Oracle on Wednesday said it is adding new AI and automation capabilities to its Fusion Supply Chain Management (SCM) and Fusion Human Capital Management (HCM) suites to help enterprises increase efficiency across divisions.

The updates to the SCM suite, which have been made generally available, include an AI-based planning tool, an enhanced quote-to-cash process for Fusion applications, and new rebate management capabilities.

The AI-based planning tool, according to the company, is expected to aid enterprises in improving the accuracy of lead time assumptions across their supply chain through machine learning.

“The new feature can improve planning efficiency and results by identifying lead time trends, anomalies, and their potential impact with prioritized actions and resolution suggestions,” the company said in a statement.

The new planning tool has been added to the planning advisor inside Oracle Supply Chain Planning, an application that is part of the company’s SCM suite.

Since last year, Oracle has been gradually adding new capabilities, including some AI and automation features, to its supply chain suite.

Last year in February, Oracle introduced machine learning-based shipping time forecasting along with real-time analytics for the supply chain.

In October, the company released a new supply chain management application customized for healthcare companies, dubbed Oracle SCM for Healthcare. The application offers capabilities such as a supply chain planning service and added capabilities for the Oracle Procurement application to help drive down supply chain costs.

As part of the new updates to its SCM suite, Oracle is offering an enhanced quote-to-cash process across all Fusion applications.

Quote-to-cash (QTC) process is a part of the sales cycle in an enterprise that constitutes end-to-end delivery of a product or service. Typical components of the process include sales, account management, order fulfillment, billing, and accounts receivables functions.

The enhanced QTC process, according to the company, will help enterprises centralize subscription orchestration, comply with accounting requirements, improve order management, reduce costs while decreasing time to market, and improve customer experience.

“The integrated solution connecting Subscription Management (CX), Configure Price and Quote (CX), Order Management (SCM), and Financials (ERP),enables customers to quote, capture, and fulfill orders (of mixed physical goods, subscriptions, and services) more efficiently and recognize revenue accordingly,” the company said in a statement.

Oracle has added new rebate management capabilities inside the SCM suite to aid enterprises to optimize discounts or promotional campaigns targeted toward their customers.

The new capabilities automate the rebate management process, the company said, adding that automation includes rebate calculation, financial settlement, and closing customer claims.

This helps reduce administration costs and improves customer experience, the company said, adding that the new capabilities are being offered as part of Oracle’s Channel Revenue Management application under the SCM suite.

New updates to Oracle Fusion HCM suite

In addition to the new updates to the SCM suite, Oracle has announced a new application, dubbed Oracle Grow, in an effort to add more AI capabilities to its HCM suite.

“Oracle Grow is designed to enhance the employee experience and improve performance by engaging with individuals to discover new growth opportunities and empowering managers to align upskilling and reskilling with business priorities,” Chris Leone, executive vice president of applications development at Oracle Cloud HCM, said in a statement.

To be offered as part of Oracle Me that was released in April last year under the HCM suite, the AI-powered application delivers personalized insights and intelligent guidance across all interactions from Oracle Learning, Oracle Dynamic Skills, and Oracle Talent Management in one interface, the company said.

In order to provide insights, the AI engine inside the application is trained on an enterprise’s data in a controlled environment before being rolled out completely, according to Natalia Rachelson, group vice president of outbound product management for Fusion Applications at Oracle.

“We would start small, and we would see what kind of results the AI is recommending and then we work with customers to fine-tune the models to adjust to their specific sort of datasets,” Rachelson said, adding that the data normalization is done by Oracle data scientists.

This means that for new Oracle Fusion customers, rolling out Oracle Grow’s AI capabilities would require a longer time, the group vice president said.

Oracle Grow’s AI capabilities include growth experience for employees, suggestions for career paths within their enterprise, personalized development suggestions, and managerial skilling.

The AI engine in Oracle Grow, according to the company, can suggest development opportunities that workers need to adapt to changes in their role, discover new growth options, and achieve their career aspirations. “By unifying people data from across Oracle Cloud HCM, Oracle Grow provides personalized guidance on the next steps employees should take based on their responsibilities, career interests, desired skills, individual learning styles, and changes in the business,” the company said in a statement.

