In a rapidly evolving digital environment, it is critical for businesses to keep up with the latest trends and strategies to remain competitive. But in the face of economic uncertainty and recessionary pressures, it becomes equally important to focus on short-term tactical opportunities to add value. For those working in IT and data management, now is the perfect time to test your proficiency in digital fundamentals.
Curious about how to achieve this? Here are five key ingredients that form the foundation of a robust digital strategy. Persistent digitization, process exploration, human-digital collaboration, strategic contextualization, and data flow optimization. Dive into each of these dimensions to discover how to push your organization to the forefront of your industry.
Laying the foundation for success with sustained digitization
Years before the digital transformation, you might think we were all done creating digital versions of analog data. But that’s not all. The normal processes and interactions between various stakeholders in an enterprise generate an endless amount of unstructured information. And it’s this information that needs to be transformed into structured data as efficiently as possible. Businesses should use all the tools at their disposal to achieve the same thing, including artificial intelligence (AI) and natural language processing (NLP).
Digitization must be a constant effort in modern enterprises. Structured data can be manipulated, aggregated, and analyzed. Structured data is a fundamental component of machine learning and predictive analytics and can lead to competitive advantage in many industries.
Gain insight into business processes for continuous improvement
Every business should make it a priority to achieve every continuous improvement and automation goal possible. This can be achieved by companies that know how their processes run and how people interact with processes and systems at any given time.
Investing in process discovery is key to gaining this insight. Process discovery, also known as task mining, involves creating a digitized version of a human worker’s representation on a specific device. Using this digitized data, businesses can identify bottlenecks, streamline workflows, and identify opportunities for automation.
However, given the presence of Shadow IT, limited access to many devices, and the vast amount of data generated by individual clicks, the process can be difficult to detect. Remember, like many organizations, if you have blind spots in this area, it’s hard to improve without deciphering your processes. Only by knowing what is happening in your business can you identify opportunities for optimization or automation.
Embracing the future of work with human-digital collaboration
With the right data, you can deploy automated scripts to reduce the number of manual processes and speed up your work while improving reliability and accuracy. Robotic process automation (RPA) is already well advanced in factories and self-driving cars supported by AI and machine learning (ML). But why not welcome these new “digital workers” into your office? The labor shortages and constraints that surfaced during the pandemic show that “bots” are capable of closing accounts, quoting prices, collecting payments, interacting with customers, and performing a variety of other repetitive tasks. Indeed, all of this is overseen by human workers, who intervene when necessary.
Unlock your data’s potential through strategic contextualization
To truly reap the benefits of intelligent automation, you need the right data. Leverage data that leads to contextual intelligence through ongoing digitization and discovery efforts. This intelligence becomes more valuable as you integrate relevant systems within and across organizations.
The challenge, however, is establishing proper governance between business and technology. As with automation, sharing policies and decisions with “digital workers” can require a mindset shift. Remember, the goal is not to replace people, but to put your data in place to provide the most value.
Optimizing data flow and collaboration for greater efficiency
Data latency is an important factor to consider when effectively distributing relevant data to appropriate recipients. This problem can lead to communication delays between departments or between external partners, and can have a significant impact on various company processes such as supply chain, marketing, and sales. It’s also important to recognize that not all options require real-time data, and higher data rates come at a price. This makes it critical to perform a thorough assessment to identify tasks, responsibilities, or choices that affect near-real-time data, and allocate resources accordingly. Addressing data latency issues and encouraging collaborative ideas is essential for enterprise success. To achieve this, it will be essential for companies within the ecosystem to adopt a shared vocabulary that enables seamless information exchange.
practical game plan
Digital transformation cannot be achieved in one leap. That said, being too abstract can make it difficult for your project to get off the ground. During the current recession, there are only a few intermediate actions that will help us stay focused on outcomes that add value and reduce costs.
It is important to note that digitizing and organizing data is a prerequisite for everything else. Don’t forget process discovery. It’s a by-product of digitization. Automation can add digital workers to the human workforce. Facts are welcome because they have the potential to accomplish more when put in the right context. Finally, turn on the timer. If it takes weeks, days, or even hours to transfer critical data from one area of your company to another, you know it’s time to pick up the pace.
The author is CEO of Edge Platforms of EdgeVerve, a subsidiary of Infosys.