03 May 2022

Increasing productivity with workflow automation

Productivity
Increasing productivity with workflow automation

Workflow automation is no news in many industries, but what about project management?

Ronald Tong discusses whether it’s possible to automate our work for better productivity.

Project managers are constantly bogged down by repetitive administrative tasks. While these activities are necessary to lead to management decisions, in current practice considerable amount of time is spent in the manual process, obstructing project managers from utilising outcome of these activities.


What is project management automation?

In the old days, we used to do manual copy and hand calculations. These are now replaced by electronic documents and spreadsheets. When we look back to ourselves in the future, the way we work today will again be replaced by another wave of automation. For the context of this article, automation means eliminating repetitive administrative tasks that requires little professional judgement. Typical examples like files processing, manual read up or internet browsing.


Why automation attracts little attention in project management

Unlike engineering disciplines, project management puts much more emphasis on soft skills, or behavioural skills. Works cannot simply be carried out behind a computer, and management styles vary across individuals. Works cannot be easily standardised and there is no one-size-fit-all management approach. As a result, relying on technology is usually not the first resort to solve problems.
 

It is a common misperception that resolutions by technology require a complete shift of profession into IT.



If we look back to the days when we first started using computers in our daily work, we may have thought the same thing, but we know now that it doesn’t mean we all have to be software engineers. It takes time to demonstrate how to work differently from ‘current best practice’ as technology continues to evolve.


How to automate project management

Since discovering the computer programming language Python, it has changed the way I work. I don’t have any affiliation with it; I simply recommend it because it has a low entry barrier, solves many issues, and is free. Yes, writing scripts with Python is a new skill to learn, but I believe it’s very much worth it, and it should be on your list for 2022 if it isn’t already.
 

Python

There is a vast spectrum of libraries created by the Python community that virtually covers any repetitive administrative tasks performed on a computer. Although individual tasks may differ, below are some examples that illustrate how automation can be achieved in project management through Python.


Example 1: Document lookup

Proper document control means files are stored in a clear hierarchy of folders. However, it is not easy to search for content of a certain document that contains multiple pages and is hidden within layers of folders, or if the text desired is in the form of scanned copies or photos that is not searchable by conventional methods.
 

Utilising Python’s text recognition library, directories and documents can be opened, scanned, and search results returned all in a matter of seconds.



Example 2: Browser scraping

Project managers often need to harvest information from fixed sources of folders, servers, or the internet. The repeated steps of acquiring documents, with the same mouse clicks and keyboard strokes, are time consuming and add no value to the management process. By building the retrieval workflow once, details can be automatically returned from any locations at any intervals, allowing project managers focus on using the information for next-step decisions.


Example 3: Document control

As part of document control such as drawings vetting, invoice processing or Primavera update, files need to be downloaded, read and details logged. The manual approach is time consuming and requires little professional judgement, let alone it is prone to human errors. By mapping the source and destination, Python can repeat and automate the data update process. Benchmarks can even be built in to highlight items that require project management intervention.


Example 4: File manipulation

It is not uncommon to see monthly project reports start off with well-thought commentaries and fancy graphics, that gradually deteriorate to just another check-box exercise due to the time consumed to update the report itself, and content of the report is not used to make informed decisions. By designing an update routine on the quantitative part of the report, project managers can focus on qualitative aspects such as prioritising areas that need attention.


Example 5: Enhance performance of incumbent tools

Data visualisation is a powerful tool for storytelling, especially in large-scale projects. However, using conventional software like Excel, Power BI or Tableau to build up visualisations from large amount of data is slow, mainly due to their heavy computational user interface. In comparison, light-weight Python can carry out data processing much faster, and combining it with incumbent project management tools, benefits can be achieved from both worlds of high-speed data manipulation and sophisticated visualisation options.


Where will project management automation take us?

What we have seen so far is the automation of tasks that are standardised and modular in nature. Python tools need to be adjusted if there are abnormalities not built into the automation workflow. Moreover, today’s technology is still not mature enough to make experienced-based professional judgements. Nonetheless, we already see promising trends under development.

In the future, professional writings can be automatically generated based on circumstances and individuals’ writing style:

  • Project managers only need to cast a final review before sending off correspondences, e.g., conversations generated by chatbots will become more intellectually advanced based on project information available.

  • Instead of spending hours combing through lengthy documents, basic reading comprehension such as summarisation, information extraction can be automated, reserving time to make management decisions, e.g., natural language processing is catching up on human performance as seen in the XTREME linguistic benchmarks.

  • Site walks and progress checks can be carried out by robotics, capturing images and identifying areas that requires further attention, e.g., visually impaired are able to ‘see’ with the aid of smart glasses translating images to text.

All these achievements do not mean project managers will lose their jobs or require total shift in their professional focus. Instead, artificial intelligence (with a backbone algorithm written in Python) will augment project managers in our works, and new roles will emerge who translate technology into domain-specific needs, in this case project management. As access barrier to automation continues to lower, embracing new ways of working in project management will allow us to rethink how the ‘best practice’ of future will look like.

Author: Ronald Tong is a Principal Project Manager with Mott MacDonald Group. He has 15 years’ experience in the building industry across transport, healthcare, and industrial sectors. He is a chartered engineer and delivers Coding Club in Mott MacDonald, advocating project delivery with automation, computational design and coding.


This article appears in the Autumn 2022 edition of Paradigm Shift magazine. Find out more about the AIPM digital magazine and take a look at the full edition.