ERP Systems, Oracle, Supply Chain Management Software

In a bid to help retailers transform their in-store, inventory-checking processes and enhance their e-commerce sites, Google on Friday said that it is enhancing Google Cloud for Retailers with a new shelf-checking, AI-based capability, and updating its Discovery AI and Recommendation AI services.

Shelf-checking technology for inventory at physical retail stories has been a sought-after capability since low — or no — inventory is a troubling issue for retailers. Empty shelves cost US retailers $82 billion in missed sales in 2021 alone, according to an analysis from NielsenIQ.

The new AI-based tool for shelf-checking, according to the company, can be used to improve on-shelf product availability, provide better visibility into current conditions at the shelves, and identify where restocks are needed.

The tool, which is built on Google’s Vertex AI Vision and powered by two machine learning models — product recognizer and tag organizer — can be used to identify different product types based on visual imaging and text features, the company said, adding that retailers don’t have to spend time and effort into training their own AI models.

Further, the shelf-checking tool can identify products from images taken from a variety of angles and across devices such as a ceiling-mounted camera, a mobile phone or a store robot, Google said in a statement. Images from these devices are fed into Google Cloud for Retailers.

The capability, which is currently in preview and is expected to be generally available to retailers globally in the coming months, will not share any retailer’s imagery and data with Google and can only be used to identify products and tags, the company added.

Improving retail website experience

To help retailers make their online browsing and product discovery experience better, Google Cloud is also introducing a new AI-powered browse feature in its Discovery AI service for retailers.

The capability uses machine learning to select the optimal ordering of products to display on a retailer’s e-commerce site once shoppers choose a category, the company said, adding that the algorithm learns the ideal product ordering for each page over time based on historical data.

As it learns, the algorithm can optimize how and what products are shown for accuracy, relevance, and the likelihood of making a sale, Google said, adding that the capability can be used on different pages within a website.

“This browse technology takes a whole new approach, self-curating, learning from experience, and requiring no manual intervention. In addition to driving significant improvements in revenue per visit, it can also save retailers the time and expense of manually curating multiple ecommerce pages,” the company said in a statement.

The new capability, which has been made generally available, currently supports 72 languages.

Personalized recommendations for customers

In order to help retailers create hyperpersonalization for their online customers, Google Cloud has released a new AI-based capability for its Recommendation AI service for retailers.

The new capability, which is expected to advance Google Cloud’s existing Retail Search service, is underpinned by a product-pattern recognizer machine learning model that can study a customer’s behavior on a retail website, such as clicks and purchases, to understand the person’s preferences.

The AI then moves products that match those preferences up in search and browse rankings for a personalized result, the company said.

“A shopper’s personalized search and browse results are based solely on their interactions on that specific retailer’s ecommerce site, and are not linked to their Google account activity,” Google said, adding that the shopper is identified either through an account they have created with the retailer’s site, or by a first-party cookie on the website.

The capability has been made generally available.

Artificial Intelligence, Cloud Computing, Retail Industry, Supply Chain

In a bid to help enterprises offer better customer service and experience, Amazon Web Services (AWS) on Tuesday, at its annual re:Invent conference, said that it was adding new machine learning capabilities to its cloud-based contact center service, Amazon Connect.

AWS launched Amazon Connect in 2017 in an effort to offer a low-cost, high-value alternative to traditional customer service software suites.

As part of the announcement, the company said that it was making the forecasting, capacity planning, scheduling and Contact Lens feature of Amazon Connect generally available while introducing two new features in preview.

Forecasting, capacity planning and scheduling now available

The forecasting, capacity planning and scheduling features, which were announced in March and have been in preview until now, are geared toward helping enterprises predict contact center demand, plan staffing, and schedule agents as required.

In order to forecast demand, Amazon Connect uses machine learning models to analyze and predict contact volume and average handle time based on historical data, the company said, adding that the forecasts include predictions for inbound calls, transfer calls, and callback contacts in both voice and chat channels.

