What we wish we knew before building 100+ automated processes

By Tylor Bunting and Jarred Grimmond

Achieving 100+ automated processes is no easy feat! Yes, automation technologies are getting better and have more functionality. However, the technology component of a large-scale Intelligent Automation program is only part of the equation and there are still plenty of other considerations.

Everything takes careful planning and execution, from the messaging to your business about what automation means, right through to figuring out how your organisation is going to actually support the day to day running of the digital workforce.

We have led the development and operations of Intelligent Automation programs at scale and want to share some key tips and pointers we have learned over time. Our aim for this article is to help others get their program to the magical 100+ automated process mark!

1. Begin with the end in mind

The saying “if you fail to prepare then you should prepare to fail” rings true in automation. A “make it up as you go” approach can lead to poorly automated processes, internal conflicts, and ultimately a loss of confidence in the technology. When starting an automation program organisations should strongly consider the following three points.

Executive sponsorship and alignment

One of the best ways to ensure the success of an automation program is to create an automation movement in your organisation. What we should be aiming for here is a pull not push mentality from process owners and their managers towards automation (i.e. The business is excited about automation and is keen to provide further opportunities).

Now, this doesn’t just happen overnight, but a fantastic way to get there is through executive alignment, as well as clear messaging and communication of the automation vision to the organisation. Because let’s face it if your leaders aren’t excited about automation then why should you be?

The hot tip to executives here is when it comes to vision — center it around a focus on enabling employees rather than replacing them, this can lead to greater benefits than cost savings.

Align business and IT

Alignment between the business and IT from the get-go is key because, in this world, automation doesn’t exist without a strong symbiotic relationship and a shared common goal between the two factions. The quicker this is achieved the quicker automations get built.

Agree early on the unified ways of working together, key checkpoints, and governance structure to enable your automation delivery team to churn out automated processes and hit triple figures.

Ensure end to end methodologies are in place covering the hire to retire of your digital workers

A common mistake we see is the segmentation of the discovery, delivery, and run phases which can foster disjointed automation when we consider the many different social styles involved in an automation team.

Really think about how you can integrate the three key phases of automation so they act as one integrated flow rather than three separate methodologies avoiding “throw over the fence” handovers in between phases (e.g. think DevOps instead of Agile + Ops).

2. Invest in your people

You may be building automations but your people are still your most important assets. Typically when you implement Intelligent Automation programs you are not looking to actually remove the human in the loop (note that this often leads to failed programs) but instead implement automations that work with and augment your human capability.

As previously mentioned, aligning with key business stakeholders is critical for this new relationship to result in productive outputs. However, special training and attention needs to be provided to those responsible for developing / teaching the automations. When thinking about the investments required for your development teams consider the following.

Create and enforce development standards

To the engineers and computer programmers reading this you might be thinking that this consideration is obvious. However, Intelligent Automation programs are often business-led (and so they should be) and the benefits of proper standardisation may not be known.

For those that are not aware of the benefits that can be obtained from proper development standards let us describe a few. Development standards result in the following:

  • Minimised technical debt because standards include lessons learned from previous experiences / development projects.
  • Reduced handover times because all developers follow similar patterns and can more easily understand the code that others in the team have built.
  • Increased support / process ratio (e.g 1 automation controller per 100 automations) because support staff intuitively understand how processes work based on their experiences working with other processes that follow the same development standards.
  • Increased speed of development because a core principle of coding standards is reusability, which prevents developers from having to start from scratch when building new automations (i.e. teaching automations to do basic things like “login to SAP” should only be done once and reused across all processes that use SAP).

Invest in base training early on

The key message behind this consideration is that you should apply the 80/20 rule when it comes to training your development team.

Okay, firstly what’s the 80/20 rule? This is essentially a universal productivity principle that says “80% of your outputs typically come from 20% of inputs”. Now if we try to frame that same definition from the context of training a development team — “80% of the processes you develop will only require 20% of the development training that’s available”.

The money question is “what’s the 20% of training development teams should focus on?” Fortunately, the answer is quite simple:

  1. Make sure developers complete base level certifications (e.g. BluePrism Accredited Developer OR RPA Developer Advanced Certification for UiPath).
  2. Make sure new developers complete training related to the development standards the rest of the team follows. Doing this allows the previously mentioned benefits to be realised.

3. Use your automations as the foundation for revolutionary innovation

Automation is a catalyst that can help organisations form a better view of their processes and get a grasp on AI technologies. When steaming towards 100+ automated processes, things like real-time dashboard monitoring, and increasing the ease of building automations through AI becomes an ever more important part of your journey.

Make the most of automation telemetry

You might be asking yourself “what is automation telemetry and how can I make the most of it?” Let’s break it down.

An “automation” within the content of this article is a “digital worker that has been trained to interact with a computers’ Graphical User Interfaces to perform a specific business process just like a human would”. It’s worth noting that the automations leave a digital trail of exact actions taken when performing specified business processes.

Telemetry is defined as “the process of recording and transmitting the readings of an instrument”. If you merge these two definitions, you can see how “automations” have the potential to be used as “instruments” that generate data on business processes. This data can then be recorded and transmitted for further analysis. Can you see the value of automation telemetry?

The point we are trying to make is that you should (1) design your automations so they leave useful (and secure) digital trails, (2) analyze the trends that those digital trails leave, and (3) identify better ways of working from data-backed insights! Just imagine all of the data you could play with if you had 100+ automations running in production, all leaving digital trails!

Automation is just the foundation

Automation platforms are a great catalyst for the introduction of AI into an organisation. Think about it this way — automation platforms are the arms and legs that move things (data, documents, email, etc) from point A to point B, and AI is the brain that can make inferential decisions and enable those arms and legs to perform more meaningful and difficult tasks.

What this means is that with the introduction of AI greater value can be unlocked faster. Three years ago it would take months to build out rulesets to complex decisions with limited success, now AI solutions can be built in a day and easily integrated by using automation tools.

A lot of organisations still see AI as something that is still coming, well we can tell you now that it is here and it is here to stay. Don’t be afraid or standoffish to begin experimenting and implementing AI with your automations early in your program if you or your Intelligent Automation partner has the capability! We have seen new AI technologies unlock tremendous value and the earlier you do it, the more value you will realise over time.

AI is real and more accessible than ever! However, a word of caution is to be careful about how you use certain AI platforms with respect to personal data. There can be legal restrictions on the sharing and storing of sensitive data. Luckily, this merely restricts you to “on-premise” AI as opposed to “cloud” AI.

Conclusion

Now with all this said, we aren’t going to beat around the bush here. The tips and pointers we have covered in this article aren’t the silver bullet to nailing an Intelligent Automation program at scale! However, these considerations, if given thought and the proper attention, will make you and your teams lives easier on the journey to 100+ automated processes. Trust us, we have made the mistakes so you don’t have to!

Please note that this article reflects our personal views only and not necessarily the views of our respective employers

Automation | Analytics | Cloud | DevOps