Blog: Reducing the burden of repetitive tasks within a project environment.

Published by Clare Patterson on

The June London meetup focused on how we can use automation to help to remove the burden of repetitive processes.  

First up was Dean Murphy from UI Path who provided a useful overview of what robotic process is all about and how it can be used. In essence, it is a capability that replicates what a human operator would do by utilising computer vision and processes that are similar to macros. Humans are then able to focus on decisions, exceptions and providing oversight. By using a machine to undertake this work we remove the risk errors associated with manual entry.  

Although AI Path offers one solution, there are others. Some organisations may want to start by utilising some of the capabilities within Microsoft Office such as Microsoft Flow and Power Apps. These provide solutions to automate simple workflows and also provide a more user friendly solution for data capture. But the complexity rapidly begins to escalate when the automation spans different software products, which is when RPA comes into its own.  

James Smith, the CTO at Projecting Success, then provided an overview of the background to the challenge. In summary, in April 2019 James volunteered to address a number of user cases on behalf of the community, to provide an opportunity for everyone to understand the art of the possible. Using real data and real challenges he provided 5 separate use cases: 

  1. Timesheets. He demonstrated a use case using UI Path to extract information from timesheets, check it against tolerance parameters, sum it and then submit it to payroll. This simple use case offered the potential to save ~40 hours per year.
  2. BIM Models. Ashley, from Kier explained a use case associated with the collation and distribution of BIM model data. This process is currently very labour intensive and takes around 150 hours per year, per project. By utilising RPA James was able to demonstrate that RPA could be used to automate the entire 71 step process, end to end. This included extracting two factor authentication codes from emails and pasting them into other applications.  
  3. Data extraction and amalgamation. James then demonstrated a use case associated with web scraping data on over 5,000 records. By using R, Python and ‘Beautiful Soup’ he was able to fully automate this process. By utilising domain knowledge he was also able to get around some of the website protections which hinder bot based web scraping. 
  4. Processing delivery notes. Anne-Marie from Osborne provided an overview of the process that they used for managing delivery notes and reconciling them with invoices. The entire process costs approximately £80,000 per year. James provided a demonstration of how he utilised PowerApps and Python to extract the text from email based orders and present this within an app. Osborne are then able to utilise the app to book in goods directly at the gate relieving them of the burden of data input. There is also an opportunity to fully automate the process by matching the delivery with the invoice and flagging any exceptions.  
  5. Balfour Beatty provided a summary of an additional use case, which will be presented within a future meetup.  

          In summary, James was able to demonstrate that automation could be used to remove the burden of repetitive processes, often in their entirety. The key observations that he took from this work were: 

          1. Do not just automate an existing process. Ensure that you have a good grasp of the use case because there may be a more efficient solution for solving it.  
          2. Think beyond the immediate use case. Automation has the potential to create a rich pool of data that can be used for future AI based applications, some of which will be predictive.  
          3. Assess the organisation’s capacity for change. What legacy IT constraints do they have? How will they install some of the robots?  
          4. Consider a blend of applications from Powerapps through to RPA software. There is no ‘one size fits all’.  
          5. Some of the applications are fairly intuitive to use and it should be possible to self serve some of the easier use cases. But as complexity increases there is a need to include logic through capabilities such as Python. Third parties can leverage their existing code which may shorten the overall development time.  

                  In summary, it’s a great starting point for a journey into advanced project data analytics and offers the potential to free up capacity for other higher value activities. It also improves accuracy and data consistency; an essential stepping stone towards an AI future.    

                  The video is available via this link. 

                  The slides can be found here RPA – Meetup 

                  Martin Paver is CEO/Founder of Projecting Success. In Dec 2017 he saw the opportunity to transform how projects could be delivered through the application of advanced data analytics and founded the London Project Data Analytics meetup, which has expanded throughout the UK and has grown to a community of ~3000 people. He delivers strategic and tactical solutions that integrate project management and leading edge data science and analytics.

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