Seven Principles For Intelligent Automation Success

Everyone is talking about Intelligent Automation. It’s the current hot trend – the new Digital Transformation. Your business should either be planning it or have a project inflight right now.

Intelligent automation is the combination of emerging technologies such as artificial intelligence (AI), machine learning, process automation, blockchain and IoT to solve a business problem. Solutions might comprise a single component or multiple components can be combined to solve a problem. Just think of it as your toolbox.

I’ve been fortunate to spend much of my career at the sharp end of intelligent automation (before it became mainstream), working across industries, using different technologies and platforms, with project teams ranging from 5 to 1,000. Despite this variation, there has been commonalities that have influenced my seven principles of intelligent automation success. Here’s what I keep front of mind when shaping a project:

1) Don’t automate a broken process

It’s obvious but I’ve seen it several times. With technology so accessible and easy to adopt, you can jump into the solution before really asking what problem you’re trying to solve. You might not need more technology to solve that problem!

2) Go from idea to live within 6 months

Cut your scope so that you can go live within 6 months There will be subsequent releases after that. You’ll learn more and get more value out of a solution in production than lots of use cases and design specs on SharePoint.

3) Don’t get too hooked up on delivery methodology

Waterfall, Agile, Wagile, they all work and have pros and cons. You and your team can make any model work. Pick a delivery model, make sure the team understands and are bought in, then crack on!

4) Jump into it…yes…BUT

You still need some solution hygiene (we’re all now so good at washing our hands). If you dive in and just start building the probability that you’ll hit a roadblock later on is pretty high. Scope, solution architecture, data model & security model…these are all artifacts that need to be in place.

5) Clear operating model when working with suppliers

Working with a supplier to support or accelerate your project is great! But remember that it’s your project so make sure it’s a proactive decision of how you want to run things when in BAU. What knowledge do you want to grow and keep in-house? You’ll always want someone in the business to play a Functional Product Owner and a Technical Product Owner at a minimum.

6) To PoC or not to PoC

Proof of concepts are wonderful things. They can get stakeholders to buy into a solution, evaluate tech options, etc. However, they can take a few weeks from your project schedule and eat some of your budget. Be unambiguous with what you’re trying to prove, it needs a mini scope too if you want to get the most out of it.

7) The best, hardest, most valuable…Data

I’ve saved the best to last! We all know the value of data and how hard it is to manage. It’s even harder if you’ve gone live without asking these questions:

  • What’s mastered where?
  • What’s stored where?
  • How is it stored?
  • What is the retention policy?
  • How do I / can I delete data?
  • Do I need to replicate the data elsewhere?
  • Do I need to keep data in sync with other systems?

I’m not asking for a normalized data model or an entity diagram (that can be completed during sprints). I am asking for some small upfront investment of time to cover the basics.

Intelligent automation can solve a multitude of business challenges to help companies scale at speed or evolve into the new world of the distributed workforce.

Need to connect to or extract data from a legacy system that doesn’t have interfaces?

Not a problem, use RPA.

Need to extract data from documents?

Use intelligent document processing and you won’t need to write a line of code.

Need to drive business processes in a particular way and connect to internal & external APIs?

Use a low code platform to build an enterprise solution in weeks with a handful of developers. No need for the big dev team and months to wait.

Whether you look at it from a pure tech or business outcome perspective – intelligent automation is exciting. Thinking and evaluating for another 12 months is not an option if you’re looking to control your own destiny…

Deepak Chandarana – Managing Director

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