For a show that dedicated huge amounts of time and coverage to generative AI, multi-cloud co-existence, and healthcare (including the Cerner acquisition), Oracle CloudWorld did give some love to the back office. Those announcements targeted the firm’s Fusion Applications. These included a number of AI-related news items along with analytics and functionality improvements. Interviews with a couple of Oracle senior executives also shed light on areas like EPM (Enterprise Performance Management) and ESG (Environmental, Social & Governance) reporting.
But first, let’s add some context.
Oracle Fusion Cloud Applications evolution
Oracle announced its Fusion development program many years ago after it had acquired HR and Financial software vendor Peoplesoft. One goal of Fusion was to unify the code bases of numerous acquired and native Oracle applications while also upgrading everything to a more modern cloud platform.
Today’s Oracle Fusion Applications product line is indeed something to see. In the past, the company sold products it picked up from:
- Taleo (talent acquisition)
- Peoplesoft (HR and Finance)
- Datalogix International (process manufacturing)
- JD Edwards (financials, discrete manufacturing, construction)
- Siebel (CRM)
Now, Oracle Fusion Applications’ product line contains one of the largest suites of vertical and horizontal focused applications built on a single technology stack. All applications use Oracle Cloud Infrastructure (OCI), Oracle’s database technology, and common analytics, data lake and AI services layers. Currently, Oracle is re-platforming its recent healthcare acquisition, Cerner, to the Oracle stack.
Oracle’s install base for back-office applications is quite large. Here are some of the highlights mentioned at CloudWorld.
Prescriptive AI/ML models
Oracle is now offering new AI/ML capabilities in its ERP, SCM, HCM and CX Fusion application suites.
In ERP, these advanced capabilities are designed to:
- Predict Collection Risk (a key cash management/forecasting need)
- Predict On-Time payments and receipts for same
- Automatically classify spend/expenditures based on a number of invoice, receipt, etc. parameters
- Detect expense anomalies
The last item caught my attention as some research has suggested that as much as seven percent of all T&E spending could be fraudulent. This could represent a significant ROI opportunity for this one AI model/tool.
Oracle then discussed a different class of advanced capabilities re: its ERP applications. These new capabilities are being built with (and/or are possible via) generative AI and Large Language Model (LLM) tools. Think of these as highly secured corporate generative AI tools that mimic some of the capabilities found in consumer grade generative AI products (e.g., ChatGPT).
The generative AI tools can provide writing assistance, summaries, and recommendations for application end users, as well as writing code, extending applications, automating workflows and performing many other functions. Oracle repeatedly pointed out how its applications/tools will prevent a customer’s corporate data from becoming part of a public AI or training data set.
Some examples Oracle provided included helping Finance professionals add narratives to management reports and variance descriptions. Likewise, these authoring tools can kickstart the generation of notes to financial statements, journal entries, etc.
In HR, Oracle’s AI/ML tools will:
- Analyze a number of diversity factors
- Match employees and their skillsets to current and future employment/promotion needs
- Infer a person’s skills to more accurately and totally reflect an employee’s capabilities and potential
- Identify persons at-risk for leaving the company
Of these AI/ML tools, the skills points are particularly noteworthy as many firms are still making little or no progress in their wars for talent. One option for these firms is to better understand the people they already have in their employ and identify the skills, job experiences, etc. those individuals may need to fill other positions within the firm. AI/ML tools can really help here as they can dynamically generate any number of potential career paths for an employee based on different skills building scenarios. Furthermore, these tools can identify skills an employee may already possess although those skills may not be delineated in the HRMS system currently (e.g., an Accounts Payable manager that has been with your firm for many years very likely possesses many office automation, leadership and other skills).
Like ERP and Finance Applications, Oracle is bringing generative AI capabilities to the HR function. Assisted authoring capabilities will help HR personnel quickly generate job descriptions, summarize an employee’s performance/work history, and suggest questions for employee surveys. Additionally, these tools can suggest training and work experiences for employees. Other use cases included the authoring tools helping frontline managers generate potential copy for employee performance reviews and employee recognition.
Oracle representatives stated that these first wave of generative AI capabilities were mostly ideated by Oracle personnel but are hopeful that most future capabilities will be identified by customers and partners as the technology acquires greater familiarity within the install base.
Not all of the news involved AI and ML. Analytics got a lot of keynote time, too.
Oracle shared this screen [below] highlighting their rich interactive analytics. I suspect they made it an eye/vision chart so that we’d see just how many analytics are now available. I’ll spare you from eye strain and tell you that many of these analytics:
- Are the things many staff accountants have had to prepare/produce for most every accounting period
- Used to be calculated in spreadsheets that often required additional, periodic debugging
- Used to trigger a number of requests for additional detail or explanation when results deviated from expected values
- Make managerial or financial reporting less of drag.
What’s also nice about these analytics is that they let users get more into providing insights and consultative commentary to operational leaders. I’ve heard many new accounting college graduates state that they want to have value-adding, consultative careers and not just be a person that prepares schedules, books journal entries, etc.
Human Resources analytics are also offered. These analytics touch almost every aspect of HR.
These capabilities are available right out the box.
