These days, companies have a myriad of problems to deal with that are slowing down their throughput and increasing their operating expenses. Some of these problems include:
- Using antiquated, legacy software that isn’t keeping up with business demands
- Integrations between systems
- Lack of open APIs to move data in and out of systems easily
- Using people, not technology to operate these systems
- Data integrity issues
These issues have led to linear increases in operating expenses for companies as they scale revenue.
It starts with repetitive clicks
A behavioral healthcare company, was challenged with a repetitive-click problem. Their end-to-end invoicing process took a person 45 clicks to complete. After walking through the process with the process owner, on average, it was taking that person 30 minutes to complete the task. In addition, only one invoice could be processed at a time, leading to a max output of 15 invoices sent per day per person.
This company had two people responsible for this task every day, so the max output of invoices sent for this customer was 30 invoices per day.*
*Note: 30 invoices per day max output for this customer was leading to a growing backlog of invoices not being sent out.
Then the as-is cost must be assessed
Once we calculated the as-is max output, we were able to assess the current cost per invoice sent by using this equation:
Cost per invoice sent = (Fully-burdened hourly cost of person) * (Person time spent sending one invoice)
The company was spending on average $9.06 to send each invoice using two people.
Knowing the transactional cost (per invoice sent) is the first key metric that is needed in the value equation.
Next, the to-be cost must be assessed
Through analysis of the current invoicing process, it was determined that 90% of the process could be automated. In addition, it was estimated that a bot could perform the task in 1 minute versus 30 minutes. this equation to determine the to-be cost:
Cost per invoice sent = (Hourly labor rate of bot) * (Bot time spent sending one invoice) + (Fully-burdened hourly cost of person) * (Person time spent sending one invoice)
The Company would spend an estimated $1.11 to send each invoice using digital workers.
This is an 87% cost reduction. Using a basic framework, we can bucket this cost savings into a simple value assessment.
- 1-20% cost savings = Low Value
- 21-40% cost savings = Medium Value
- 41%+ cost savings = High Value
In this example, 87% cost reduction is a grand slam from a value perspective.
Last, the automation complexity must be determined
How complex an automation is, determines its feasibility and likelihood of operating successfully. At Bunch Digital, we use a complex analysis to determine this scoring, but to keep it simple, I’ve broken it down into a basic high-level framework.
- ≤ 75 clicks
- 1 – 3 systems
- No Machine Learning, Artificial Intelligence, and/or Object Character Recognition
- 76-150 clicks
- 3 – 4 systems
- Some Machine Learning, Artificial Intelligence and/or Object Character Recognition
- 150+ clicks
- 5+ systems
- Major Machine Learning, Artificial Intelligence and/or Object Character Recognition
In the invoice example for our customer, their automation scored as a low complexity automation.
For the invoice automation example, it rated super high on value and low on complexity.
For opportunities that fall in this category, there is high ROI and low payback periods for investment in automation.
All of this information can seem overwhelming. That’s why we help our customers in the first part of the automation journey… the discovery phase. Our automation experts know how to assess use cases for value and complexity to ensure you’re prioritizing the right processes to automate and deliver 150%+ ROI in year one.