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How to accelerate business transformation through continuous discovery

Shift to continuous discovery empowering ongoing improvement of business outcomes

This Deloitte UiPath collaboration affords a joint perspective on enterprise mining. We provide insights into the future of technology and automation for effective digital transformations.

Process Mining enables data to be leveraged in core business systems (legacy and new) giving a holistic view of business process regardless of complexity. Task Mining further illuminates how people perform their work tasks and captures details (steps) and scenarios identified in process deviations. Emerging technology like UiPath’s Communications Mining enables data to be extracted from business conversations like emails and tickets to find opportunities for process analysis and automation. Combined these technologies enable organisations to discover the actual as-is process, bottlenecks, and deviations, whilst providing transformation opportunities. Organisations need to carefully review the scope of deployment as these tools have different insights and subsequent benefits that they can identify. The wrong scope when deploying either tool can cause pitfalls if not joined up holistically.

New harnessed insights in data mining technologies and machine learning are enabling a shift in the way organisations operate, from reactive patch fixing to proactive transformation strategy allowing them to realise true value. UiPath and Deloitte have seen its best-performing customers embracing Continuous Discovery to achieve better business outcomes and improve business Key Performance Indicators (KPIs) because of its complete approach.

As highlighted below in figure 1, by utilising a combination of process and task mining, Continuous Discovery is the ability for companies to quickly turn insights into actions, such as process re-engineering or automation, whilst continually developing an opportunity backlog for further improvements. This approach enables organisations to realise value in shorter periods of time and monitor their investment ROI.

Figure 1

Bridging the gap between strategy and execution

Stakeholder alignment is incredibly important for digital transformation. Figure 2 below demonstrates how Continuous Discovery enables process owners and automation leads to work together and seamlessly optimise processes.

The connected offering of technologies effectively promotes a bridge between IT and business functions. This co-development of intelligent solutions means organisations can go beyond automation as the pursuant outcome. Business Leaders can cohesively align their organisations’ operations across people, robots, and processes and realise benefits such as intelligent workforce management, risk mitigation and control enhancements, improved KPIs such as customer experience, optimisation of automation programs, and much more. All with the same data that is readily available to the organisation underscoring the possibility to enhance and optimise core systems within its technology stack.

Figure 2

Through using Continuous Discovery companies realise:

  • automation is not a stop gap solution but instead, a strategic initiative, supported and controlled from the COE and critical business alignment established; and
  • fact based analysis empowers executives to act upon insights and much faster than traditional discovery methods.

Intricate insights developed through process and task mining allow process owners to assess opportunities holistically from a strategic point of view and rapidly double click into problems with task mining to truly understand process issues.

It is key to note that automation should not be used as an end game. It is a means to value: how to reach business outcomes, maintain processes in a most optimised state, and achieve 'automation-fuelled' transformations. This includes process re-engineering of complex end-to-end processes and automating effectively, where it makes sense, to reap reward of productivity.

However, Continuous Discovery is also enabling organisations to solve increasingly complex issues, resulting in a fundamental Organisational cultural and technological shift.

  • Cultural shifts are occurring as a result of the collaboration between human and machines, what Deloitte calls The Age of With™. This new age is where companies can gain an advantage by designing systems in which humans and machines work together to improve the speed and quality of decision-making. Changing the work that humans such as process owners in figure 2 can shift from repetitive manual tasks to higher value-add tasks.
  • Technological shifts include a greater use of Machine Learning, Automation (RPA), Process mining, Task Mining, Artificial Intelligence, Virtual Reality and much more as standard practice within organisations. This enables companies, automation leads (figure 2) and executives to shift from ‘now what’ to ‘what if’, allowing leaders to continually imagine their business of the future.

When looking to implement Continuous Discovery within an organisation it is always a good idea to assess the Top-down approach first. This approach harnesses executives’ views that are strategic rather than operational. It also ensures clear stakeholder alignment at senior level, consideration of the big picture and all components when making decisions. This macro perspective of an organisation’s transformation mitigates the possibility of siloed deployments and unawareness within organisations. However, diligence is required when using this method as sometimes organisations miss out on potentially good opportunities by eliminating areas that don’t initially fall into investigation, limiting quick win realisation.

Also, governance plays a big role in data-driven organisations as stakeholders will need to clearly define long-term success criteria, roles, and responsibilities of the Centre of Excellence (CoE), perform cost-benefit analysis and utilise change management.

With continued growth where is process and task mining going?

The key aspect is how to scale effectively for success in organisations. With the power of insights that can be developed, it can break silos and bring people together, between the CoE and lines of business. This harmonisation of CoE and process owners can enable organisations to shift from reactive to proactive.

With analyst consensus that process mining is expected to grow at a Compound Annual Growth Rate (CAGR) of 40 – 50% and growing convergence between process and task mining with automation, it’s no longer enough to focus purely on one alone. Organisations need to bridge the divide between automation, processes, and execution.

In the enterprise world, with many stakeholders and teams, process complexity, and variations, it is crucial to quickly attain value from technology investment, yet it can be a challenge:

  • to pick the best process, or even the best variation to focus on
  • to take action to capture the value produced by the insights
  • maintain an ongoing pulse to keep operations at most optimal level

Decision-makers will increasingly require an empirical, data-driven basis for process improvement, for evaluating their automation priorities, and for taking action toward their desired business outcomes. Continuous Discovery can be truly embraced when orchestrating the underlying technologies as it allows design for technology and human workforces to work together seamlessly and enables future organisations to:

  • Identify the as-is state of business processes holistically. Map the end-to-end however complex. View multiple dimensions including by system, by department, by the client or by user/ person.
  • Continuously understand the state of the business process and how business KPIs are affected, how they could be improved, where automation can have the highest impact, and how to keep organisational processes in their most optimised state.
  • Actively apply process optimisation and process re-engineering based on scientific data and methods. From simple alerts of exceptions/reminders to promoting defined steps as automations that leverage RPA bots to optimise KPIs.
  • Finally, continuously monitor the end-to-end processes to gather real time insight into processes' evolved state and their continuously changing context to feed the next decision.

As detailed in this blog it’s no longer enough to just stand back and consider Continuous Discovery. Organisations need to bridge the divide between processes, automation, and execution in order to realise the business of the future and stay ahead of the competition.

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