2021: From Digital Firms to Autonomous Digital Enterprises

2021: From Digital Firms to Autonomous Digital Enterprises
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by Sanjeev Kapoor 02 Mar 2021

For nearly two decades, digital transformation is at the very top of the strategic agendas of many enterprises. Businesses are continually investing in IT towards improving their productivity and managerial decision-making. In recent years, many enterprises have managed to transform themselves into digital firms i.e., to manage most of their business relationships through digital channels. Likewise, they have successfully transformed many paper and pencil processes into digital ones. In this direction, enterprises have deployed many different IT systems, re-engineered their business workflows, and employed disciplined change management processes.

Once upon a time, the above-listed digital transformation activities were sufficient to make a firm stand out in the competition. Digital Firms had competitive advantages over businesses with lower digital maturity. This is no longer the case: Nowadays, most business enterprises implement digital processes and manage supply chain relationships through digital channels. Hence, digital channels are commoditized and unable to provide an advantage over competitors. Nevertheless, cutting-edge digital technologies provide new opportunities for raising enterprise productivity and building competitive advantages. These opportunities stem from leveraging data, prioritizing digital channels, providing customer-centric services, and automating business processes.

 

Prioritizing Digital Channels

Most modern enterprises operate through a variety of physical and digital channels, including sales, marketing, and commerce channels. This is the norm in a variety of sectors such as retail (e.g., physical shops and e-shops), finance (e.g., branch banking and mobile banking), and healthcare (e.g., physical healthcare services and remote care).  In this context, the digital leaders of our era prioritize digital activities over physical interactions. This prioritization helps enterprises reduce transaction and agency costs, while at the same time reducing human errors. Furthermore, it facilitates enterprises to collect large amounts of data for their customers, which enables the implementation of customer-centric services. During the last year, the coronavirus pandemic has unveiled the importance of digital channels for enterprise resilience. Specifically, during the COVID19 period, digital channels enabled enterprises to operate despite restrictions such as site lockdowns and massive teleworking policies. Overall, digital channels boost the competitiveness, productivity, and resilience of modern enterprises, which is the reason why several enterprises are increasingly designing and offering services that are 100% digital.

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Data-Driven Enterprises

We are living in a world where businesses and individuals generate data in an unprecedented pace: More than half of the data ever produced was generated during the last couple of years.  Businesses are therefore provided with opportunities for leveraging large volumes of data to improve their competitiveness. In this direction, companies must plan their transformation to data-driven enterprises. Specifically, their business processes should be optimized following the analysis of significant amounts of data. Likewise, companies must ensure that they leverage data in their decision-making. This will ensure that their decisions are educated, evidence-based, and more efficient.

To realize their transformation to data-driven enterprises, businesses must take advantage of BigData technologies, which provide the means for scalable management of very large volumes of data from heterogeneous sources. Furthermore, they can also use techniques that facilitate the creation of automated and reusable data pipelines such as DataOps.

 

Intelligence and Automation

The rise of Machine Learning (ML) and Artificial Intelligence (AI) provides enterprises with unprecedented opportunities for automating business processes. For instance, Robotics Automation Processes (RPA) help enterprises automate repetitive tasks in ways that improve efficiency and reduce human errors. Furthermore, the use of ML models enables the extraction of business insights from large amounts of data, including hidden patterns of enterprise knowledge. In cases where large amounts of data are available, ML models can accelerate data processing and knowledge acquisition. As another example, AI provides a wealth of automation opportunities based on the deployment of smart objects and autonomous systems, including both software systems (e.g., chatbots) and cyber-physical systems (e.g., drones, robots, automated guided vehicles). Also, enterprises can integrate multiple AI systems to increase the automation and intelligence of their data-driven processes, i.e., to move towards hyper-automation.

Nowadays, there also many automated development and deployment methodologies, which facilitate enterprises to leverage new data as they become available. For instance, Development and Operations (DevOps) methodologies automate the process of update ML and AI workflows, which makes enterprises more agile. In recent years, ML and AI techniques are integrated with DevOps practices leading to new development and deployment techniques like MLOps and AIOps. The latter boosts the responsiveness of modern businesses and enable them to rapidly adapt to external triggers such as changes in demand, service disruptions, and new customer requirements.

 

Exceptional Digital Skills

Digital Firms acknowledge the importance of digital skills towards leveraging advanced IT systems and the opportunities that these systems provide. This is the reason why most organizations provide their employees with access to well-structured training programs and related reskilling and upskilling processes. Upskilling and reskilling is an integral element of most enterprises’ digital transformation. It is the element that enables businesses to realize a shift in their corporate culture and to reallocate workers from the conventional manual tasks to the emerging automated activities. The latter is essential for elevating productivity and improving corporate bottom lines.

Nevertheless, conventional digital literacy is not enough for digital enterprises that leverage IT as the main source of their competitive advantage. Such enterprises must also employ digital leaders and innovators, which will help them stay at the forefront of digital innovation. Specifically, digital innovators must be knowledgeable on how to develop and launch novel services, while exhibiting critical thinking and creativity.  In this way, they will be able to leverage automation for improving customer services in ways that will set them apart from their competitors.

 

Overall, there is an on-going shift from digital firms to autonomous and intelligent digital enterprises. The latter are not limiting to operate digital channels, but rather leverage digital information to automate their business processes and provide exceptional customer-centric services. Autonomous enterprises minimize physical channels and human-mediated error-prone processes. They employ automated processes like RPA and AI, which enable hyper-automation and boost continuous business improvement.  Cutting edge digital technologies like BigData, AI and ML, along with methodologies like DataOps, MLOps and AIOps, are key enablers of this transformation.  Furthermore, enterprises cannot be successful unless they employ workers with exceptional digital skills, including digital innovators. The shift from digital firms to autonomous enterprises is taking place for over five years. Nevertheless, 2021 signals a major milestone in this transformation journey. This is because of the COVID19 pandemic, which has accelerated digital transformation and led many companies to replace physical channels with digital ones. This is not expected to change following the end of the pandemic i.e., during the new normal, yet the exact percentage of enterprises that will manage to become autonomous remains to be seen.

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