Automation in operations is the next big thing that is a big leap toward continuous and technology-enabled redesign of crucial operations forming an instinctive ‘operations to technology’ cycle in which technology enhances operations and vice versa.
Of late, operations leaders across major sectors are incorporating the latest automation tools and techniques in sync with their long term modernization strategies to swiftly digitize the last rung of processes within an organization. By integrating the advances in IT and organizational redesign, operational leaders can transform their operations into technology. This is the technology that they can eventually manage, own and consistently enhance to minimize the costs drastically while improving the quality and timeliness.
The big picture looks really alluring; however, our operations and senior leadership teams really driving this initiative? The paramount reality is most of these teams set their expectations quite less, which ultimately poses hurdles in realizing the value even in their initial leg of their journeys. The main concern is companies lack a clear target and a strong vision to modify their operating models, and the net results are quite obvious. Tentative investments, minimal impact at scale, abandonment of projects with focus only on point solutions are some of the outcomes, which is contrary should have been on constructing a true model for execution and incessant improvement.
Moreover, companies need to know how best they can leverage these tools and technologies, since using it in a chaotic and unorganized way leads to operational disorders and complicated processes that are difficult to redesign. On the other hand, managers also find it a challenge to manage a virtual workforce. However, if an organization is able to handle it in a proper way, these tools pave way for the first stage of an accelerating and consistent technology enabled redesign in multiple operational domains, reinforcing operational elasticity, while enhancing the productivity.
What does an organization need to do to break these shackles?
>> Devise instinctive ‘operations to technology cycle’ that lets the organization comprehend what exactly an operation model looks like within the context of automation and the next generation operating model.
>> Identify the greatest challenges that managers’ encounter, while planning to introduce or accelerate the operations to technology cycle.
>> Develop an effective short-term playbook to let managers mitigate these challenges, generate sustainable outcomes in both the short and longer terms, generate newer opportunities for employees and change the vision to enable continuous improvement within the organization.
While companies boast of a great history of combining the technology and operations iteratively, most institutions still struggle to leverage the innovative IT tools and technologies in the context of a highly complex, cost-driven and error-prone operations.
It’s not that organizations are immature to integrate technology with operations. There have been several instances in the past, wherein organizations had leveraged the lean and other operational excellence approaches that helped in enhancing the customer focus, minimizing the waste, increasing the transparency and generating a culture that had driven continuous improvement. However, such efforts in isolation do not yield results when IT systems are costly, complex and take time to integrate with the highly manual and disintegrated processes.
Futuristic vision in the wake of technological innovation
The future looks bright with several innovative technologies flooding the market such as process mining and natural language processing tools, robotic process automation (RPA), robotic desktop automation, machine learning, artificial intelligence (AI) and enhanced data-management tools, to name a few. These technologies have set new expectations, wherein organizations can modernize complex systems, automate manual processes and retrieve data to generate meaningful analysis and insights to swiftly identify and resolve the root causes, gaps or other pertinent issues.
This new paradigm of integrating technology with operations is called a continuous improvement cycle that transforms operations into technology. What does it mean? It codifies all the manual steps and rules that are existent in several operation shops and also the virtual playbook that exists in the heads of the operations personnel. The outcome is a set of automated steps that bots can easily and swiftly test, update and execute. And above all, these automated tools can also generate audit trails and new data, for bottom-up (for specific work being executed) and top-down (on how processes are getting executed). This eventually leads to fresh analysis, better insights, and spurs data-driven decision making.
Technologies that companies can leverage
Machine vision, natural language processing, and process mining are some of the processing tools that let an organization analyze additional data sources including desktop actions and log files. This eventually helps operators with a valuable treasure of insights and knowledge to optimize the processes and also probe and eliminate the root causes. This is the best approach to trigger a powerful flywheel of consistent improvement, which operations teams can leverage.
The permutation and combination of these tools and capabilities, when used in the right ways is overwhelming. Some of the leading organizations across the world are using this flywheel to achieve efficiencies of more than 50 percent over the next three to five years. It is noteworthy that one financial institution has used this flywheel to minimize 45 percent of its costs across operations in two years while being on the right track of further savings and enhanced business opportunities. Another financial company used this flywheel concept to redesign and automate its global operations to minimize costs by 50% while eliminating huge duplicate work and downstream errors. These savings will further drive these organizations to focus more on data-driven client service that offers immense value in the long run.
This cycle has become a reality only in the last couple of years with the advancements in automation and machine learning. The depth and breadth of the processes that can be automated have increased tremendously – from simple data entry operations to more knowledge-based processes that can generate insights from data.
Challenges and opportunities
Let’s briefly analyze some of the key challenges and opportunities of this flywheel approach in the context of phased planning.
Analysis and Review process
What is most important in this stage is identifying opportunities and engaging IT to accomplish the right level of granularity. This helps the process owner to have a macroscopic view of the processes and comprehend their performance. Often, it may so happen that when granularity is too high, businesses find it daunting to automate because of myriad exceptions. Also, when it’s too low, the complexity and the business case outcome looks challenging.
In order to ensure the success of this phase, an organization needs to identify opportunities to simplify, reorganize and standardize processes and at the same time minimize the exceptions, before it begins to probe into the next level of detail. An organization needs to discard the variants that have low value, which itself can be identified as an opportunity for continuous improvement. The success story lies in executing the work in quick sprints, instead of trying to map all cases and exceptions completely on the first iteration itself.
Technology enabled redesign
In this phase of digital transformation, an organization needs to probe deep as to what’s stopping it from automating its processes, end to end. It needs to ask some practical questions. Can it have rule-based processing to minimize exceptions and manual processing? Can it leverage the latest automation technologies? It’s prudent to understand each potential barrier, along with a realistic perspective of feasibility and the required effort to prioritize actions. Even assuming that the real benefits of digitization might trigger after a few years, it is required to understand that there are short-term automation opportunities that can dramatically minimize the digitization effort’s growing risks and implementation cost.
Setting the pace for automation
In automation and digitization, new technological innovations are disrupting the operations of an organization, wherein in-process data gets generated that helps companies to leverage for continuous improvement. Some of the discussion forums help technology heads to swiftly solve common challenges, based on certain parameters including common configuration standards, standard practices, teams restructuring, IT architecture organization, and open-source solution platforms.
Impact and data analysis
Last, but not the least, in impact and data analysis, operations managers must take ownership to successfully drive operations as technology. Advanced automation tools in conjunction with natural language processing tools and process mining can help managers analyze more data than traditional statistical tools, which can help unlock potential opportunities, suggest priorities and offer continuous monitoring. Organizations should adjust performance targets accordingly, spilled across all levels of the organization and owned by the operations team.
What to expect?
Once this redesign of flywheel commences, organizations can plan bigger and set their goals to higher echelons. Simplistic cost reductions and enhanced reliability and customer-facing capabilities are just the tips of an iceberg of process maturity and rapid organizational transformation. So, let’s get ready to tap the innumerable opportunities thrown open that can help your organization swing toward operational agility and performance excellence.
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