Four Keys to an “Automation First” Strategy for CIOs
In earlier blogs, I described the concept of the “Automation First Mindset ” (AFM) and why it is essential for enterprises seeking to drive operational transformation.
Now, let’s define four keys to achieving the potential of Automation First – and how CIOs can lead the charge.
One: Show Don’t Tell
Being an AFM champion requires credibility and confidence – specifically among boardroom stakeholders. CIOs can establish that credibility by applying an Automation First Mindset (AFM) to IT operations and by demonstrating its possibilities to the business.
CIOs are driving automation into delivery functions like service desk ticket management and network monitoring. While yielding tangible benefits and cost savings, such initiatives can serve a deeper purpose of broadening automation expertise to apply to a wide range of business processes and extend across the enterprise. The strategy and skills to drive this effort need to align with the broader context of a long-term vision for automation.
Take cybersecurity – as Oracle CEO Larry Ellison points out, the worst breaches in history have occurred after a threat was identified and a fix was available. The problem is that traditional human-centric processes are outright slow and error prone, often requiring approvals and scheduling of downtime to apply a patch. This creates a window that allows the threat to wreak havoc. Removing people from the equation, meanwhile, closes the window of vulnerability. To address this problem, Oracle reimagined the database as an autonomous, smart entity that monitors and identifies threats and self-patches solutions.
The key to AFM is to select one or more critical business processes and to re-imagine them operating in a completely unattended and autonomous way. Using the principles of Design Thinking, a team can build a tangible prototype of such processes or systems that can be visualized and discussed. This exercise can define an action plan that aligns with strategic intent of the business, while enabling quick wins and tactical progress.
Two: Map the Friction Points
Once the task is defined, the AFM is applied to documenting the steps involved in traditional business processes. For example, the insurance customer who files a claim for fire damage to his home contacts an agent, describes the damage, obtains repair estimates and receives payment. While this is occurring, back-office processes track the filing, review, and status of the claim and payment.
Working with business owners and process experts, the CIO can track the steps in this customer journey, as well as the corresponding back-office processes. This documentation exercise – which may already be underway as part of a digital transformation initiative – identifies specific points of manual intervention that create inefficiencies, delays or opportunities for errors. These can include, for example, the requirement of a manager’s approval, or admin’s inputting or transferring of data from one system to another.
Once identified, points of manual intervention become tactical automation opportunities to assess and analyze: Does the human intervention involve specific and repeatable steps? Are decisions made by humans based on clearly defined if/then rules? If the answer to those questions is “yes,” task automation could be a viable option. Subsequently, the expanded set of automation capabilities can be applied in the most cost-efficient and impactful ways.
Three: Prioritize
Identifying which automation candidates to pursue first is essential to an AFM. An impact/complexity map can help CIOs highlight the processes that yield the most value while requiring the least amount of effort to automate. Concurrently, the prioritization effort develops and incorporates new and specific automation capabilities.
To take the homeowner’s insurance example, a top priority would likely be an easy-to-automate manual intervention that significantly reduces the cycle time of claims review, thereby delivering value through an improved customer experience. At the same time, an AFM strategy can target seemingly less attractive manual interventions over the short term.
Four: Repeat as Necessary
Following implementation of an automation cycle, an AFM strategy requires reassessment to identify and address remaining manual interventions within the re-imagined process and to define competencies and capabilities to gain additional rounds of insight. This triggers a new cycle in which to develop key new capabilities and drive additional tactical efficiencies.
With each iteration, the low-hanging fruit becomes increasingly scarce and the manual interventions harder to identify and eradicate. But while the immediate benefit of each incremental gain in automation may appear increasingly minimal, over time the process creates a virtuous cycle of machine-enabled improvement where operational data is collected, analyzed and acted upon by smart tools. The result is a radically new way of attaining a vision that might have otherwise seemed impossible, while at the same time improving operations and developing new ways to solve business problems.
Given their role at the intersection of technology and business, CIOs are well-placed to help articulate the long-term vision and evangelize the AFM throughout the business. They can identify proof of concept opportunities, quantify benefits and provide key capabilities. Moreover, CIOs can offer an enterprise-wide perspective that considers the big picture beyond the immediate ROI of a tactical automation initiative, securely steering the organization towards the highly automated (and profitable) future state.
What do you think? Can AFM raise the operational bar to a new level?
Beginning in this new year, we’ll shift our focus to assessing tools and templates that can be applied to bring an AFM to life.
Rajeev Tyagi, Chief Operating Officer of Softtek US Market.
enterprise/high performance architect at Softtek
7 年AI, for example Hierarchical Task Network (HTN) planning could be a good candidate to orquestating automation processes?. Scala, AKKA, Kafka?. Scala based tools seems to be a good approach, instead of BRM or alike. Intensive computation can be solved economically(?) using GPUs. The same principles apply to a general platform for IoT, micro services and more, with a strong AI support. Just ideas.
Strategic Enterprise Architect
7 年Nailed it Rajeev, hope you're well ~