Reimagining the Back Office for the Workplace of the Future

Humankind progresses forward, thanks to continuous innovation and our ability to make and use tools. Now a new dawn approaches and promises another huge evolutionary leap: The Artificial Intelligence (AI) and automation revolution.

At businesses around the world today, the vast majority of work is still manual. Enterprises have back offices with hundreds of thousands of humans doing the grunt work of operations, through perhaps a shared services team, in each of the Fortune 500 companies worldwide. The opportunity to dramatically relook at how work can be executed using AI-powered Automation, lends itself to unimaginable opportunities that will deliver outcomes of efficiency, economics, and experience.

Enterprises still require humans for a large portion of business process operations scenarios, traditionally using tools to accomplish a few remaining tasks. However, given the outcomes desired, what if we could change that equation around? Could humans use their skills to primarily monitor and configure AI-powered machines, and extract maximum work from machines?

The answer to this question is a resounding yes, and this scenario isn’t far away from reality. A complete reimagination of the enterprise back-office function is happening through the application of AI technologies, creating what we call an “Autonomous Back Office."

Opening the door to back-office innovation

The Autonomous Back Office will enable previously unthinkable efficiencies by using AI models for image processing, natural language process, predictive analytics, and anomaly detection for various uses along an enterprise’s value chain. 

For example, say you are a chief financial officer at an enterprise. An autonomous back office will impact your day-to-day by:

• Automatically gather and consolidate data from multiple data sources in near real-time, freeing up CFOs and their finance teams to focus on strategic planning

• Improve risk management, since organizations can leverage AI to create warning systems and avoid mishaps

• Simplify the auditing process, as AI could streamline the reporting process

To explain a simple use case - For decades, financial professionals have been struggling to get the revenue forecast as close to the financial close and disclose process. Over a period, there have been various applications and models proposed to bring forecast as close to the reality, yet the science of getting those numbers have been elusive in most cases.

With the advancement of Machine Learning (ML) algorithms and computing capability, it has become possible to bring unstructured data into the process which hitherto was available but not part of the decision-making process.

The approach we took combined the traditional lever of identifying correlation using statistical tools with ML routines for hyper-localized events, unstructured content processing (customer satisfaction score (CSAT), net promoter score (NPS) qualitative, stock exchange filings by its customers, vendors and news screening from trusted information sources), and many others. Then, leveraging AI neural algorithms for glide path forecast with a “What If” interventions,  allows users to infer the causal factors which are having either positive or negative bias on the forecasts.

Using this method, we were able to proximate the financial close numbers achieving significantly high accuracy, and this approach has now been adapted for multiple industries as well.

The impact is far-reaching. This has a direct impact on topline and bottom-line of the enterprise, including borrowed working capital typically factored as a liability on the books.

By baking interoperability into Autonomous Back Office solutions, enterprises will have an end-to-end view of their business processes and functions. This will enable companies to identify and address organizational problems, easing stakeholder concerns.

But how will this impact my job?

As with previous technology innovations, there has been a narrative suggesting automation will result in a job loss. While research from the World Economic Forum suggests that by 2022, 75 million jobs may be displaced by automation, it also found that an additional 133 million new roles will concurrently emerge, indicating a positive outlook.

With machines doing more of the heavy lifting, the organization’s talent will be free to pursue higher value work and goals. Instead of focusing on mundane or repetitive work, companies will be able to better leverage the unique skills of humans, such as emotional intelligence, complex problem solving, strategic planning, and communication.

Looking Ahead

In this decade ahead, an enterprise that is backed by AI is one that will stand a better chance of staying in business. Automation will be the key to sustainable growth, helping companies be more efficient, more competitive, more profitable, and more relevant to its customers.