(This Web Exclusive by Scott Nelson originally appeared on Monitor in September 2022)
Everyone has heard the saying about doing things right vs doing the right things. Being really good at doing something that doesn’t matter, doesn’t really have much benefit. But the lesson is not about making a choice; it’s about understanding the two “rights” and doing both to be more productive.
Doing the right things is about producing results that matter and being effective in one’s mission. Doing things right is about operational excellence and being efficient at what one does. Companies that focus on building and managing teams that perform both effectively and efficiently, deliver on an important equipment finance business goal, productivity.
However, leaders are plagued by a set of challenges that prevent them from achieving this productivity aim. Many know what they need to do to be effective, but they don’t have access to the data or insights they need to measure and manage the output. Those that have begun their digital transformations may have access to data, but the data may not be in one place, so analysis-to-action is often difficult or time consuming. Lack of the proper data and analysis tools forces some to continue to rely on past experience and intuition, which do not scale or drive growth.
The lesson here: Be aware — know what matters, know your measurements, know your data. When you know these things, you can build business intelligence and leverage new tools like AI for automation to become more efficient and effective and drive greater productivity.
Measures that Matter: Being Effective
What does it mean to be effective in equipment finance? Simply put, being effective is delivering the results that were desired. Three groups of stakeholders integral to equipment finance success are customers, shareholders, and employees/partners. By considering the primary results desired by each – and results that matter to each – one can identify the business measures they each need to be effective.
Table 1 Digital measures that matter to equipment finance stakeholders.
|Stakeholder||Desired Results||“Effective” Measures|
|Employee / Partner||
The table highlights how measurements of effectiveness in equipment finance – deals approved, deals funded, revenue, margins, win rates, and growth of the business – can focus both leadership and employees on the right things that need to be done in order to be effective. Further, when these measures are part of the digital operations of the business, the application of analysis tools and the use of AI to drive the second part of productivity, higher efficiency, becomes more realistic.
Digital Workflow Automation: Becoming More Efficient
Success in equipment finance is all about volume. An equipment finance business has to replace nearly one third of its book-of-business every year just to maintain its position in the marketplace, even more if it wants to grow or to capture market share. A strategy to drive greater efficiencies is looking at the operational workflow from the point of view of the customer. More and happier customers mean more volume and thus greater business success.
Figure 1 Equipment finance workflow from the customer’s perspective.
Another measure of efficiency is dividing total output by total input. A workflow defines both outputs by stage and the inputs: dollars funded, applications, approvals, and, of course, time. All measurements are made relative to the workflow participants of each stage that address efficiency. The table below lists the efficiency measures for a customer-centric equipment finance workflow.
Table 2 Workflow efficiency requires granular identification and measurement of inputs, outputs and participants.
The Efficiency Measures column shows how to properly measure workflow enabled action. When Inputs and Outputs are tagged by ID, stage bottlenecks and relative performance are easily identified for corrective action. AI tools can be applied to those reviews that need help with decisions or need to be fully automated. Focusing on measures that matter to the customer provides transparency across all stages and participants of the workflow can learn how to improve what matters to the business – more and happier customers.
Getting to the next level of productivity in Digital Finance
The adage “haste makes waste” provides an underlying cause for why equipment finance organizations are not closing more deals faster. Part of that root cause is risk. If time measures are taken with a granularity that can highlight the steps where risk is measured and taken, all the steps before and after can then be improved without increasing the associated risks. The dashboard below is an example of AI and automation can improve the workflow pre and post credit reviews. There is a more intense focus on the efficiency of those specific parts of the workflow and automation can increase the volume as well as the capacity of reviews by approving them automatically. Thereby reallocating human resources to other tasks.
Figure 2 The Productivity Dashboard highlights volume produced by labor input as well as time and efficiency per stage through focused improvement efforts.
The Productivity Dashboard shows average Revenue and Margin per FTE and is backed up with underlying data – supplying information on every component of the average. The chart shows the business average, but also the analysis of the average when both outputs and participants are identified. This allows equipment finance teams to leverage the most productive resources in the workflow and drive greater productivity.
Economists like to measure productivity at a macro scale, e.g., GDP. This is a simplified measure of productivity but does not actually help to improve productivity; that happens at the micro level. The same is true in an equipment finance business. One can measure productivity at a company level like “Revenue per head”: and this is an important start, but to improve this measure, business leaders need to identify the bottlenecks and soft spots in order to fix them.
Top level measures alone do not improve the business. That requires a level of detail for input, output and participant data that can be collected, analyzed, and modeled for each resource and process step in the workflow. A properly built Productivity Dashboard will quickly show a CEO if the business is heading in the right direction as well as help them drive productivity – by being more effective AND efficient.