Managing the Pipeline

Process Inventory Management

Process Inventory Management can be viewed as putting in place the infrastructure that enables effective programme or portfolio management of the opportunities for automation. It is also the platform from which reporting can be done, to ensure that the value of your automation programme is communicated to your business.

CREATING A UNIQUE ID: Define an ID structure that is applicable across your organisation and through the funnel, and that means something to the informed.

TRACKING SYSTEM REQUIREMENTS: Naturally, you need to store this data somewhere and so, require some sort of a system. The key requirements for a tracking system are: Easy to manage, accessible to key users and change controlled.

The system could be an Excel spreadsheet or an automated workflow. Provided the below are satisfied, tracking should be possible.

ATTACHING DATA TO GENERATE INSIGHT: To ensure that the necessary data is captured to generate insight. Define key data to be captured at each stage of the automation lifecycle. Ensure progress or status measures can only be selected from a pre-defined list, e.g. the status of an assessed process may be: Pending, Accepted, Rejected.

Key metrics may include:

  • Conversion rate of processes to automation (at each stage of Process Discovery)
  • Effectiveness of methodology (for continuous improvement)
  • Benefit opportunity forecast versus actual
  • Accuracy in forecasting
  • Average benefit realized per process (to enable programme level forecasting)
  • Breakdown of processes across regions and functions
  • Heat map of automation across the organisation
  • Prioritization of next stages of expansion into new areas of the organisation.

Key Steps for Managing a Demand Pipeline

There are 4 steps to managing a demand pipeline:

1. Prioritization 

  • Review Automation requests
  • Analyze Automation request and review process mined data, if required
  • Perform Business case modelling
  • Prioritize requests received from the broader business areas
  • Track Process Backlog.

2. Impact Assessment 

  • Follow a structured impact assessment process that evaluates benefits, delivery and ongoing support costs (specifying ownership as required). Ensure alignment to strategic business drivers and the impact of not making the change
  • Risk Assessment
  • Is the AS IS process risky? Is the delivery timeline a risk? Is the delivery team experience level a risk? Does unavailability of test data/apps present a risk (e.g., prolonged hyper-care period)? 
  • What are the risks of exceptions from the TO BE process automation? What is the risk to the Business if the TO BE process automation goes down during BAU? 
  • Process to reflect existing organisational approach for managing change.

3. Governance Board Approval 

  • Enables key stakeholders to review all proposed automations and assess the projected value in terms of strategic business drivers
  • Chaired by Head of Robotic Process Automation, and attended by business, IT and change reps.

4. Scheduling 

  • Build and manage the RPA change schedule – balancing maximisation of business benefit, delivery resource availability, and reuse of existing processes and objects
  • Head of RPA is responsible for scheduling and managing stakeholder expectations across the business and IT community. 

Checklist

  • Is there a built and managed RPA change schedule?  
  • Does prioritization for requests received from broader business or IT externally managed?  
  • Is the Head of Robotic Automation responsible for scheduling and managing stakeholder expectations?  
  • Does the pipeline cater for Change Requests and are managed and prioritized accordingly?  
  • Is the pipeline constantly reviewed and updated?  
  • Is the pipeline made readily available to people in the organization for viewing the scheduled automations
The Blue Prism Process Discovery Tool

The Process Discovery Tool enables your RPA team to discover the processes most suitable for automation, with the greatest potential benefit, applying a proven methodology. It provides a means of scaling up process discovery, managing process inventory, tracking realized benefits, and maximizing return-on-effort.