These forecasts are then combined with planning scenarios and metrics such as occupancy, daily attrition, and full-time equivalent (FTE) hours per week to help with staffing, the company said, adding that the capacity planning feature helps predict the number of agents required to meet service level targets for a certain period of time.

Amazon Connect uses the forecasts generated from historical data and combines them with metrics or inputs such as shift profiles and staffing groups to create schedules that match an enterprise’s requirements.

The schedules created can be edited or reviewed if needed and once the schedules are published, Amazon Connect notifies the agent and the supervisor that a new schedule has been made available.

Additionally, the scheduling feature now supports intraday agent request management which helps track time off or overtime for agents.

A machine learning model at the back end that drives scheduling can make real-time adjustments in context of the rules input by an enterprise, AWS said, adding that enterprises can take advantage of the new features by enabling them at the Amazon Connect Console.

After they have been activated via the Console, the capabilities can be accessed via the Amazon Connect Analytics and Optimization module within Connect.

The forecasting, capacity planning, and scheduling features are available initially across US East (North Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (London) Regions.

Contact Lens to provide conversational analytics

The Contact Lens service, which was added to Amazon Connect to analyze conversations in real time using natural language processing (NLP) and speech-to-text analytics, has been made generally available.

The capability to do analysis has been extended to text messages from Amazon Connect Chat, AWS said.

Contact Lens’ conversational analytics for chat helps you understand customer sentiment, redact sensitive customer information, and monitor agent compliance with company guidelines to improve agent performance and customer experience,” the company said in a statement.

Another feature within Contact Lens, dubbed contact search, will allow enterprises to search for chats based on specific keywords, customer sentiment score, contact categories, and other chat-specific analytics such as agent response time, the company said, adding that Lens will also offer a chat summarization feature.

This feature, according to the company, uses machine learning to classify, and highlight key parts of the customer’s conversation, such as issue, outcome, or action item.

New features allow for agent evaluation

AWS also said that it was adding two new capabilities—evaluating agents and recreating contact center workflow—to Amazon Connect, in preview. Using Contact Lens for Amazon Connect, enterprises will be able to create agent performance evaluation forms, the company said, adding that the service is now in preview and available across regions including  US East (North Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (London).

New evaluation criteria, such as agents’ adherence to scripts and compliance, can be added to the review forms, AWS said, adding that machine-learning based scoring can be activated.

The machine learning scoring will use the same underlying technology used by Contact Lens to analyze conversations.

Additionally, AWS said that it was giving enterprises the chance to create new workflows for agents who use the Amazon Connect Agent Workspace to do daily tasks.

“You can now also use Amazon Connect’s no-code, drag-and-drop interface to create custom workflows and step-by-step guides for your agents,” the company said in a statement.

Amazon Connect uses a pay-for-what-you-use model, and no upfront payments or long-term commitments are required to sign up for the service.

Cloud Computing, Enterprise Applications, Machine Learning

Increasing its focus on healthcare industry customers, Oracle on Wednesday announced updates  for its Cloud Fusion suite aimed at meeting their financial planning, supply chain and human resources needs.  

The updates, which were announced at the company’s ongoing annual CloudWorld conference, include additions to the company’s Enterprise Performance Management (EPM), Supply Chain management (SCM) and Human Capital Management (HCM) suites.

The healthcare sector has become a major target for Oracle, as signaled by its $28 billion acquisition of healthcare systems maker Cerner, which closed in June.

Better financial planning via EPM suite

In order to help healthcare companies optimize financial and operational management, the company said it was launching planning capabilities that can model scenarios, determine future demand, optimize resources, and help users make better financial, workforce, and patient care decisions.

Dubbed Oracle Cloud EPM Solutions for Healthcare, the new features will be offered as part of Oracle Fusion Cloud Enterprise Performance Management (EPM) suite.

“Outdated financial systems and processes prevent many healthcare organizations from being able to adapt quickly to operational uncertainties, which impact their ability to manage costs, operate efficiently, and provide the best possible care,” Matthew Bradley, senior vice president of applications development at Oracle, said in a statement.

