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Business processes can get complex quick and become a black box with a mind of their own. While...
Hyperautomation
Hyperautomation from RelayiQ reveals AI as a fast and affordable game-changer.
Whether under the umbrella of AI, ML, BI, or process mining, companies spend more than $50 billion a year on their AI and automation solutions. Why is it that no one you know is likely using AI to solve their daily business problems, let alone doing it quickly or cost-effectively? The answer lies in a fundamental approach – more specifically a capability, to take a fundamentally different approach.
Hyperautomation promises that all processes that can be automated will be. So the question becomes, how do you get there from here? The answer is from the bottom up.
The better way to operationalize AI-driven automation is from the bottom up. For hyperautomation solutions to work, companies must abandon the top-down approach to AI solutions that have failed them in the past and adopt the bottom-up approach RelayiQ has championed from the start.
When building the RelayiQ platform, we assumed that everyone’s problems would be different and require a customized solution. However, we also considered the potential for significant overlap in data sources, core requirements for algorithms, and the need for an enterprise-grade application that almost every organization could use and manage on its own.
RelayiQ has built an affordable and approachable hyperautomation solution for business consumers. Our bottom-up marketplace approach is proving highly effective. Once adopted, it expands across multiple use cases, and it spreads throughout organizations. From reducing employee theft to maximizing quality inventory production, the RelayiQ hyperautomation platform has unlimited potential.
Hyperautomation is destined to be a foundational element in the modern, fast-growing enterprise.
Hearing the term automation, RPA, or Robotic Process automation is what immediately comes to mind. But hyperautomation is quite different. Hyperautomation combines tools and technologies in a highly advanced way that leads to new ways of working and optimizing operations. In theory, you’re able to automatically produce the output even for the low-value repetitive tasks by using automation tools and advanced AI platforms. With minimal human dependency, hyperautomation creates an agile environment and allows you to make data-driven decisions leading to timely and process-improving actions.
Why your hyperautomation isn’t materializing, and your problem backlog continues to grow.
Legacy AI-driven solutions have failed to deliver results because they have traditionally been too difficult to implement with fixed platforms, and they are expensive to purchase, customize, and deploy. Giant corporate AI initiatives often become a technological arms race, with continuous capability building yet insufficient clarity regarding the problems. Given that the average person lacks a million-dollar budget, their issues go unsolved.
Peter Sargent | VP of Product Management
Peter Sargant gives us an overview and perspective of Hyperautomation.
So automation, and I think robotic process automation is really what people think of most of when they think of automation. Automation has really been around automating those mundane processes that are better suited for software and systems to perform,
But I see the industry’s evolution over the last number of years has been on really driving better recognition of your business processes. And so now there’s so there’s so much more technology involved in identifying those areas of friction within your business processes.
And what we do is we put that information in the hands of your employees at the right time, at the right moment, With the proper context so that they can decide what decisions to make from there. So we very much rely upon human intuition and human judgment. To be a big factor in how we determine what to do next in terms of improving those processes.
We very much focus on empowering the individual to be a part of this process, using their human judgment, their intuition. We allow them to make those decisions, and really that the. Hype automation of the data that we provide is just to make them that much smarter and put them in a better position to identify these points of friction,
Make the changes as necessary. And obviously, automating those mundane tasks can still be part of the equation. But we think it’s really critical to focus on a recognition of the data. And recognition of what we detect within that data.
And then arming the individual with the information they need to take the next step. Well, the beauty of our solution is we really recommend you keep it simple,
I think you all recognize within your organizations there are areas where things can improve, processes have friction, And it’s really around focusing on just one simple use case. One use case where, you know, if you can reduce that friction, it will improve your processes.
I guarantee once you do that and we see this with our clients all the time, The light bulb goes off almost immediately. They recognize that there are so many other processes that they could also see this software being used to service.
And so, we recommend that you focus on a single use case because those additional use cases will come very quickly. And we’ll be able to create apps and create algorithms for you. To recognize any number of processes and allow you to have a great impact across really the entire organization.
So it really starts with one, keep it simple, identify the opportunity. And then once you see it work, once you see it at play, once you see one of our demonstrations.
I think you’ll immediately recognize that it has much broader applicability than just that one use case.
Download our RelayiQ Executive Brief on all things Hyperautomation
Hyperautomation is a rewarding journey, here’s how to take it one validating step at a time.
Organizations are often pressured to identify an exhaustive list of benefits before adopting a new technology. But with RelayiQ, it takes only a nominal investment and a single use case to get started. Once you see how hyperautomation can solve that single business problem, you’ll quickly recognize a broad array of possible applications.
Target a specific and hard to solve business challenge
Our “problem first” approach requires starting with a clearly defined problem, goal, and outcome. Typically, these problems benefit from detecting anomalies in data and business processes coupled with the automated delivery of prescribed actions that humans, machines, or both should take. This scenario could include:
- Predicting part failures with manufacturing data
- Identifying salespeople at risk of missing their quota
- Identifying fraud in financial data
- Predicting customer churn
- Automating steps to improve retention, etc.
Align your team to a well-defined outcome
Understanding what defines a successful outcome for the POC is as essential as determining the problem upfront. A POC can often help with one or more existing KPIs, and if not, it is sometimes better to re-evaluate the nature of the problem to ensure that the effort aligns with goals that will have a significant business impact.
- What is your business challenge that needs solving?
- Who within your organization is most directly impacted by this challenge?
- How is this challenge negatively affecting your business (i.e. KPI)?
- In what ways (and to what degree) do you hope you can improve this KPI with the help of hyperautomation?
- When must you start to realize improvements in your KPIs?
- What other ancillary benefits could come by addressing the core issue?
Validate with a compelling Proof-of-Concept
When conceptualizing the POC begin by defining the people that will be a part of your project – deliver it, receive it, or judge it. It’s important to remember that everyone being affected by your project in hand is in essence, a stakeholder, and their opinion will be critical to the POCs success. You should be able to reflect your major goals in more detailed criteria. For this, you can either look up commonly used KPIs or come up with your own criteria. For example:
- What are the underlying tools and processes you should verify?
- What are the main strengths of similar solutions in the market?
- What are the main weaknesses of similar solutions in the market?
- What issue to solve or need to satisfy is your concept aimed at?
- Who is the target audience of your finished solution?
- What essential metrics are you going to use?
See it. Believe it. Do it. Schedule your RelayiQ demo today.
