Looming recession: 5 things companies can do to create value
In the face of economic uncertainty and recessionary pressures, it also becomes equally important to focus on near-term tactical opportunities to drive value. For those involved with IT and data management, there is no better time than now to test your abilities with the digital basics.
- Apr 12, 2023,
- Updated Apr 12, 2023 12:27 PM IST
In the rapidly evolving digital landscape, it is important for companies to keep up with the latest trends and strategies to remain competitive. However, in the face of economic uncertainty and recessionary pressures, it also becomes equally important to focus on near-term tactical opportunities to drive value. For those involved with IT and data management, there is no better time than now to test your abilities with the digital basics.
Curious about how to achieve this? There are five crucial elements that form the foundation of a robust digital strategy: Persistent Digitization, Process Exploration, Human and Digital Collaboration, Strategic Contextualization, and Optimizing data flow. Dive into each of these aspects and discover how they can propel your organization to the forefront of your industry.
Laying the groundwork for success with persistent digitisation
Many years into digital transformation, you might assume we are all done creating digital versions of analog data. But that is not just it. The usual processes and interactions between a company's various stakeholders generate vast amounts of unstructured information endlessly. And it is this information that needs to be converted into structured data as efficiently as possible. Companies should use all the tools at their disposal to achieve the same – artificial intelligence (AI) and natural language processing (NLP).
In a modern enterprise, digitization must become a constant endeavor. Once structured, data can then be manipulated, aggregated and analyzed. Structured data is a fundamental component for machine learning and predictive analytics, and it can lead to competitive advantage in many industries.
Gaining insights into business processes for continuous improvement
Every business should make it a priority to achieve the goal of continuous improvement and automation of everything possible. This can be attained by companies knowing how their processes are executed and how people interact with the processes and systems at any given time.
To gain this insight, it now becomes important to invest in process discovery. Process discovery, also known as task mining, involves creating a digitized version of a human worker’s expression on a given device. With this digitised data, companies can identify bottlenecks, streamline workflows and identify opportunities for automation.
But given the presence of Shadow IT and limited access to many devices, as well as the sheer volume of data generated by individual clicks, process discovery can be difficult. If, like many organizations, you have blind spots in this area, remember that without deciphering processes, it is difficult to improve them. Only by knowing what is going on in your business can you identify opportunities for optimization or automation.
Embracing the future of work with human and digital collaboration
With the right data, you can deploy automated scripts that reduce the number of manual processes, speeding up work while improving reliability and accuracy. Robotic process automation (RPA) is already well-advanced in factories and automated vehicles supported by AI and machine learning (ML). But how about welcoming these new ‘digital workers’ into the office! The labor shortages and constraints that surfaced during the pandemic have shown that ‘bots’ are capable of closing books, quoting prices, collecting payments, interacting with customers and performing a variety of other repetitive tasks. Certainly, all of this with human workers supervising and intervening as needed.
Unlocking data potential through strategic contextualisation
To truly reap the benefits of intelligent automation, you need the right data. Through ongoing digitization and discovery efforts, data that leads to contextual intelligence can be leveraged. And this intelligence becomes more valuable as you integrate related systems within and across organizations.
However, the challenge is to establish the right governance between business and technology. As with automation, sharing policies and decision-making with ‘digital workers’ may require a shift in thinking. Remember, the goal is not to replace people, but to position data to deliver maximum value.
Optimising data flow and collaboration for greater efficiency
When effectively distributing pertinent data to the right recipients, data latency is an important factor to consider. This problem may result in information transmission delays between departments or outside partners, which might significantly impact different company processes, including supply chains, marketing, and sales. It is also critical to recognize that not all choices call for real-time data, and accelerating data speed comes at a cost. This makes it crucial to carry out a complete evaluation to identify which tasks, responsibilities, or choices are sensitive to almost real-time data and to allocate resources accordingly. For a company to succeed, it is essential to deal with data latency concerns and encourage collaborative ideas. To achieve this, it becomes vital for enterprises within an ecosystem to adopt a shared vocabulary that enables seamless information exchange.
A practical game plan
Digital transformation cannot be accomplished in a single step. Nonetheless, it might be challenging for a project to ever take off if it is too abstract. During the current economic downturn, it is just a few intermediate actions that can help you maintain your focus on results that add value and save costs.
It is important to note that digitising and organising data are necessary preconditions for everything else. Do not forget about process discovery; it is a byproduct of digitization. Automation may add additional digital workers to your human workforce. When you place facts in the appropriate context, they may achieve much more, therefore welcome them. And lastly, set your timer on. If it takes weeks, days, or even hours to transfer critical data from one area of the company to another, you very well know that its time to pick up the pace.
