Anna Frazzetto
Contributing writer

4 ways to mature your digital automation strategy

Jan 27, 2022
Artificial IntelligenceData ScienceNatural Language Processing

When it comes to realizing the benefits of digital automation, maturity matters. Here's what CIOs need to know to assess and advance their automation efforts.

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It is now a given that companies need to automate offerings and operations to optimize existing processes and generate better experiences and value for customers. But businesses do not gain maximum value and efficiency simply by adding automation. Your level of maturity is what matters.

Knowing your maturity level will help you identify opportunities for automation growth as well as evaluate the risks and challenges that come with bigger, more sophisticated automations. For example, as automation solutions cross departments and integrate disparate technologies, data loss and integrity risks can increase.

Assessing your automation maturity level

In most automation maturity models, there are three distinct stages:

  • Task-oriented stage:  In this early phase, simple manual processes are automated and typically generate significant efficiencies at the individual level. These automations are usually created using robotic process automation (RPA) bots.
  • Team/department-oriented phase:  In this stage of the maturing process, automations extend beyond the individual, connecting teams or departments within a function-focused app such as Salesforce, ServiceNow or a business process automation platform. These systems have built-in capabilities to create workflows that automatically route tasks to various team members when an event happens, such as a sales lead turning into a solid opportunity.
  • End-to-end phase: Once organizations reach this most mature level of automation, they are building end-to-end processes that extend across multiple departments or the entire enterprise. A process that registers an order in one system, checks inventory in another system, and finally triggers a shipping process in a third is a common example. Enterprise automation platforms focused on integration enable this level of automation.

Increasing the maturity of your automation solutions

Once your team understands its current state, it’s time to take steps to advance the automation strategy. Here are four tactics to focus on:

1. Connect applications and process

Immature strategies focus on simple tasks. It’s a great place to start, but to get the most out of automation, it needs to grow. To evolve these task-based automations into automated workflows, applications and systems need to communicate with each other. Steadily adding connected systems provides the opportunity to build increasingly complex, end-to-end workflows.

As more processes are connected, you will need a platform to manage the increasing complexity. Fortunately, vendors in different segments of enterprise IT are converging with offerings of business process automation (BPA) suites that include integration libraries and automation and workflow capabilities. This trend provides support for organizations building out their strategies and validates the importance of automation paired with connectivity.

2. Use RPA sparingly

RPA bots are very popular because they are powerful and easy to use. This is both a blessing and a curse because RPA is often used when it shouldn’t be, leading to poorly designed processes.

Designed to mimic human behavior navigating an application’s UI, RPA is very brittle and cannot scale across an organization. When the UI of an app changes, the RPA can break. If there are multiple RPA bots dependent on each other, a single target UI change can cause the entire process to stop.  Pinpointing the RPA breakdown point to make the fix is also difficult, which is contrary to the goals of automation to simplify workloads.

3. Use more AI   

AI can be very helpful in incorporating less organized information into the automation process. For example, AI can recognize characters on a paper document using optical character recognition (OCR) or understand the meaning of a document using natural language process (NLP) and convert unorganized information into digital forms that can be automatically processed by computers.

With access to more data and more data science tools, predictive models can also be more readily integrated into unsupervised automated processes for simple decision making. This more sophisticated implementation of AI can free up more expensive human resources to focus on higher-value tasks.

4. Build symbiotic relationships between humans and computers

As automation strategies get increasingly sophisticated, humans are less involved and may no longer be at the center of the process. This doesn’t mean that people are no longer needed. It still takes humans to ensure sophisticated automations don’t get out of hand with edge cases that challenge established operating patterns, making them too complex or nuanced for a machine to handle.

Enabling people to engage with machines efficiently is a key component of a very mature system. The most sophisticated automation strategies will allow people to manage edge cases without having to leave the environment or application they are currently working in.

Automation strategies will constantly evolve and get more sophisticated. The secret to automation success is to balance processes that enable machines and employees to effectively work together to achieve business objectives.

Anna Frazzetto
Contributing writer

Anna Frazzetto is Chief Digital Technology Officer for Tential.