In the present world of Business, organizations need people who can communicate a clear vision and strategy, drive change, and sustain an innovative, high-performance culture. No matter the position you hold with the organization, you are hired to contribute greater skills with Technological knowledge, confidence, and expertise for the growth.

Some of the major technologies such as Digital Marketing, Big Data, Cloud, Analytics, and Mobility have been transforming the businesses to grow faster and safer. The solution of data moving into the Cloud has off-loaded major problem of security and making provisions for mobile access added sense to further reduce manipulation.

Organizations are looking to employ a wide range of Digital Technologies that include the Internet and Industrial Internet of Things (IoT and IIoT), Cloud Computing, Big Data Analytics, and also Mobility to help achieve Operational Excellence (OE).

Operational Excellence with Digital Transformation

Operational Excellence is a driving factor that really changes the company’s competitive position in the marketplace. In today’s changing business environment, it is not easy to predict the strategies of your competitor. So you need to focus on a determined way of promoting business using Digital Technology.

The key focus lies with customer-centric businesses that can be improved using Digitization upon its competitors. It helps your organization challenge itself and achieves optimum potential.  It helps companies focus their efforts at establishing winning best practices and a core competitive advantage.

Digital Transformation

Technology empowers workers with Software applications that include consumer-like interfaces to increase adoption and usage. Large data can be managed with narrow segments of business activity, bring people closer to solutions.

Nations with Digital Transformation

OE includes several business elements. Digital Transformation projects can be taken up in each of these individual elements to bring about operational performance improvement. However, they must be considered a good investment by any organization.

Any organization that is seeking to achieve Operational Excellence through Digital Transformation has to work on getting its Information Technology (IT) set up aligned to its business goals. Although it’s not to initiate one big change, but simply create smaller models or prototypes, work with them and then improve flexibility and efficiency.

The present scenario in dealing business using technology clearly states and focuses on Digital Transformation. This approach is inculcated by few countries after naming it to be the fourth industrial revolution and is known by  ‘Smart Manufacturing in the U.S.’, ‘Industry 4.0 in Germany’, ‘Made in China 2025’, and so called ‘Made in India’ started in the recent past.

How does Operational Excellence work in different areas?

It is critical, especially in large, asset-intensive plants such as those found in the process manufacturing and power industries, in which the operations phase is huge relative to the installation (project) phase. The primary factor that propels process industries is to expansion and growth besides projects with the core of each organization’s value chain with excellence in operations.

Advanced Analytics & Big Data: On-going Digital Transformation Tools

Advanced Analytics along with Machine Learning is a solution provider for estimating future performance issues with machines under present running condition. They can help reduce energy consumption by avoiding mechanical failures or other issues that could result in lost profitability and/or unsafe conditions. Advanced Automation holds a special place by reduced freeing human errors in operations, maintenance, etc instead alarms to focus on solving problems that are outside the realm of automation.

Most of the organizations today are trapped in various departmental solutions with respect to data deployed over the years. The first step in deploying a good business analytics solution is to collate the information spread across multiple systems within the plant into a single repository or data saved in Multi Cloud.

Other Advanced Tools for Operational Excellence

OE clearly needs a strong pre-built connector framework with the ability to readily access the data from the process historians, ERP (enterprise resource planning), LIMS (laboratory information management systems), custom applications, Excel spread sheets and other sources. And the data needs to be collated in a data repository/model that can allow easy analysis and flexibility to enable users to “slice and dice” it as needed.

In short, an enterprise business analytics solution should cater and align all the different roles/levels starting from operators/supervisors, line and functional managers, functional analysts/strategists, and executives.

Digital Transformation with Business Process Management

Information has always been among the most prized assets of any organization. How information is used, however, is changing. Business Process Management (BPM) enables companies to access, distribute, manage, and analyze and act on information, achieving objectives that lead to sustainability and competitive advantage. Data is the currency of the global economy.

We consider this piece of the organizational puzzle ‘enablement,’ as without deep insights into how the business is running (combined with acceptance as to the need to change it), very little can happen.

Digital Transformation is the driving force for autonomous systems with automation being the enabling technology. A long established axiom in manufacturing and in business process improvement (BPI) is “if you automate a bad process you just do badly bigger and faster.”

Levels of Process Maturity & Digital Maturity

When comes to understanding OE, organizations have their setup with either low or high levels of maturity in process and digitization. However, maturity here refers to functioning of firms with respect to the present world.

In the recent past, Technology has been in the new phase of era with Automation and Artificial Intelligence. For instance, say firm X has initiated to have some sensitive data on cloud which it believes to be a safer zone but the Process isn’t effective for such storage. Or in other words, all the older data has to be gathered from multiple files on the PC or manual files. So such scenario could be quoted under Low Process-High Digital Quadrant.

The kinds of such scenarios can otherwise be named with 4 levels of Process and Digital Maturity. Below are the 4 levels:

Low Process-Low Digital Quadrant

Low Process-High Digital Quadrant

High Process-Low Digital Quadrant

High Process-High Digital Quadrant

In a similar fashion, when both the Process and Digitization are at higher level of maturity, the fourth level mentioned above is the case. For example, an ordered list of data with the particulars of around 8,000 employees can be retrieved for referring faster during financial year end when digitized on Big Data tool. Here comes the role of Process and Digital Quadrant at a higher level.

With simple examples of maturity levels in this digital world, many more technologies are yet be updated. However, these levels of maturity do relate to the Operational Excellence depending on the choice of Process and Digital Quadrant chosen.

KPI metrics in Digital Transformation

Once process definition and modeling activities are underway, it is important to define Key Performance Indicator (KPI) metrics to measure the effectiveness of process digitization. Examples could be metrics related to process cycle time, process efficiency, productivity of people involved in the process, customer experience impact, and so on. An example of a well-known metric in Insurance claims processing is settlement time. Another goal for Digital Operational Excellence is to measure such KPI metrics and aim to constantly improve them over time.

Some years ago, settlement times for an auto insurance claim for example, would have perhaps been a week or two. With the initial IT and BPM implementations for First Notice of Loss and related downstream activities, settlement times were cut down to a few days. Next were mobile apps for claims, which provided the ability to upload photos of your damaged vehicle directly from your phone. A claims assessor could view the photos and take a decision, cutting down settlement times to a day or less.

Now, Artificial Intelligence (AI) based applications using computer vision algorithms can estimate the damage automatically (especially for minor damages) and process the claim in a ‘straight through’ manner, cutting down settlement times to a few seconds. A metric being cut down from weeks to days to seconds is a good illustration of what digital transformation really means.

Operational Excellence with collaborative effort

The key factors of achieving Operational Excellence are vision, planning, and a team effort.  This typically involves collaboration across the value chain.  How well companies design, engineer, source, make, distribute, and support products and manage their assets will ultimately determine their success.  Close collaboration with people, processes, technologies, and organizations plays a vital role.

Operational Excellence with a systematic approach

Operational Excellence works best for industrial organization to reach desired performance in productivity, quality, and delivery of services. However, the same refers with the product reach across the locations in manufacturing industries. 

OE spans product design and development; enterprise resource planning and control; supply chain management; manufacturing execution; and operational effectiveness of people, processes, and assets. By aiming a destination or endpoint, Operational Excellence is an ongoing journey that also requires a roadmap.

Operational Excellence is a never ending journey

An Operational Excellence roadmap considers the customer needs and business environment. To meet these changing needs, the operational excellence goals will also have invariable change over time.


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