Pega used its annual user, customer & partner convention this year to showcase a set of solid extensions, connections and augmentations to its core platform. The working functions encapsulated within Pega Infinity ’23 help to showcase how low-code technologies actually work – and, if we drink the Pega Kool-Aid – they also help organisations get on the road to more comprehensive operational autonomy.
NOTE: Pega has now shifted the naming convention of its platform to reflect its annual release cadence, hence Pega Infinity ’23 in 2023.
But before we open up the low-code toolbox and start looking for the spanners, wrench and grease gun, what is this operational autonomy proposition that the company is so keen to put forward?
Pega suggests that the autonomous enterprise is the notion of any business (in any given industry vertical) that is capable of comprehensively applying Artificial Intelligence (AI) and Machine Learning (ML) across its business fabric to provide a utilitarian approach to automation that sees it applied to customer engagement, servicing and operations across the entire organisation.
It is (if you can get past the industry marketing-speak) and means of operationalising agility to create a business that can become self-optimising. A Pega-driven independently executed study found that 58% of respondents expect to define themselves as an autonomous enterprise within the next 10 years.
According to Pega, “With just 15% [of firms questioned] saying they feel they are already at this stage today and 36% projecting they will reach this point five years from now, the upward curve of autonomous enterprise adoption is clear. Tellingly, three-quarters (73%) of respondents said they already have some sort of plan to start becoming an autonomous enterprise. When asked what they expected their position to be 10-years from now, an overwhelming 96% said the same.”
How do firms get to this state of being?
Ask the low-code advocates at Pega and they’ll point you to Pega Infinity ’23, the current iteration of the company’s core platform, suite and tools designed to help software application developers to build and iterate enterprise apps with essentially rich customer engagement and customer service characteristics.
“Pega Infinity unifies customer engagement, customer service and intelligent automation capabilities within a single platform to help accelerate digital transformation. By engaging customers with the right message, at the right time, across any channel, clients can improve customer satisfaction, increase customer lifetime value and boost productivity,” said the company, a press statement.
How do those productivity boosts come about?
Through low-code functions that we will explore here in an attempt to understand how these platforms really help software engineers to work better, smarter, faster and more enjoyably.
Governed pre-built business logic
Pega has provided a ‘reuse library’ as part of its Pega App Studio technology that works to enable users to discover and share reusable software code components. Designed for professional developers and also offering a functionality nod to citizen developers, the company insists it has locked down this technology for robustness so that users can make effective and governed use of pre-built business logic, integrations, AI models and so on.
In the User eXperience (UX) space, Pega says it has delivered its Pega Constellation technology to help build applications based upon low-code flexible architecture precepts that it promises will be more engaging and accessible with more intuitive UX throughout.
“With Constellation, users can seamlessly scale application designs with the latest built-in design components, templates and patterns. Additionally, automatic updates follow Pega’s latest best practices to help ensure applications are in top shape,” notes Pega.
For inclusivity, Pega says it has now delivered enhanced accessibility functions with the W3C’s Web Content Accessibility Guides (WCAG) 2.1. This means that Pega Infinity ’23 will offer standard accessibility compliance in its out-of-the-box features, along with design guidance built directly into authoring tools so that developers will be able to create more inclusive applications.
We can cross off the process management checkbox here too.
Pega has brought forward process AI case categorisations. This involves new AI capabilities that will predict the class and category of a particular ‘customer query case’, categorise data to implement a user’s chosen data classification categories and route and assign work to the proper individual. Additionally, users will be provided with related context so they can get up to speed and resolve the case as quickly as possible. This will help avoid re-assignments and save valuable costs and time while providing better experiences and trust in AI effectiveness.
There are (as we would expect from Pega) extended low-code marketing tools on offer here. For what the company likes to call ‘agile 1:1 operations’, new features include One-Time Actions, a software tool that can be used to create new ‘customer messages’ for specific audiences to address a distinct and immediate need, such as an emergency notification.
Higher ‘decisioning accuracy’
In strategy optimisation. Developers will be able to achieve higher ‘decisioning accuracy’ with new Pega Infinity ‘23 features including Conversion Modeling (the term in this case being used to describe the ‘conversion’ of prospects to customers, or the ‘conversion’ of new users to any given service into being fully signed up members) which will use adaptive models to determine a customer’s propensity to take a specific action, such as making a purchase or finishing an onboarding journey.
“Although perhaps unlikely to feature in the Oxford English Dictionary ‘word of the year’, the notion of ‘decisioning’ describes human-governed machine-supported business decision-making underpinned, fueled, accelerated and driven by AI models and a decision engine spanning not just generative AI, but also where other types of AI are also featured such as sense and response analytics, traditional statistical models and more,” clarified Vince Jeffs, senior director, product strategy, marketing & decisioning at Pega.
In terms of further official take on this term, the company says that real-time decisioning is the core capability of Pega Customer Decision Hub™. [Our] always-on, AI-driven engagement engine ingests interaction data instantly, evaluates all options and selects the next best action for each individual. It enables you to predict customer needs and personalise every interaction on any channel.
Additionally, an enhanced capability for testing and deploying Machine Learning (ML) models will help users conduct field experiments with specific models for high-value use cases and complex interactions to determine success. Once satisfied, users can activate those models with a single click.
New capabilities like Pega Feature Finder will allow users to configure Pega to turn customer data into actionable insights by continuously scanning data to identify new predictors as they arise (e.g. finding and using the feature ‘contract expiration date’ to improve propensity to respond). In addition, new integrated Identity Management capabilities will improve the use of prospect and customer data for more complete profiles and relevant actions.
Users will also be able to get their hands on the latest Pega Constellation APIs to integrate Pega workflows and knowledge articles into portals or mobile apps – and these can be built into any modern enterprise application design system. Pega says this will provide the flexibility to use existing technology with Pega Customer Service for more consistent, end-to-end customer journeys across applications. For example, clients can embed Pega self-service workflows to automate resolutions from start to finish for faster resolution and better customer experiences.
Rise of the autonomous enterprise
As deep-dive as some of these functions are, they are all still essentially low-code platform technologies designed to provide organisations with a route to achieving this dream of the autonomous enterprise that Pega puts forward here. As we go forwards, it is surely not unreasonable to suggest that a) the functions themselves will become even further abstracted, compartmentalised and low-coded so that b) organisations have even faster routes to creating self-service or indeed no-touch operations inside the business as it runs every day.
The autonomous enterprise is becoming real… and this is a reality that is (perhaps paradoxically) being delivered and created in an ultimately virtualised AI-enriched way.