Operational Metrics to make your Automation Program Soar
Shail Khiyara
Top AI Voice | Founder, CEO | Author | Board Member | Gartner Peer Ambassador | Speaker | Bridge Builder
Depending on the publication of your choice, it is stated that about 30 to 55% of automation programs fail. Various reasons are cited for this unanticipated outcome amidst two common threads - metrics and change management.
The hidden costs of automation are no secret. Approximately 30% of the cost of automating a process is tied to the licensing costs of software. A staggering 70% is made up of services, infrastructure, hiring developers etc.
Part one of our series outlines the Finance metrics you can consider to judge the success of your automation program. Part two, outlined the Business metrics to consider. Today we consider the operational metrics required to measure the success of running an automation program (i.e. process, program and digital worker metrics).
Operational Metrics of an Automation Program
Your CFO has the software used to measure finance metrics, Marketing has ways and over 1000 tools available to measure marketing effectiveness, Sales as you all know, is heavily metrics driven. There are metrics to measure sales efficiency, velocity and my favorite, Vitamin R (revenue). How are operational metrics related to your automation program measured? Are you relying solely on an RPA vendor analytics solution? What is the single measure of success for your COE?
It starts with the process. Regrettably firms have found out, often late in their automation journey, that they have selected the wrong processes to automate. This has resulted in fragile bots, costly maintenance cycles and sometimes failed automation programs. Inefficient bot utilization and euphoric buying of bots in bulk has led to many bots sitting on the shelf. A significantly high (80%) number of customers have approximately 10 bots in a market of about 28k customers.
"RPA & IA is your single best opportunity to revisit and rethink old legacy processes. Fresh people and minds should be involved in the process assessment and analysis phase, so that they can challenge the status quo without any emotional connection with it. The more you challenge and question the status quo, the better solutions you deliver. The problem doesn’t only lie on the old and legacy processes though."- Konstantinos Vogiatzakis, Global RPA Lead
1. Cultural Transformation: One of the most misunderstood, underestimated and often mismanaged attributes that shapes and automation program is culture. Try asking the question in your automation circles "what is your budget for cultural transformation"? There are several metrics that come to mind here.
- Program/rollout KPIs: The number of volunteers involved and actively participating in giving you ideas for your automation program. Ideas rejected vs accepted ratio also highlights what was considered vs just accepted for automation.
- My favorite and self-coined - Automation Emotion: The degree of excitement around a corporate automation initiative measured by behavioral KPIs often through internal surveys.
- Digital Talent Velocity: Speed at which re-skilling employees to become digital citizens in your organization? (different from #16 below)
Video 1: LPL Financial, Deepika Chopra on the ying-yang, qualitative and quantitative metrics and cultural transformation as the driving force.
2. Process Break Even Time: Simple processes reach breakeven in 2 - 4 months, medium complexity processes in 6 months, while highly complex processes reap ROI anywhere between 6 - 24 months.
The better the process selection for automation, the more efficient the processing and operation of digital workers, the lowest the run cost and the better the overall automation business case.
"We all know the keys success factors for getting an initiative or project delivered successfully; a clear vision with an understood strategy, a sponsor backing a business case aligned to the strategic goals, great capability (tech and people) and a super change program backed by a culture that rewards action." - Elaine Mannix, Global Insurance Leader
3. Operational Elasticity: In 5 Ways to Overcome Passive Resistance and Drive Organizational Transformation, I defined Operational elasticity as the a mode where adequate time and the right resources are in place, to effectively accomplish a purpose and produce the intended, expected result. In an automated environment it is loosely defined as capacity created. A better way to measure this would be 'capacity deployed' and where - vs just hours saved back to the business.
4. Customer Experience: Consistent measure of reduction in repeat contacts, customer complaint volume, backlogs, improved NPS.
Video 2: Thames Water UK, RPA Lead Nikki North with insights on Customer Experience, measuring journeys and increasing customer satisfaction.
5. Number of open positions filled by robots or created by automation and no longer requiring filling as they replace human workers v. those filled by automation.
"I believe that we will not "lose our jobs" to AI and robots. Use of automation will make our lives easier, taking away those boring repetitive tasks, helping us find our 'centre of genius' and our unique human resource. AI and robots will help humans create more value, give us more time, and the ability to - just be human" - Coreyne Woodman-Holoubek, Progressive HR Podcaster, LinkedIn Live Host
6. Project Delivered ($) - Annualized return from automation e.g. total FTE saved ($), Errors and Omissions avoided ($) and revenue generated ($)
Video 3: Thermo Fisher, USA Ankit Thakkar on dollar cost out, cost avoidance and incremental cash flow.
7. Size of Pipeline ($) - For an automation program to work a continued, sizable pipeline of automatable processes needs to be maintained.
