The intelligent automation journey: a few challenges ahead

Today’s need for automation is real and is not going away.

It is undeniable that the intelligent automation market is going through a rapid development and workers are somehow more inclined to coexist with virtual workers. From automation that just “execute” to automation that “think” and “learn”, the intelligent automation ecosystem is growing at fast pace and in an orchestrated manner.

The quest for more intelligent automation will be a promising and rewarding journey but without any doubt a challenging one.

• Given that intelligent automation is the next wave of innovation for large multinational organisations, there will be a race between business areas to be the "first one" to evaluate and pilot these new technologies. Without a macro view of on-going departmental initiatives, organisations will run the risk of internal cannibalisation and the consequences of that situation could be quite damaging. It is quite crucial to ensure that all initiatives are aligned and the net aggregated outcome is presented in a unified way.
• Getting the right intelligent automation strategy enabled by a balanced mix of technology enablers, supported by a well-defined service delivery framework and last but not least governed by an effective operating model will require proper design thinking. Will intelligent automation be deployed to serve specific tactical requirements of each business area or will it be used to holistically and gradually transform the workforce environment across the organisation? Should organisations put intelligent automation at the centre of their overall digitisation strategy, acting as a key enabler for front and back office transformation?
• Solving the initial automation silo challenge should be a priority. Defining automation principles and derived standards across the organisation will be required in order to ensure maintainability and interoperability of automation. Failure to enforce automation principles since the beginning will drastically limit the organisation's ability to scale and be resilient. To achieve this, commitment and support from senior leadership is a must-have (clear "Tone at Top").
• Significant ongoing co-investment between organisations and strategic service providers for defining and aligning the intelligent automation strategy will be the norm. Money will be spent on trial and error experiments, determining how to scale up the pilot and recalibrating the target operating model. Selecting and prioritizing the right projects for maximum ROI (and finding the required budget) will not be an easy task.
• “ You don’t reward reaction, you reward results” (Edwin Louis Cole). And results are measured through the realisation of expected benefits. Measuring benefit realisation from your intelligent automation initiative will certainly not be an easy task, especially when dealing with intangible benefits. Benefits will not be realised at the same time and organisations need to consider the "speed of onset" of each and every benefit in their overall benefit realisation plan.
• In many cases, optimal automation will require major process adaptation. Even if the change is minimal, the transition to automation will require change management. The key question here is how much will it actually cost to adapt or transform processes in order to enable automation? Is the organisation actually ready, financially and emotionally, to undertake a new "automation-enabled" transformation? Overcoming resistance to automation and managing the change will require planning, discipline, and effective communication. Don’t underestimate the operational fatigue that has been built up during the long and tedious IT-enabled business transformation years.
• Initial strategies for scale will face execution obstacles that can potentially slow down mass adoption. From a business perspective, deployment of intelligent automation at process levels will not consistently realise expected benefits. A wide range of processes and activities are and will continue to be highly unstructured and therefore resistant to automation. From an IT perspective, will IT functions feel that intelligent automation is another burdensome project that will stretch resources and create additional maintenance and support activities? Dependencies with other ongoing IT and business transformation programme or termination date of existing outsourcing contracts will also create an initial bottleneck that can block your aspirational plan.
• Ongoing reliability challenges will create business fatigue in the organisation. Reliability is an important determinant of human use of automation because of its influence on human trust. Lack of reliability could simply totally undermine the benefits of your intelligent automation programme. Hence ensuring high reliability will be one of the most critical focus when applying intelligent automation.
• Resilience and adaptability are key in order to sustain changes to the internal and external contexts. A wide range of factors, ranging from ongoing changes to technology, process, data and customer behaviors, will directly impact the effectiveness of the intelligent automation environment. The deployment of a continuous monitoring system coupled with a flexible human-bot collaborative control must be an integral part of the overall intelligent automation framework in order to allow fast recovery when automation fails.
• It is not a surprise that compliance oversight functions and independent assurance providers will spend non negligible time and effort during initial years to perform a wide range of “baseline” assurance activities in order to ensure that intelligent automation environment (people, process and technology) is reliable. What about robots running critical financial activities or accessing and processing sensitive HR information? What about the auditability of a deep learning algorithms for example that are used to learn and take decisions? How auditors will be able to evaluate the effectiveness of these algorithms knowing that machine learning systems have a low interpretability? A lot of scrutiny will be applied and let's be honest here, this situation will inevitably end up costing money to all organisations.
• The tricky question of resource reallocation mechanisms needs to be addressed in a holistic and procedural manner. Training future employees and re-training current ones will be a significant challenge. But how will the resource reallocation process will actually be executed and who will pay for it? Will it be easy to reallocate a resource to another existing function/ process by “augmenting” skills? Or convert an accounting data entry/ reconciliation person into a virtual agent calibrator or a data insight curator?
• In addition to key drivers such as increased productivity, reallocation of resources to more value-added activities or better customer service, cost reduction will remain a key driver for investing in intelligent automation. There is no doubt that reducing operational costs will be a quick and easy win. But will it be as simple for organisations to deploy intelligent automation in order to ultimately create business value and boost agility?
• There will be non-negligible security concerns regarding the risk of the entire intelligent automation environment being vulnerable to data manipulation. Now that intelligent automation is actually increasing the level of digitisation and networking, how to ensure that the environment is reliable, secured and cannot be tampered by unauthorised activities? Cost related to security administration and monitoring must be factored in projects and BAU budgets.

I hope you enjoyed the reading and I would be very interested in hearing your thoughts. If you want to read more about automation, please check my other posts:

RPA: 6 checks that you must perform before releasing a bot in production

RPA operating model: evolve to succeed

Robotic Process Automation: Think Resilience

The forward-looking benefits of RPA

RPA bot development: power to the business

High levels of automation can also have negative consequences

Opinions expressed are solely my own and do not necessarily express the views or opinions of my employer.