The additions to the EPM suite will offer planning and management capabilities for financial statements, balance sheets, and cash flow.

Other capabilities include performance management monitoring, demand forecasting, workforce optimization and capital expense planning.

Updates to supply chain management suite

Oracle on Wednesday also added specific tools to aid healthcare firms with supply chain issues.

These tools, according to Oracle, will help improve patient care by optimizing supply chain planning, automating processes, and enhancing visibility into what’s happening across a company’s supply chain.

Dubbed Oracle SCM for Healthcare, the new capabilities will be offered as part of Oracle’s Fusion Cloud Supply Chain and Manufacturing (SCM) suite. They include a new home equipment delivery application, a new supply chain planning service and added capabilities for the Oracle Procurement application to help drive down supply chain costs.

Updates to human resource management suite

In an effort to help healthcare providers manage staff efficiently, Oracle said that it was launching a specialized set of tools for Oracle ME (my experience), which is part of the Fusion Cloud Human Capital Management (HCM) suite.

The new capabilities will reduce burnout and costs by improving efficiency, and deliver better patient care by providing a user interface that meets the unique needs of healthcare workers, the company said in a statement.

The tool set includes capabilities designed to attract talent and develop staff skills, reduce costs, improve productivity, and optimize staffing and scheduling.

Oracle said that the healthcare additions to the EPM suite are generally available now; some of the new HCM features are available now, and a schedule for rollout of all the new capabilities will be issued soon; and the SCM updates will be generally available soon.

(This story has been updated to correctly spell out the term EPM, which stands for Enterprise Performance Management.)

Cloud Computing, ERP Systems, Healthcare Industry

Whenever CIOs talk about using low-code tools to enable citizen development, a recurring theme is how to ensure appropriate governance of the applications produced.

Microsoft has heard them loud and clear, and at its Ignite 2022 show in Seattle this week, it introduced a range of new governance capabilities and other enhancements for its Power automation platform.

It also previewed new management capabilities for automated workloads in its Entra Identity governance tool, new compliance reporting tools for monitoring the roll-out of Windows updates on enterprise desktops, and a host of updates to its Azure cloud platform.

Power to the people

Even low-code may seem like a foreign language to some workers, so Microsoft has been experimenting with ways to enable them to generate workflows with Power Automate, describing in natural language what they want to achieve and leaving an AI to build the corresponding flow. The feature, now in preview, will still require workers to set up connectors for the inputs to and outputs from the automated workflow, and to tweak it to ensure it behaves as intended.

Given the scope for ambiguity in natural language, CIOs may want to reinforce governance of applications created in this way — and with the new Managed Environments for Power Platform, Microsoft will help them do just that. First previewed in July, it’s now generally available.

Checks and balances

A new Weekly Digest feature enables admins to see how much use each Power app is getting, directing attention to the most used and reclaiming resources from unused ones.

There are also new tools to limit sharing of apps by security group or number of users, so apps don’t go viral across the enterprise until they’ve been thoroughly tested and channels are set up to communicate changes to them.

Those features will be important to CIOs, according to Kyle Davis, a VP and analyst at Garner covering low-code adoption.

“When it comes to citizen development and low code, governance is front and center,” he said.

Managed Environments is more of an evolution than a revolution, he added, saying, “There really isn’t anything there that someone couldn’t build for themselves if they wanted to.”

Indeed, Managed Environments has its origins in Microsoft’s Automation Center of Excellence starter kit, which enables enterprises to define their own best practices for Power app governance. But as the company itself acknowledges, customers found that this required a lot of manual work and expertise.

Davis said that CIOs looking for the simplicity of low-code development are often also looking for similar simplicity in its management. Managed Environments’ ability to deploy controls in a few clicks will be appealing. “It makes it easier to do things at scale,” he said.

The option to limit usage of an app to a few cubicle neighbors makes sense too, he said, because, “You can just yell across the hallway, ‘Hey, I’m going to make a change,’ and everyone’s aware,” while a change departmental app would need to go through a proper process. “What Microsoft offers with Managed Environments is something that you don’t really get from other low-code vendors in a similar space,” he said.

