How Intelligent Automation will take us from the Now into the Next and Beyond during these unprecedented times

The Coronavirus (COVID-19) has very quickly spread across the globe infecting hundreds of thousands of people within only a few months. The severity of this pandemic has forced a fundamental shift in behaviour, both locally and abroad.

These changes, amongst others, have predominantly focussed on limiting the spread of COVID-19 by restricting human interaction and have fundamentally changed the way people work, the way businesses operate and the environments in which we all exist. At this stage the full impact of what we need to prepare for, is still very uncertain.

The key challenges keeping business decision makers up at night are how to successfully ensure that:

• employee welfare and wellbeing are effectively managed 
• current and future revenue streams remain relatively consistent
• proactive workforce management takes place so that all critical processes remain operational
• new and existing business risks are proactively identified and managed
• costs are maintained within reason; and
• business as a whole remains relevant and resilient and is well positioned to sustain itself for continued relevance post the stabilisation of the COVID-19 pandemic.

We simultaneously find ourselves amidst the fourth industrial revolution which provides direct access to specific capabilities that can strategically be leveraged to inhibit the expected business impact. Today’s technological landscape allows the integration of digital capabilities to enable new revenue streams delivered through innovative business models, and efficient processing with low-cost structures via new operating models. Each of which, could be positioned in such a way that does not only support current operations and survival within our current context, but also could facilitate increased profit and market share post stabilisation of the COVID-19 pandemic.

Although there is a myriad of technologies that can be leveraged, the challenge is that COVID-19 is far reaching and life threatening. It is therefore on that premise that any technological remedies that need to be considered, need to adhere to the qualification criteria of being effective and fast to implement. Based on our experience, Intelligent Automation (IA) is very well suited with the above context in mind.

IA can simply be considered as the activation of operational efficiencies and strategic advantages enabled through the deployment of digital capabilities. Although evolving, IA capabilities include, but are not limited to, Robotic Process Automation (RPA), Machine Learning (ML), Artificial Intelligence (AI), Object Character Recognition (OCR), Chat Bots and Virtual Advisors. The technologies themselves are independently proven and have already shown results, many of which have been deployed discretely and have unlocked tactical savings. Although impressive, the potential of IA lies in the ability to identify and integrate the afore mentioned exponential technologies to solve for fundamental business challenges, or opportunities. One such example could be the optimisation and digitisation of Business As Usual (BAU) processes that support new ways of working, as introduced by COVID-19.

1.    Supporting BAU processing and self-isolation: The increased requirement for self-isolation emphasises the importance of remote working which in turn, creates the requirement for increased connectivity and easier ways to support teams in following due process with limited or reduced oversight. As an example, consider a contact centre agent whose job it is to process multiple service query types, each of which requires the appropriate knowledge and expertise to execute the correct activities, following the correct processes on the correct systems, all dependant and varied based on client requirements. Traditionally this agent has been based in a large contact centre and has direct access to a lead agent for advice and guidance. In this context, IA can be leveraged to formalise the workflow that easily guides the agent through each of the required steps needed to service the request, ensuring the correct governance and risk management requirements are adhered to. In addition, while the agent is being navigated through the call, the workflow is recording and structuring the captured information and data points needed to execute the query. Post the conclusion of the call, the structured file can then be handed over to an RPA capability which will then execute the request on the required systems, whilst the agent has picked up and started processing the next call. 

The key objectives of this scenario includes correct processing, faster processing, reduced rework, increased client satisfaction and the shift of the required skills of an agent being able to follow processes to being able to effectively understand and solve client queries, in multiple languages. 

2.    Reducing direct contact between parties in the fulfilment of services: In South Africa, we are still very dependent on the completion of paper-based forms for processing requests. These completed forms are often assessed for completeness before being recaptured into existing systems. Although highly manual, these types of processes are very dependent on capacity and often require direct interaction between parties. Again, using a front of mind scenario, consider an administration clerk registering a patient at a hospital. A patient will enter a hospital and be required to register before being admitted. The admission process requires that the patient, or someone on behalf of the patient, completes a manual form which is then handed to the administration clerk upon completion. In addition to the form, the patient will also hand over identification, and in some instances a medical aid card, which is then scanned, or photocopied, and then returned. All details are then recaptured by the clerks. The application of IA in this instance can support remote or pre-registration that facilitates the full capturing of required details and images without an amination clerk having to directly engage with the patient. The same exact example can also be applicable to banks originating a client, or a service agent receiving and executing an instruction. The opportunity in this instance is not just reduced contact between parties but faster and more accurate processing that has limited to no dependence on the number of staff. In addition, IA, as a result of its capabilities and speed in processing of tasks, can also be leveraged for preventative and information-based processes.

3.    Ensuring optimal performance of business-critical processes: Although we have created awareness around a number of client facing scenarios, COVID 19 is industry agnostic and it is appropriate to considered that a large number of businesses have simply put business critical processes on hold as they have been unable to support remote working while ensuring risk is proactively controlled. In this instance consider the application of IA to a process such invoice processing where the application of RPA combined with OCR can extract the necessary data points from invoices, purchase orders and delivery notes, do the necessary matching and reconciliations and prepare the corresponding payment. The benefits in this situation is that regardless of the current scenario, the core requirement of invoice processing is being effectively and efficiently fulfilled, while ensuring that the necessary risks and controls are adhered to. This process is common to multiple businesses and can be quickly implemented to show immediate value and savings.

4.    The enablement of high-volume communications: From a social perspective, as the awareness and infection rate of COVID-19 increases, there will be increasing interest, or concern, in key topics such as how to identify key symptoms, what the real time infection rate is in the country, province or even suburb, which hospitals are able to admit COVID-19 patients etc. Instead of having multiple administrators manning a chat line, IA can be leveraged to facilitate a conversation with a user that is able to understand the request and successfully identify and compute the correct response quickly and effectively. Not only would this need to be real time, but this would need to be able to facilitate multiple sessions simultaneously with a multitude of different people all interacting at the same time. A solution such as this, can be supported by simply combining a digital agent with RPA and predictive analytics.

5.    The forecasting of no-go zones: To add to the above example, in addition to current information, the availability of predictive hypothesis-based analytics can also be very effective. By applying machine learning algorithms to infection data at a suburb level, combined with mobile Global Positioning System (GPS) data, models that estimate the likelihood of infection within specific areas can start to be developed. The same data can be used inversely when combined with regional sales data, to estimate low peak traffic and shopping times therefore recommending the most opportune time to visit your favourite store. Again, the application of IA can be linked to mobile devices to ensure that individuals steer clear of areas that may result in an increased risk of infection. From a healthcare perspective, these results can be consolidated to proactively inform hospitals of the number of patients to be expected, beds required to be prepared, and the extent and number of treatments that will be required. In the instance that the number of patients exceeds current capacity of a hospital, patients can seamlessly be referred to the next available facility.

Although the above examples may seem simple, they have been determined by the fundamental need to solve for supporting BAU processing during self-isolation, reducing direct contact between parties to limit infection potential, providing the basis to inform the public of how to “flatten the curve” and how to mitigate risk of exposure.

In summary

The impact of COVID-19 is still being understood and it has fundamentally changed the way that we interact with clients, with businesses, with our teams, our friends and families. To ensure that we remain relevant, it’s important that we adapt accordingly to not only survive but to remain relevant. Leveraging IA in what we do both in our professional environment as well as in our personal environment is no longer is an option, but rather a necessity.