When it comes to taking advantage of the advantages of digital automation, it all depends on the degree of maturity. Here’s what CIOs need to know to evaluate and drive their automation efforts. […]
It is now a matter of course that companies automate their offers and processes in order to optimize existing processes and create better experiences and values for customers. But companies do not simply achieve maximum value and efficiency through additional automation. Your level of maturity is crucial.
Knowing your maturity level will help you identify opportunities for automation expansion and assess the risks and challenges associated with larger, more sophisticated automations. For example, if automation solutions are cross-departmental and integrate different technologies, the risks of data loss and integrity may increase.
Assessment of the degree of maturity of your automation
There are three different levels in most automation maturity models:
- Task-oriented stage: In this early phase, simple manual processes are automated, which usually bring significant efficiency gains at the individual level. These automations are usually created with Robotic Process Automation (RPA) bots.
- Team-/departmental-oriented phase: In this phase of the maturation process, the automations go beyond the individual and connect teams or departments within a function-oriented app such as Salesforce, ServiceNow or a platform for automating business processes. These systems have built-in workflow creation capabilities that automatically route tasks to different team members when an event occurs, such as when a sales lead becomes a solid sales opportunity.
- End-to-end phase: Once companies have reached this most mature level of automation, they create end-to-end processes that span multiple departments or the entire company. A process that registers an order in one system, checks the stock in another system, and finally triggers a shipping process in a third system is a common example. Enterprise automation platforms focused on integration enable this level of automation.
Increase the maturity of your automation solutions
As soon as your team knows the current state of affairs, it’s time to advance the automation strategy. Here are four tactics you should focus on:
1. Connect applications and processes
Immature strategies focus on simple tasks. This is a good start, but to get the most out of automation, it needs to grow. In order to further develop these task-based automations into automated workflows, applications and systems must communicate with each other. The constant expansion of the connected systems offers the possibility to create increasingly complex, consistent workflows.
As more and more processes are connected, they need a platform to cope with the increasing complexity. Fortunately, vendors in various segments of enterprise IT are converging with their business process automation (BPA) offerings, which include integration libraries and automation and workflow capabilities. This trend supports companies in developing their strategies and confirms the importance of automation in connection 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 where it should not be, which leads to poorly designed processes.
RPA is designed to mimic human behavior when navigating through the user interface of an application, but it is very vulnerable and cannot be scaled across an entire enterprise. If the user interface of an application changes, the RPA may fail. When multiple RPA bots are interdependent, a single target UI change can bring the entire process to a standstill. It is also difficult to locate the RPA failure point to make the correction, which is contrary to the goal of automation to simplify workloads.
3. Use more AI
AI can be very helpful when it comes to integrating 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 processing (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 easily integrated into unsupervised automated processes for easy decision-making. This more sophisticated implementation of AI can free up expensive human resources to focus on higher-value tasks.
4. Building symbiotic relationships between humans and computers
As automation strategies become more and more sophisticated, people are less and less involved and are no longer at the center of the process. However, this does not mean that man is no longer needed. It still takes people to ensure that sophisticated automations do not get out of hand, as they challenge established operating patterns and are therefore too complex or too differentiated for a machine to be able to handle them.
A key component of a mature system is to give people the opportunity to work efficiently with machines. The most sophisticated automation strategies will allow people to manage edge cases without having to leave the environment or application in which they are currently working.
Automation strategies will constantly evolve and become more and more sophisticated. The secret of automation success lies in the balance of processes that allow machines and employees to work together effectively to achieve business goals.
*Anna Frazzetto is Chief Digital Technology Officer at Tential.