Environmental awareness

Not all the news at Ignite concerned Power Platform, however. Microsoft also had plenty to say about updates to its Azure cloud infrastructure offering, and an update of Syntex, its AI content management tool. Computerworld has the low-down on Syntex, but CIOs will want to be aware of other innovations that may help them trim management budgets or redeploy staff away from routine tasks.

There are new features for Microsoft Sustainability Manager, an environmental reporting tool for enterprises, including an extended data model to assist them estimating so-called Scope 3 emissions of greenhouse gases by their entire supply chain, and an Emissions Impact Dashboard for Microsoft 365 showing greenhouse gas emissions resulting from their use of Microsoft’s SaaS productivity suite.

Azure Deployment Environments, previewed at the show, offer enterprises a way to apply project-based templates to each development environment they spin up. Much like the managed environments Microsoft is introducing for low-code applications, these new templates will help development teams consistently maintain best practices across projects with minimum effort, the company said.

Cost cutting

Another management feature, Azure Automanage, is now generally available for Azure VMs and has new capabilities including the ability to patch VMs without rebooting, reducing downtime costs.

For variable computing workloads in the Azure cloud, Microsoft is introducing the ability to mix Standard and Spot Virtual Machines in the same scale set, enabling CIOs to profit from the deep discounts available for Spot VMs as their computing needs vary.

But Microsoft also wants customers to see Azure as an economical solution for base workloads. Azure savings plan for compute, available later this month, offers a discount to customers who commit to spending a minimum hourly amount on computing resources for one to three years; consumption above the minimum commitment will be charged at regular rates.

Staying Intune

Microsoft is reshuffling its branding around endpoint management: Intune, previously a component of its enterprise mobility management offering, is now the umbrella brand for its whole range of endpoint management products such as Configuration Manager — with the promise of more to come. At Ignite, the company is previewing new endpoint privilege management capabilities such as the ability to temporarily grant users limited admin permissions, and automated app patching by combining Intune with Microsoft Defender. In January 2023, it will add Microsoft Tunnel so employees can securely access company resources from their own devices without having to enroll them first. And then in March 2023, a new bundle of premium endpoint management services called Advanced Management Suite will be introduced.


Google on Tuesday said it was updating its AI agent-based technology to add an enterprise-scale translation service, and to further automate document processing.  

The services, announced at the Google Cloud Next conference, are being delivered via a new AI-based translation service called Translation Hub, and two new features in Google’s Document AI offering.

The Translation Hub, according to the company, is an AI agent-based service that offers self-service document translation with support for 135 languages.

To translate documents, the service uses a combination of Google technologies such as neural machine translation and AutoML, the company said.  Translation Hub will support Google Docs, Slides, PDFs and Microsoft Word documents.

“It not only preserves layouts and formatting, but also provides granular management controls such as support for post-editing human-in-the-loop feedback and document review,” June Yang, vice president of cloud AI and industry solutions at Google, wrote in a blog post.

Using Translation Hub, enterprises can share their translated findings across the world in a cost-effective manner, Yang added.

At Google I/O this year, the technology giant had announced the addition of 24 new languages to Google Translate.

AI agent to automate document processing

To make document processing easier for enterprises, Google has added two new features to its Document AI service, which was first made available in April last year, designed to allow enterprises to parse documents efficiently and drive data towards the right employee within the enterprise.

Document AI also includes a human-in-the-loop (HITL) workflows to ensure accuracy when needed.

The two new features include Document AI Workbench and Document AI Warehouse.

The Document AI Workbench, according to the company, allows enterprises to custom select the fields of interest while parsing a document.

“Relative to more traditional development approaches, it (Document AI Workbench) requires less training data and offers a simple interface for both labelling data and one-click model training,” Yang wrote.

The Document AI Warehouse feature brings Google’s search technologies to Google Document AI, the company said, adding that the feature is expected to make it easy to search and manage documents including their workflows within the enterprise.

Document AI competes with services such as Amazon Textract and Microsoft Azure Form Recognizer.

Artificial Intelligence, Cloud Computing, Document Management Systems