Part 2 of a 2-part series about how finance teams can apply new technologies to improve enterprise performance. Read Part 1.
In Part 1 of this series, we explored whether it’s worth it for finance to adopt smart technologies – and revealed that the typical finance organization can reduce process costs by 41% by optimizing its technology landscape and deploying new technologies. But as with any transformation initiative, challenges exist. That said, there are best practices for getting started and avoiding pitfalls.
How do you align the right automation tool with the right process? The first step is to determine the type of work that’s being targeted, the process and automation complexity, and the appropriate tool to use, and ultimately to build a prioritization and integration roadmap. Work can be bucketed into three types: structured work that applies prescribed rules, methods, or scripts; knowledge work that applies knowledge or some type of creation or decisioning; and interaction work that is non-scripted collaboration with people. By determining the kind of work that is being executed, it’s easier to see what tool might be most suitable.
Here are some examples of the kinds of work that you should consider:
What is the suitability of the process to be automated? That’s going to depend on several criteria: current pain points and resource consumption; existing automation levels; process stability, including future changes, and frequency; the degree of process pain points; and the extent to which the process is rules-based or scripted.
For example, to determine the complexity of the process, finance should look at how many applications that process already relies on or interacts with and the type of applications (core transactional, reporting, or ancillary) and transaction type (read, write, or third-party system). By figuring out the kind of existing systems in use, we can assess criticality. The decision on what’s core and what’s ancillary will ultimately help articulate a reliable directive to move forward.
We’ve often translated these inputs into process heatmaps that consider the client’s specific inputs (see an example of a thumbnail below). For example, we see moderate to high opportunity of smart data capture and RPA application across order management activities, such as order entry, processing, customer service, and contract administration. We also see cognitive automation being used in credit management, specifically in customer segmentation and customer credit management.
Lessons from early adopters
We have seen many real-life examples of companies that have explored, experimented with, or fully deployed smart automation. What are some lessons early adopters can offer?
- Be strategic about your digital transformation: Smart automation is tricky. It’s advertised as something that can be quickly implemented, but it’s hard to get right. The key to long-term success is looking at the adoption strategically. That means first gaining a clear understanding of your business’ needs, as well as the organization’s broader operational strategy and how going digital will support it. Plus, you need to become fluent in new methods of technology implementation and tools. This will help you avoid the common mistake of setting up automation potholes – deploying (even successful) automations without much direction or strategy – which often prevents initiatives from generating real value for the organization.
- Don’t underestimate the effort to manage change: Human work is being displaced by software, AI, and bots, but is also being created to develop, support, and orchestrate the implementation of new solutions. That doesn’t mean that everyone in the company is aware of the upside. Take time to educate the organization, sell your success, and communicate the challenges and how others can get involved; invest in training to upskill resources; and be open to evolving roles and responsibilities.
- Lead with strong cross-functional partnerships: In general, smart automation is seen as a business-led initiative, but it must be closely aligned across IT and internal audit to ensure success. Technology may be the entry point to improving your overall service design, but digital transformation requires the adaptation of all aspects of the service delivery model and collaboration across the organization.
Putting together a strategic automation roadmap is essential to success, but clearly requires a lot of work. The reality is that digital transformation is here, and there’s no one right way to approach it. To get the biggest value, finance must assemble a robust team of individuals who understand these new technologies and the various process components. These individuals must be able to work together to address the organization’s shortcomings and challenges in order to better connect with – and deliver value to – the finance function’s stakeholders. Good luck!
The Hackett Group is an SAP platinum partner.
Learn more about opportunities and challenges as finance experiences a massive shift towards automation to support the intelligent enterprise in Part 1 and Part 2 of the Future-Forward Finance series.