8. Audit passes or fails - audit teams are there to support the secure and efficient running of business programs. Overall fails or passes per year indicate the general health of an automation program.
9. Process - Robot density - a measure of the number of, or percentage, of an organization's processes interacting with and positively impacted by automation and digitization.
10. Number of processes deployed / Time processes wait in test or development environments / Time to deliver processes - to deliver value from digital workers, digitized processes need to run off an automation production line. The faster the development cycle, the more code and digital workers can go into production to deliver value.
11. Object Reuse - Every time an organization reinvents repeated use of code, it costs money. The more code that can be reused the faster the development cycle and the cheaper the cost of automation delivery. While we expect new processes and code to be developed as the tentacles of automation spread across the organization firms should create an object library, design and re-use at least 80%+ of the code they possess.
"Object or code reuse is important for reducing costs and increasing the efficiency of software development processes, especially when scaling systems" - Iurii Shubin, Head of Intelligent Automation
12. Number of transactions processed day/month/quarter/year-on-year - the higher the number of transactions transacted by robots, the more time saved that can be reused for other purposes, including innovation. To derive the maximum value possible from automation organizations must seek to maximize the output from their existing bots (i.e. 20/7 processing or increasing number of efficient bots running multi-code/threaded processes).
"Hours Saved, Cost Avoidance, Peak Volume mitigation, Human error reduction and process leverage (hard to measure but what else can you now do with an automated process vs a manual one with resource limitations)." - Adam Bilson, Group Intelligent Automation Lead
13. Change Requests Received / Approved / Rejected / Completed / Unexpected - the higher the number of unplanned code changes, the higher the cost of maintenance and the lower the amount of time spend creating new code as automation staff fight to keep existing bots alive and working.
Video 4: RPA expert at F500 companies, Doug Shannon on COE time spent, building resilience and creating a stable automation environment.
14. Percentage of Process compliance (effectiveness): Bot do what they are told for as long as you have them running, or until they break (yes bot fragility is real). Process compliance can be significantly improved using bots, particularly for routine work with minimum to no exceptions.
15. Rework Hours (post-RPA) / Rework Hours (pre-RPA): Automation allows firms to eliminate the errors that are unavoidable with manual efforts. This can be measured as the amount of work that needs to be done to compensate for errors before and after RPA implementation.
16. Measuring Digital Competency: Measures the number of certifications within the automation, digital or overall business teams. Higher number of digitally certified staff employed, over a period of time, can point to the growth in the digital DNA of an organization.
Conclusion:
Automation programs can scale or fail based on metrics and change management. Failure to align your management team on Finance, Business and Operational metrics upfront, could stand between a soaring or declining automation effort. While every functional group has a measure, what is the measure of your COE? Organizations that efficiently manage the inputs and outputs of their program find they can maximize their business objectives and make their programs soar. Vision without execution and measurement of that execution is indeed, hallucination.
About the authors:
Shail is recognized as a thought leader, advisor and investor in RPA & Intelligent Automation. He writes extensively about digital transformation & automation and has served as a CMO & Chief Customer Officer of three leading automation firms, helping shape the industry. Shail founded & runs VOCAL (Voice of the Customer in the Automation Landscape) an independent, global automation customers only council, comprised of over 50 global brands. He is also an Advisor to multiple RPA & AI firms. LinkedIn and Twitter.
Kieran is recognized as an digital transformation, intelligent automation, data analytics and robotic process automation industry leader.
He writes and talks extensively about better ways for businesses to use digital and intelligent automation technologies to drive business performance. Follow him on LinkedIn, join him monthly on LinkedIn Live.
#intelligentautomation #bots #rpaworks #digitaltransformation#roboticprocessautomation #rpa #cognitiveautomation #digitaldisruption#digitalworkforce #processautomation #digitalfuture #digitalstrategy
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Manage @ Engg Programs
3 年@Shailkhiyara little late to read this but this is amazing. A must checklist for every COE .Reusable components should be a way to go and Pipeline and Audit controls are my Favorite things. But I know a lot of senior management stuck on hours saved which will eventually fail COE.
Founder Led Sales | SAP & AWS Sales | GTM | Pipeline Creation | SPJIMR | Deutsche Bank | HCL | Infosys
3 年Very Insightful Shail
C-Suite Executive / Strategic Advisor
3 年Terrific insights! ROI! ROI! ROI! Goals = well defined with clear measurements for success. Thank you for sharing!
Enterprise Data and AI Leader at Thermo Fisher Scientific
3 年Thanks Shail Khiyara and Kieran Gilmurray for having me as a part of this wonderful series. It is great platform to collaborate and learn Industry Practitioners. Thanks for the initiative.
Senior Vice President | Digital Transformation | Innovation | Product Management
3 年So excited to be part of this series and learning from other leading practitioners in this community! Great article Shail Khiyara and Kieran Gilmurray … Thanks for the opportunity!