How to Build Enterprise Resilience — 4 Decisive Factors

For organizations to unlock the advantages of operational resilience, they must look at the digital basics to understand what lies under the hood and what differentiates the predictive vs. reactive approach.
How to Build Enterprise Resilience — 4 Decisive Factors

The last few years have been the poster child of disruption – from dealing with a pandemic that shut down the world to heightened geopolitical conflict and a looming recession. Authorities on the economic outlook, including the UN, the World Bank, and the IMF, have predicted that these disruptions will cost the global economy anywhere between US$4-22 trillion.

We have seen first-hand how shock events, such as the COVID-19 pandemic can dramatically impact the economic outlook for enterprises. For example, enterprise preparedness was overtaken during the pandemic, causing cascading failure for companies across industries – banking, oil and gas, food and beverages, and aerospace – reportedly leading to a loss of over 30% of their market value.

On the other hand, companies that pivoted and made data-driven decisions across connected value chains came out relatively unscathed.

"In a constantly changing world, organizational resilience depends on predicting the future and responding with agility."

Sateesh Seetharamiah | CEO of Edge Platforms

In a constantly changing world, organizational resilience depends on predicting the future and responding with agility. Without the right data and predictive capabilities at hand, organizations leave themselves open to the risk of under-preparing and overreacting.

Establishing operational resilience and predictive decision-making

The COVID-19 pandemic has been a significant catalyst for change, accelerating the adoption of automated solutions across various sectors. Businesses worldwide were required to embrace operational resilience by adapting to new ways of working, and automation has been instrumental in this transition.

Those businesses embraced a predictive approach to evolve with the needs of their customers. But doing so didn’t happen overnight; it required a shift in mindset.

For organizations to unlock the advantages of operational resilience — whether a shock event like a pandemic occurs or not — they must look at the digital basics to understand what lies under the hood and what differentiates the predictive vs. reactive approach, focusing on five key areas:

  1. Digitize: Are your processes and documents digitized?

  2. Discover: Are you able to connect parties and customer journeys?

  3. Automate: Can you exchange data and information seamlessly and in near real-time?

  4. Contextualize: Can you leverage data to generate insights that augment human decision-making?

  5. Accelerate Data Exchange: Are your cross-functional teams empowered to innovate and collaborate faster?

Getting these pieces in place will set a strong foundation for business resilience and create more opportunities even in difficult circumstances.

What sets truly resilient enterprises apart?

Resilient enterprises don’t operate from siloes. They proactively enable a clear flow of data and information across connected systems and have clear visibility of what is going on in their business. In these businesses, systems integrate more seamlessly, technology connects more effectively, processes run effortlessly, and information flows more freely.

Several recent studies have shown that companies that leverage AI, automation, and intelligent insights perform better financially, are more productive and profitable, and are more likely to outperform the competition.

Across these and other vectors of resilience, building an intelligent connected enterprise has helped several companies anticipate and overcome challenges or leverage opportunities.

1. Leveraging AI

The adoption of AI models offers a significant competitive advantage for businesses. The rise of technology has consistently disrupted various industries, creating new opportunities and challenges for humans to adapt and solve. AI-led transformation follows this pattern, and it is vital to approach its impact on human workers with a balanced and nuanced perspective.

While AI has the potential to automate certain jobs and tasks, it also creates vast opportunities and jobs, particularly in the field of data science and machine learning.

"Many tasks and jobs require creativity, emotional intelligence, and human interaction, which are less likely to be fully automated by AI."

Many tasks and jobs require creativity, emotional intelligence, and human interaction, which are less likely to be fully automated by AI. Thus, it is essential to view AI as a complement to human workers rather than a replacement.

For example, one of the largest telecommunications companies in the world saw that its sales, mobile tower negotiation, and contract enforcement teams were overwhelmed with over 650,000 tower rental contracts. Moreover, manually reviewing the contracts affected both team efficiency and information accuracy.

Instead of being reactive to this issue, they were proactive in addressing the issue, extracting contract clauses faster and more accurately by embracing the value of AI. The client’s contract enforcement team was thus able to automate the contract review process, enabling teams to work on higher-value tasks to save millions with better negotiations by having correct and instantly accessible information.

As the digital transformation journey continues its advancement, maximizing the benefits of AI requires organizations to break down silos and improve collaboration. Investing in education and upskilling programs is vital to thriving in an increasingly AI-driven world. This will equip workers with the necessary skills to adapt to new roles, ensuring they can effectively contribute to the workforce and benefit from AI opportunities.