The author is CEO, Edge Platforms, EdgeVerve, a subsidiary of Infosys
In the rapidly evolving digital landscape, it is important for companies to keep up with the latest trends and strategies to remain competitive. However, in the face of economic uncertainty and recessionary pressures, it also becomes equally important to focus on near-term tactical opportunities to drive value. For those involved with IT and data management, there is no better time than now to test your abilities with the digital basics.
Curious about how to achieve this? There are five crucial elements that form the foundation of a robust digital strategy: Persistent Digitization, Process Exploration, Human and Digital Collaboration, Strategic Contextualization, and Optimizing data flow. Dive into each of these aspects and discover how they can propel your organization to the forefront of your industry.
Laying the groundwork for success with persistent digitisation
Many years into digital transformation, you might assume we are all done creating digital versions of analog data. But that is not just it. The usual processes and interactions between a company's various stakeholders generate vast amounts of unstructured information endlessly. And it is this information that needs to be converted into structured data as efficiently as possible. Companies should use all the tools at their disposal to achieve the same – artificial intelligence (AI) and natural language processing (NLP).
In a modern enterprise, digitization must become a constant endeavor. Once structured, data can then be manipulated, aggregated and analyzed. Structured data is a fundamental component for machine learning and predictive analytics, and it can lead to competitive advantage in many industries.
Gaining insights into business processes for continuous improvement
Every business should make it a priority to achieve the goal of continuous improvement and automation of everything possible. This can be attained by companies knowing how their processes are executed and how people interact with the processes and systems at any given time.
To gain this insight, it now becomes important to invest in process discovery. Process discovery, also known as task mining, involves creating a digitized version of a human worker’s expression on a given device. With this digitised data, companies can identify bottlenecks, streamline workflows and identify opportunities for automation.
But given the presence of Shadow IT and limited access to many devices, as well as the sheer volume of data generated by individual clicks, process discovery can be difficult. If, like many organizations, you have blind spots in this area, remember that without deciphering processes, it is difficult to improve them. Only by knowing what is going on in your business can you identify opportunities for optimization or automation.
Embracing the future of work with human and digital collaboration
With the right data, you can deploy automated scripts that reduce the number of manual processes, speeding up work while improving reliability and accuracy. Robotic process automation (RPA) is already well-advanced in factories and automated vehicles supported by AI and machine learning (ML). But how about welcoming these new ‘digital workers’ into the office! The labor shortages and constraints that surfaced during the pandemic have shown that ‘bots’ are capable of closing books, quoting prices, collecting payments, interacting with customers and performing a variety of other repetitive tasks. Certainly, all of this with human workers supervising and intervening as needed.
Unlocking data potential through strategic contextualisation
To truly reap the benefits of intelligent automation, you need the right data. Through ongoing digitization and discovery efforts, data that leads to contextual intelligence can be leveraged. And this intelligence becomes more valuable as you integrate related systems within and across organizations.
However, the challenge is to establish the right governance between business and technology. As with automation, sharing policies and decision-making with ‘digital workers’ may require a shift in thinking. Remember, the goal is not to replace people, but to position data to deliver maximum value.
Optimising data flow and collaboration for greater efficiency
When effectively distributing pertinent data to the right recipients, data latency is an important factor to consider. This problem may result in information transmission delays between departments or outside partners, which might significantly impact different company processes, including supply chains, marketing, and sales. It is also critical to recognize that not all choices call for real-time data, and accelerating data speed comes at a cost. This makes it crucial to carry out a complete evaluation to identify which tasks, responsibilities, or choices are sensitive to almost real-time data and to allocate resources accordingly. For a company to succeed, it is essential to deal with data latency concerns and encourage collaborative ideas. To achieve this, it becomes vital for enterprises within an ecosystem to adopt a shared vocabulary that enables seamless information exchange.
A practical game plan
Digital transformation cannot be accomplished in a single step. Nonetheless, it might be challenging for a project to ever take off if it is too abstract. During the current economic downturn, it is just a few intermediate actions that can help you maintain your focus on results that add value and save costs.
It is important to note that digitising and organising data are necessary preconditions for everything else. Do not forget about process discovery; it is a byproduct of digitization. Automation may add additional digital workers to your human workforce. When you place facts in the appropriate context, they may achieve much more, therefore welcome them. And lastly, set your timer on. If it takes weeks, days, or even hours to transfer critical data from one area of the company to another, you very well know that its time to pick up the pace.
The author is CEO, Edge Platforms, EdgeVerve, a subsidiary of Infosys