We've all been involved in automated processes in companies, governments, or schools that might have made sense in theory—but fell apart when they were rolled out. That’s because automating a process is different from automating a process well. Developing a process automation strategy helps you automate effectively—but only if it includes these three often-overlooked elements:
- Aligning technology and data.
- Operationalizing AI capabilities.
- Planning big.
Now let’s talk about why they’re so necessary to automation success.
If you want to learn more process automation basics, such as what it is, how it works, how to implement it, and benefits, check out our process automation overview page.
1. Aligning technology and data.
Your organization may already have countless automation technologies. But if they don’t work well together, they’ll cause more problems than they solve. You may have already seen the signs and symptoms of a disjointed automation journey at your organization:
- High maintenance costs and upgrade complexity.
- A lack of skilled resources for managing various automation vendors and tools.
- Complex integration needs between technologies.
- Overlapping tools and misaligned governance.
In addition, if the supporting data used in your automations is unreliable, you’ll deliver automations that hinder rather than help business leaders make data-driven decisions as they serve customers.
To avoid this process automation pitfall, you need a convergence of process automation technology and well-governed data. This way, the technologies will not only work well together, they’ll also align with customer expectations—both internally and externally.
Hear Jim Reis, Vice President of Technology at Capital Group, explain how he’s built up a value engine using process automation to quickly address a long list of business priorities.
What are some methods to ensure both streamlined automation and reliable data?
Convergence of automation technologies.
A surefire way to ensure that your process automation technologies will work together is to build your strategy on an enterprise-grade platform. In fact, even vendors in markets selling individual automation capabilities like robotic process automation (RPA) are moving toward broader automation plays (see trends in RPA).
With a comprehensive platform, your team can choose the best-fit technology for the job every time, because they have a complete catalog of technologies to choose from. But not all platforms are built alike. A process automation platform should enable you to orchestrate your digital workers, whether you’re using AI, API integrations, RPA, or decision rules, within and between processes. It should also provide a semantic layer atop your data so that data is available and accessible by your automation technology (and human employees). It should also enable you to mine insights so that you can continuously improve processes.
Get more tips in our guide to end-to-end process automation.
Well-governed data.
Why is data so crucial to a process automation strategy? Your data’s accuracy and availability determines whether your processes will deliver the best outputs. For strong processes, make data models available throughout the automation processes, ensuring they have:
- Well-defined structures and interactions.
- Properly enforced authorization.
A data fabric—a better alternative to data warehouses, lakes, and meshes—can meet these two requirements. It supplies a semantic layer over your data so the data can be accessed in one central location. This provides a strong foundation for your process automation platform, not only because it makes data accessible, but also because it provides security controls down to the row level. Only users assigned to see that data in the process flow can view or edit it.
So now that you’ve thought through the platform and the data, consider this important aspect of your process automation strategy: where does AI fit in?
2. Operationalizing AI capabilities.
Artificial intelligence needs to be part of any 2024 process automation strategy. It’s not enough to say you’ll use AI for business. Unless you have a plan for operationalizing AI capabilities so they work in real-world use cases and deliver actionable outcomes, you’ll be at risk of falling behind. Consider these aspects for your process automation strategy:
How will you define suitable AI use cases?
How will you identify, train, and optimize the target model?
How will you provision the required resources to apply the technology?
Thinking through these questions gives you a headstart on adopting AI’s ever-expanding capabilities.
Fortunately, many business process automation vendors are experimenting with AI technologies. Gartner® makes this strategic planning assumption in the 2023 Market Guide for Business Automation Tools:
By 2025, 60% of business process automation (BPA) vendors will offer generative-AI-driven process modeling to reduce process development times.1
New capabilities like AI-powered content processing and instant PDF-to-form generation will enable faster adoption into your process automation strategy (and create quicker results for end-users).
Want more guidance about the future of AI and how to implement it? We spoke with 8 experts for the 2024 AI Outlook.
3. Planning big.
Organizations can fall into the trap of planning too small for their automation efforts. While it’s helpful to start with a specific use case in mind, you want to think past the first deployment. This protects you from limiting yourself with a platform that can’t do enough or scale to meet future needs and from creating islands of automation by applying small solutions to big problems.
For example, if you have one piece of a process that requires automated document processing, but that process is much bigger than that one piece (and the whole thing needs to be optimized), you’ll want to understand that so you can apply the right-sized solution. Investing time and money into a solution that can’t scale will hinder your business process automation initiative.
And even if you do start small, you should still think big technology-wise: ultimately, you’ll need to scale and grow your automation program, and you’ll require capabilities to support you both in your immediate success and future growth.
It was important that we partner with a platform that can be scaled up, and that we can not only use it for the corporate credit process, but also across the banking group for as many processes as we can possibly think of. – Csongor Nemeth, Chief Corporate Business Officer, Addiko Bank
Make sure your automation strategy is complete.
If you want to develop a process automation strategy that will work for your company, keep these three guiding principles in mind:
- Take a platform approach to automation so that you can ensure the convergence of process automation technologies and data.
- Operationalize AI capabilities so you can apply them to real-world use cases.
- Plan bigger than your first use case so you can support future automation growth.
Get guidance on business process automation vendors in the Gartner Market Guide to Business Process Automation Tools.
1 Gartner, Market Guide for Business Process Automation Tools 23 October 2023, Tim Faith Et Al.
