Adopting automation: Is your organisation ready?

As working from home has become the norm, many organisations have sought to make critical business processes more scalable and resilient through automation.

In a recent article, Gartner predicts that “90% of large organizations globally will have adopted RPA in some form by 2022.” But why the rapid, widespread uptake and what are the benefits that Robotic Process Automation (RPA) offers?

RPA can help organisations:

  • Minimise the risk of error in transactions for better quality control and compliance
  • Reduce manual effort and time spent working on simple and frequent rule-based tasks
  • Improve task turnaround times
  • Achieve near real-time responses for information or task requests.

Manual activities that can typically be replaced by RPA bots are:

  • Filing - creating, copying, pasting, moving files and folders
  • Opening emails and copying attachments
  • Copying and pasting structured data from documents or databases
  • Making rule-based calculations and storing them in an enterprise application
  • Mimicking human users to follow and complete if/else decisions in business processes (for example, expense approvals)
  • Filling forms and scraping data from the web.

In order to enable rapid adoption of RPA and to reap the maximum benefits of this cutting edge technology, however, business leaders must pay special attention to the governance of information in their organisations.

Data governance plays a key role in identifying and assessing processes that are candidates for successful automation – i.e. those that offer a potentially high return on investment (ROI) after the RPA process is implemented. The more mature an organisation’s governance processes are, the higher the chances of successful business outcomes from RPA.

Before embarking on the RPA process, leaders should ask the following questions to assess the state of their data governance processes:

  1. Who are the data custodians and owners of business processes and systems in our organisation?
    RPA bots need to be configured to read from and write to files, documents and systems in order to mimic the steps a human follows to complete a business process. Data owners and custodians in well governed environments would usually be the best resource to confirm the currency, accuracy, sensitivity, and definitions along with storage and transport mechanisms of data sources to be utilised by automated processes.
  2. Is our data quality reliable enough to produce consistent and useful outcomes if utilised for RPA?
    Like any other system, RPA follows the principle of ‘garbage in-garbage out’. Better practice suggests conducting a data profiling exercise to understand the quality of data used by a process prior to considering whether to automate it. RPA thrives in environments that promote superior data quality leading to consistent outcomes
  3. Is the data for our business processes saved and accessed from a system in a structured format?
    Automation of business processes via RPA is most feasible if information is retrieved, utilised and stored in a structured format. This may be in the form of relational database tables, excel tables and infrequently changing web systems.
  4. Are our organisation’s data assets classified to group sources by sensitivity of the information they hold?
    RPA is well suited to automating processes retrieving, utilising and/or storing highly sensitive information, where minimal human interaction is desired. This utility is particularly useful in industries where personal information is stored and used for business processes and/or where confidentiality control mechanisms are imperative such as Defence, Health and Government.
  5. Is our data security strategy and operational model conducive to supporting RPA?
    Data security operational models in organisations outline and uphold the confidentiality, integrity and availability of data sources that are required to complete a multitude of tasks in business processes. As a result, RPA processes are directly affected by constraints set out in these operational models which may either catalyse or hinder the effectiveness of automated processes.
  6. Is our data architecture contemporary, scalable, flexible and robust enough to support RPA?
    An organisation’s data architecture defines how their information technology function supports their data requirements, including capturing, storing, querying and securing information assets. Modern data architecture works hand in hand with RPA processes as it allows for easier ways of retrieving and storing structured information via highly available and reliable APIs.
  7. Is our strategy for digitally capturing, storing, retaining and utilising paper-based information favourable to supporting RPA?
    Most popular RPA tools on the market have optical character recognition (OCR) capability, which enables reading and interpretation of digitally scanned paper data. A contemporary document and content management strategy that promotes digital capture of paper-based information will significantly increase utility of RPA.

To discuss assessing your data governance or readiness for automation, get in touch with one of our team.