The intelligent automation journey: 13 challenges that you must overcome

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

It is undeniable that the intelligent automation market is going through a rapid development and we, humans, are somehow much 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 has always been a promising journey, but without any doubt a challenging one. Here are the 13 "macro" challenges that still burden large organizations:

• There is still an "unspoken" race within and between IT and business areas to be the first one to run the show. Without a macro view of on-going initiatives and BU/function levels, organisations are running the risk of internal cannibalisation and the consequences of that situation is very damaging. A proper intelligent automation program shouldn't be deployed to serve specific tactical requirements of each business area. It must be launched from day 1 to holistically and gradually transform the workforce environment across the enterprise. Intelligent automation must be at the centre of the overall digital strategy, acting as a key enabler for front and back office transformation. It is quite crucial to ensure that all initiatives are aligned toward a common vision and solving the initial automation silo challenge must be the top priority.
• Defining automation principles and derived design standards across the organisation is required in order to ensure maintainability and interoperability of the overall intelligent automation environment. it's not a nice to have exercise but a crucial one, and doing this "on the fly" is not option. 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.
• The right intelligent automation strategy must be enabled by 1) a balanced mix of technology enablers, 2) supported by a well-defined service delivery framework and last but not least 3) governed by an effective operating model. It's not one or the other, it's one and the other. Excelling in one but struggling in another is like building a house without considering all the structural support and foundations necessary to make that house strong and capable of withstanding contextual changes. And with intelligence automation, it's all about staying in control of contextual changes.
• You cannot sustain an intelligent automation program without keeping the necessary internal roles and core expertise alive. And to achieve that you must embed a wide range of roles, from architecture to operation, right into the fabric of your organization. In addition to service providers that will help you run business as usual activities (through their development factories and operation centres) and provide you the much needed capabilities to progress in your journey, you must ensure that key internal roles (at global and local levels) remain in-house to keep invigorating the intelligent automation journey and ensure that you don't loose momentum. Intelligent automation introduces new emerging technologies that bring complexity and you must ensure that you have the right internal talent to run and scale them.
• Significant ongoing co-investment between organisations, customers, and strategic service providers for defining and aligning the intelligent automation strategy should be the norm. Money but 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 and it crucial to bring the ecosystem together to take the most suitable decisions in a collective manner.
• “ 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 is not an easy task, especially when dealing with intangible benefits. But you must measure your outcomes. It is very important to keep in mind (and manage your stakeholder expectations accordingly) that benefits will not be realized 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 appropriate 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 will potentially slow down mass adoption. But don't give up as this is perfectly normal. 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 resistant to automation. From an IT perspective, IT functions might 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. But again, don't give up.
• Ongoing reliability challenges will create business fatigue in the organisation. Reliability is probably the most important determinant of human use of automation because of its influence on human trust. Unreliability creates operational frictions (time spent for recovery and root cause analysis) and add significant costs to the overall operating model (more human intervention is required to restore the automation). Lack of reliability could simply totally undermine the benefits of your intelligent automation programme. Hence ensuring high reliability should 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 initial deployment of a holistic 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 risk and compliance oversight functions will spend non negligible time and effort during initial years to perform a wide range of “baseline” assurance activities in order to ensure that the intelligent automation environment (people, process and technology) is reliable. What about automation running critical financial activities or accessing/ processing sensitive HR information? What about the auditability of complex machine learning algorithms that are used to take more and more complex and autonomous decisions? How auditors will be able to evaluate the effectiveness of these algorithms knowing that still many 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. It's good to have a great HR strategy on paper, but it's even more important to properly execute and this is certainly not a walk in the park. Training future employees and re-training current ones will be a significant challenge. How the resource reallocation process will be executed and who will pay for it? How employees will be incentivised to actually learn new skills in addition to their day to day activities? Will it be easy to reallocate resources to another function/ process by just “augmenting” skills? Will it be easy to convert an accounting clerk into a virtual agent calibrator or a data insight curator?
• 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? Appropriate management of non-human privileged access across the enterprise will certainly not be an option. Cost related to security administration and monitoring must be factored in initial projects and subsequent BAU budgets.

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