The companies willing to embrace this approach will see improved communication and data exchange across value networks, ultimately leading to a more responsive organization.

2. How automation enables operational resilience and predictive decision-making

Automation in business processes aims to simplify and optimize repetitive and time-consuming tasks by leveraging technology to complement or augment human labor. By automating business processes, companies can provide businesses with real-time data and insights, which can be used to make more informed decisions and improve overall performance.

Additionally, business process automation can save time, reduce errors, and increase efficiency, leading to cost savings and improved productivity, ultimately helping businesses scale their operations more effectively without incurring high costs.

For instance, a multinational brewing company struggled with secondary sales visibility and sales rep productivity for its African operations. Lack of adequate IT infrastructure, prolonged power cuts, poor and expensive internet connectivity, lack of IT skills, and language challenges made implementing a sophisticated technology solution difficult.

This hindered the sales teams’ ability to deliver the personalized, timely, and reliable customer services needed to be successful. But did it stop them from pursuing connected systems? No!

They used an app with offline capabilities and put the power of this technology in their people’s hands. The result? They gained a massive competitive advantage as their sales representative’s productivity shot through the roof.

"Businesses generate massive volumes of data and documents – almost 80% unstructured."

Businesses generate massive volumes of data and documents – almost 80% unstructured. This makes digitization a continuous endeavor to convert this information to structured data that can be harnessed, aggregated, and analyzed. Using this data to create a digital blueprint of processes gives a clearer picture of what’s happening in the business.

What needs to be reimagined, optimized, or automated to amplify outcomes? This clarity helps define automation objectives and create an end-to-end intelligent automation program that consistently delivers top-tier results.

The benefits of intelligent automation can only materialize if the data it works on is contextual and available in a usable format in near real time, as data is constantly evolving. This means not only digitizing documents and data within the process but also integrating related systems within and between organizations that can exchange data at speed and scale.

Driving collaborative insights is only possible when there is a shared vocabulary for a seamless exchange of information. If accomplished, the benefits can be immense. For instance, a Fortune 50 F&B brand connected multiple distributors across different geographies over an automated cloud-based data exchange. This helped them eliminate distributor operation inefficiencies, improve data quality, and skyrocket employee productivity by 70%.

3. Data-driven approaches make for intelligent insights

As organizations shift from simply surviving in a digital era to thriving in a digital world, the business opportunities for enterprises that can extract value from their data have never been greater.

The ability to track and trace products across the supply chain can make a massive difference to a manufacturer’s risk profile. For instance, Mars Inc. connected partner systems across the value chain for real-time product movement and storage visibility.

This improved brand resilience and reduced traceability time from 4 days to 2 hours – a 48x improvement. Similarly, a Dutch multinational conglomerate in the health tech and consumer electronics space used automation to remove inefficiencies and get better visibility into risk, cash flow, and performance.

This helped their finance team get the data and information needed to steer the business in the right direction and improve overall resilience. The impact on the topline was significant, too, as they reduced blocked payments by 90% and improved collection by 21%.

This resilience comes from their ability to methodically run cognitive operations, create value networks, and amplify human potential. The ability to tap into data – not just within a business but across the ecosystem – helps understand market evolutions and make crucial decisions proactively instead of simply being reactive.

4. Building resilience requires a mindset shift

While deploying intelligent technology is essential to building resilience, it will only be effective with a mindset shift. The onus of creating acceptance for this technology lies with the business leaders.

They must step up and drive a cultural shift, creating awareness, assuaging concerns, and driving collaboration between human and digital workers. The point is not to displace humans but to augment what they can do with data and intelligence to future-proof business decisions.

About the author:

Sateesh Seetharamiah is the CEO of Edge Platforms, EdgeVerve Systems Limited (An Infosys Company), and a board member and Whole-time Director at EdgeVerve. Seetharamiah is an industry veteran with three decades of rich experience in entrepreneurship, management consulting, IT leadership, and supply chain.

He believes in AI and Automation’s immense potential to transform future enterprises. With deep-rooted experience in the area of supply chains, he pioneered the Internet of Things (IoT) in its early days. Seetharamiah is one of the founding members of EdgeVerve and comes with rich experience in the product and platforms domain.

Being a passionate technologist, he has been instrumental in establishing many foundational technology capabilities that drive today’s EdgeVerve strategy. In addition, he has been on the board of various start-up firms in the IoT and pervasive computing space.

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