practices is best done if looked at from a maturity model perspective and execute in phases starting with Connectivity – the fundamental backbone for any (IoT) digitalization program or Industry 4.0 implementation. You can also treat Industry 4.0 similar to ISO or any other standard containing multiple levels of execution helping derive sequentially more enhanced outcomes.

Technology

There are many technologies that are being used or implemented depending on the specific use case or application. It starts with evaluating the fit for purpose and choosing the best or a combination thereof - that will help meet the goals and address the challenges. The list keeps evolving;, but to name a few that are being considered and implemented – Cloud technologies, Internet of Things (IoT), Big Data, Data Analytics, machine related analytics like descriptive, predictive, and prescriptive, Anomaly detection, Early Warning System (EWS), Machine Learning, Deep Learning, Artificial Intelligence, Augmented Reality, Virtual Reality, Software defined Networking, 5G etc. These technologies must be seen in the context of new or existing systems and applications including Enterprise Asset Management (EAM), Enterprise Resource Planning (ERP), Business Intelligence (BI) tools, Manufacturing Execution Systems (MES), Database, Data Historian, Data Lake, Condition Monitoring System (CMS), Computerized Maintenance Management System (CMMS), Asset Performance Monitoring (APM), Field Service Management (FSM), Laboratory Information Management System (LIMS) and many more.

More often than not, you will need to prepare a roadmap or a blueprint that charts out the course of actions to be undertaken to bring about the transformation. And make sure to do a thorough Cost Benefit Analysis (CBA) study and document/quantify the Return on Investment (ROI).

Internet of Things (IoT)