Tinker, experiment, explore, then disrupt: The Hyper-Connected Enterprise will be driven by Intelligent Automation.

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As business operations have advanced through several inflections points over the last three decades, the core component at the heart of these changes has been the emergence of digital interactivity driving the hyper-connected global business – only made possible by intelligent automation.

Digital connectivity has transformed both front and back offices over the last three decades. The key now is to integrate and automate these activities to place the customer at the core of business operations

As you can see in our (below) “voyage to hyper-connected, interactive enterprise” we have leveraged digital connectivity to drive productivity and innovation across both the back and front offices of our organizations. Offshoring and outsourcing became a huge bi-product of digital connectivity to run business processes and apps remotely to save Western businesses huge costs through global labor and centralization of resources.

However, until recently, most of these activities have been restricted to improving efficiencies and reducing costs.  At the front end of the business, the advent of ecommerce hit its stride in the late ’90s, where customers could communicate digitally with organizations to make purchases, make genuine inquiries and get connected with others with like-minded business interests. Where automation comes into play is being able to pull together these disparate front and back office activities into one single office (aka the HFS Digital OneOffice), where customer needs are placed front and center across all business processes, where staff performance can be measured on delivering customer driven outcomes, where the entire business operations are in-tune with their customer needs… and superior to those of their competitors to stay ahead of the game.  

The urgency to be Hyper-Connected dictates why we have to drive Automation with real Intelligence

“Basic digital” capabilities (where most companies are today) make it possible for business operations to respond to their customers as those needs happen.  Emerging capabilities in data analytics tools, machine learning and cognitive computing are making it possible to anticipate changing customer needs before they happen, where shifts in global supply chains, market and competitive dynamics, economic or political changes, compliance or regularity issues, all combine to change customer behavior. 

The more intelligent your business operations, the more you can stay ahead of the game, but none of this is possible if your processes are not automated effectively to create this knowledge for your business operators:

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Once the digital baseline is created, enterprises need to create more intelligent bots to perform more sophisticated tasks than repetitive data and process loops. This means having unattended and attended interactions with data sources both inside and outside of the enterprise.  

From Experimenting to Disrupting:  Cracking the Intelligent Automation code in Four Stages

The industry is struggling to solve challenges around the process, change, talent, training, infrastructure, security, and governance. There is deafening noise and hype around Intelligent Automation, but there are very few enterprises that have cracked the code of driving transformative impact by leveraging Intelligent Automation at an industrial scale. Why?

Our research and ongoing conversations over the last six years (remember our ‘Greetings from Robotistan’ in 2012?) in the automation space has allowed us to interact, help, and follow automation initiatives at several global 2000 enterprises. And we leveraged this extensive experience to develop HFS’ Intelligent Automation Maturity Model (see exhibit below).  Our experience suggests that the organizational maturity and the resultant impact from intelligent automation typically follow four stages of evolution:

  1. The experimenter – trying out new ideas, methods, or activities. The intelligent automation journey often starts with some maverick individuals in some corner of the organization playing with different technologies. There is no real strategy at this stage, just passion. The objective is simply driven by automating a particular task that is innately boring or transactional but still time-consuming and inefficient. Different experimenters start at different places across the Trifecta. It is not necessary to start with basic automation and then advance to AI-based automation, but experimenter’s automation solutions are typically piecemeal.  
  2. The tinkerer – trying to improve something in a casual or desultory way, often to no useful effect. The early successes from experimentation often result in the most frustrating stages of the intelligent automation maturity model. The tinkerers start to copy and paste what worked in experimentation for everything else. But if all you have is a hammer, everything looks like a nail. Failures are widespread at this stage, but tinkerers who don’t give up are the ones who eventually succeed to move to the next step. This is the stage where enterprises are trying to find some method to the madness but often with limited success. The tinkering stage is exemplified by rhetoric winning over reality!
  3. The explorer – charting out new territories. As reality dawns after extensive tinkering, enterprises start to realize the different pieces of the puzzle. They start investing in organizational management (often through COEs and a hub-spoke model), recognize that they need to invest in multiple technologies across the trifecta to solve problems and start tackling end-to-end processes versus individual tasks.
  4. The disruptor – radically changing the status quo. Intelligent Automation transcends from a program and becomes an enterprise-wide movement at this stage. Disruptors can bring to bear integrated solutions that combine the power of automation, analytics, and AI. Several automations at this stage are scaled up, and there is a high degree of confidence in scaling up others. It is only at this disruptor level when the promise of intelligent automation starts to become a reality.

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The Bottom-Line:  The more hyper-connected we get, the more this is about people, purpose, and planning – and less about whichever shiny new gadget is the flavor of the month

While the industry is busily adding fancy new words to their résumés and job titles, we have to remember that our technological journey is gradual.  Change comes slowly and incrementally and you can’t just rip off the proverbial BandAid, hire a bunch of Millennials and Gen-Z kids… and it’s mission accomplished. As the Hyper-Connected journey illustrates, it took 30 years to get where we are today – and that’s because both front and back offices needed to go through major, secular changes to become efficient and digitized.

But the next phase is not a trade-secret – this “Future of Work” is merely a phased transformation of the present.  Dumb robots evolving into intelligent assistants… ineffective supply chains plagued with manual breakpoints becoming fluid, autonomous and intelligent – with the ability to interact with other supply chains.  Quantum computing and blockchain emerging to challenge the very logic of TCP/IP and computing architectures. But to get there, we need to be experimenting, tinkering, exploring and disrupting with the kit that available today to get our organizations in a place where all these far-flung innovations can have some real possibilities.  

So let’s have less talk about the future of work and focus on the present… we know where we are and what we need to do.  So let’s do it!

Posted in : OneOffice



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  1. Today we are simply experiencing disruption across all four dimensions – – the workforce, the workplace, technology, and social norms.

  2. Good article and concept. I am however a little worried that every such article portrays the past as bad. That can’t be true. I see hyper connected future as an issue. Too much connectivity is a distraction and an excuse often. It hinders deep work.

  3. People, purpose and planning… those 3 inter-related areas of knowledge from which our technical education have kept as away for the longest time! I still remember claims like – “don’t worry about programmers/analysts! They’re logical by nature, they’ll understand… HR issues will be dealt with by HR dept” – all too clearly.

    Well Phil, this excellent text of yours serves to show we missed the “people” dimension all together. Now, as PEOPLE is, clearly, the single most critical set of success factors for ANY KIND of tangible transformation, we have to scramble to obtain this knowledge. The race is on: learn how to persuade, how to build consensus, how to personalize business benefit, how to identify and tackle obsolete paradigms, how to inculcate digital reasoning in your staff, or else…

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