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Srividya Kannan

Kannan is Founder & Director, Avaali Solutions

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Trends in Enterprise Productivity with Digital

Technologies such as Internet of Things, Machine Learning, Artificial Intelligence and Information Management are driving significant productivity increases.

Photo Credit : whichvoip.co.za,

“The biggest impediment to a company’s future success is its past success.” - Dan Schulman | CEO of PayPal

“In today’s era of volatility, there is no other way but to re-invent. The only sustainable advantage you can have over others is agility, that’s it.  Because nothing else is sustainable, everything else you create, somebody else will replicate.” Jeff Bezos | Amazon founder

Technologies such as Internet of Things, Machine Learning, Artificial Intelligence and Information Management are driving significant productivity increases. According to some recent research, almost half of the activities that people are paid to do in the world’s workforce could be automated with technology. That amounts to $ 15 trillion in wages. It is estimated to affect almost all jobs to a greater or lesser extent depending on the type of work. Any role or activity that entails physical work involving data collection, data processing and predictable set of tasks has seen a far higher potential to be automated vs. the ones entailing subjective, decision making skills that needs a higher level of intelligence and experience.

Automation has often been associated with job losses and increase in unemployment rates or requirement to upskill. However, history suggests that this cannot be generalized. Employment in non-routine cognitive and non-routine manual tasks have grown whereas employment in routine jobs have been broadly flat largely as a result of automation.

Productivity improvements because of automation can be analyzed by the way it has impacted four key strategic levers for any business process – React, Predict, Get Intelligence and Transform.

React: As Charles Darwin says “It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change”.  Agility is the key to enterprise success. Responding to changing customer requirements, significantly improving time to market, the ability to address new business opportunities and making the cost base scalable are priorities for any organization. Agility is an enterprise quality that pervades across the organization and everything it does. Executing with agility is arguably the hardest and the most important capability to get right. To be able to respond quickly to market changes, what enterprises need is the visibility to information and the ability to execute faster processes. Enterprises have adopted Information Management solutions rich with dashboards and mobile features, that allows them to have the visibility to unstructured content and fully automate business processes entailing workflows, exception handling, validations and approvals. These solutions can be deployed as a platform and used to automate multiple business processes from operational to customer facing processes. Several enterprises are looking to adopt best of breed solutions that talk to their existing applications such as ERP, CRM, HR, SRM etc. and fully automate such processes such that the cycle time to process comes down by a factor of close to 60%. With Robotic Process Automation (RPA), enterprises can signficantly bring down the cycle time to process. Some enterprises are looking to marry AI with RPA to help robots to see like humans.

Predict: Predictive analytics is a game changer for enterprises.  Enterprises are adopting new industry tools that allow them to predict the future more accurately. The opporunities to use big data analytics to solve specific business problems are expanding rapidly and has the potential to reinvent the way enterprises work. This can be used by enterprises to predict an outcome, behaviour (from across customers, employees, debtors, suppliers, criminal suspects, voters etc), proactively averting bad outcomes, resource allocation, route optimization etc. to then drive operational decisions and processes effectively. It is this generality that makes the technology so ubiquitous.  In simple terms, predictive analytics is the systematic use of data, machine learning and stastical algorithms to identify patterns based on a huge chunk of data to then predict the likelihood of future outcomes.  

Get Intelligence: Fostering a data-driven organization emboldens the vision of a faster, agile and well informed organzation with significantly better productivity and lower costs. It significantly improves the velocity of enterprise decisions. The volume, velocity and variety of content and data is only increasing exponentially. By connecting diverse data points, key stakeholders in the process are able to draw a comprehensive picture of the current state, thereby ensuring faster decisions. Making the most of ‘Best of breed solutions’ coupled with a sound implementation exection strategy, ensures that all the relevant data is collected, integration requirements with other pieces of information is taken care of and the insights are well presented, thereby enabling actionable decision making. As with any automation, business Intelligence requires enterprise commitment to action over indecision and passion to make a difference.

Transform: The boundaries between the digital world continue to blur making profound implications on the way enterprises innovate. The pace of innovation, launching products and solutions has changed significantly with digital. Enterprises are transforming the pace at which they operate and serve their customers. Some examples include outcome-based model, expansion to new industries or markets, creating a marketplace model with the ecosystem, accessing a shared economy and resources of others, accelerating the way products / services are conceived and designed to changing or defining new customer experiences.

To achieve broad based and a powerful desired impact, technology must be adopted at scale and diffused through-out the organization. For enterprises at a lower scale of maturity with respect to technology adoption, this could be too overwhelming. Such enterprises could deploy a set of use cases with a smaller scope and with immediate returns. These could be the stepping stones for building scalable models. Nevertheless, the complex journey of scaling up is one of the biggest challenges. Only a minority of companies are successful to mobilize, strategize, innovate and scale up at a consistent pace.

Data is a strategic asset for any enterprise. As Eric Schmidt, Google’s co-founder and Alphabet’s CEO, has observed, data is so powerful that countries will likely go to war over it. However, most enterprises are still struggling to put a strong foundation and mechanism to explore, evaluate and importantly execute their strategic digital business plans in a consistent and on-going manner. Executives must constantly challenge themselves to understand how they could transform processes and deliver better performance by capturing the value of automation. This also requires senior leadership commitment and alignment to be the key driver of this change.

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house


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