The 360-degree world
In addition to the AI/ML and generative-AI capabilities, Oracle touted its 360-degree data models. These data models help companies better understand its constituents (e.g., employees and suppliers), things (e.g., inventory, accounts and products), and, shipments. The Supplier 360 data models help customers “understand supplier performance based on delivery record, field quality inputs, financials and ESG ratings from data providers”.
Once assembled, Oracle calls these back-office solutions and capabilities its Fusion Data Intelligence Platform. This represents a new order of solutions where more than transaction processing and basic reporting occurs.
The new world possesses AI/ML powered and assisted apps that expedite, correctly, transaction processing and then use more AI/ML and generative AI tools to help decision makers make faster, better decisions. It’s not just a productivity play, it’s an intelligence play, too. And, the power behind all of this are highly efficient, cloud, hyperscaler data centers running Oracle equipment, systems software, etc. The Fusion Data Intelligence Platform runs on top of the OCI Data Lakehouse services, making the running of LLMs, ML algorithms, and complex analysis a breeze. Additional OCI platform services can be added to fit any analytics workload.
But wait, there’s more!
Oracle had other back-office announcements at this show. One of these detailed how Oracle has developed a number of employee engagement capabilities. According to Oracle:
Oracle has added new employee recognition and rewards capabilities to Oracle ME, the employee experience platform within Oracle Fusion Cloud Human Capital Management (HCM). The latest updates include Oracle Celebrate, a first-of-its-kind recognition and rewards offering that helps organizations boost performance, engagement, and retention by providing the workforce insights and capabilities needed to deliver a more personalized, meaningful experience for employees.
Oracle Celebrate is natively built in Oracle ME, part of Oracle Cloud HCM. This helps HR and business leaders tailor recognition programs to organizational values, naturally embed peer-to-peer recognition in daily workflows, and connect data across the entire employee experience platform to truly understand what is working and what isn’t among their workforce.
Oracle Celebrate offers a generative AI assistant to help managers make more meaningful feedback for employees.
Another innovation occurred in the Workforce Management area for Healthcare:
Oracle has introduced new workforce management capabilities within Oracle Fusion Cloud Human Capital Management (HCM) to help healthcare organizations adapt to changing labor markets, meet volatile customer demand, and better attract and retain workers. The new capabilities, Oracle Workforce Scheduling and Oracle Workforce Labor Optimization, connect business and Electronic Health Record (EHR) data on a single cloud platform to help healthcare organizations navigate advanced scheduling and labor needs.
AI/ML tools are often great technologies to assist in scheduling applications.
Office of the CFO
I spent time with Oracle’s Chief Sustainability Officer and one of their top EPM (Enterprise Performance Management) executives. These were unquestionably the most interesting and engaging conversations of the show. I previously noted Oracle’s ESG efforts and won’t duplicate my comments.
The ESG conversation took an interesting turn as we discussed not just the water and energy that cloud data centers consume but looked at how this usage is exploding as ever more algorithms, LLMs and other AI/ML capabilities are used by companies. In particular, we discussed:
- Do companies need to keep LLM and other AI-style training data online once it has been reflected in the tool’s logic? In other words, do companies need to keep sensor, meter, website navigation and other data online after a period of time has lapsed? Could much of this data be placed on a different media than always-on servers? Should great AI strategies be cognizant of this and have protocols for the access, use, long-term storage and retrieval of this information?
- Should more ROI case studies look at the long-term power and cooling costs associated with newer AI based tools?
- Are companies factoring in these matters in their current ESG reports and will they need to soon?
- How will Oracle incentivize its customers to be good cloud and environmental stewards as to their cloud and advanced technology usage?
I also had conversations concerning the need to marry the best of a software firm’s EPM, ESG and Enterprise Risk Management applications together to better reflect the rapidly growing functional needs, analysis and exposure/risks controls needed in businesses today.
To isolate one discussion item of ours, we talked about how new SEC ESG reporting requirements will likely hit US-headquartered firms this Fall. Firms that do not or cannot accurately report their full and complete exposure to forever chemicals or other items harmful to the environment or humans could see significant increases in risk exposure, government actions and potential shareholder suits should the firm’s stock price decline due to these reporting shortcomings.
In short, firms will want to better track a number of new risks (via an ERM tool), capture in real time many key ESG-related date elements (in an EPM tool), and then map these values to numerous regulatory reports (via ESG or EPM tools). EPM is no longer just a tool for budgeting, planning and financial consolidation.
Other notable items
Oracle also discussed how it will incorporate other external data into its AI capabilities. Marrying this with the data in its Fusion Applications can create what it describes as Intelligent Applications. Oracle mentioned three that I saw:
- A Supply Chain Command Center that monitors and dynamically adjusts a firm’s supply chain based on new data (e.g., a Pacific hurricane could disrupt a number of planned cargo container shipments unless a SC planner adjusts orders, etc.)
- A People Leader Workbench that grabs all kinds of information (including social media data) about a worker so that managers can better prepare for career planning, training, etc. discussions.
- A Dynamic Sales Forecasting tool that uses scenario modeling to improve forecast accuracy.
Attendees might have gotten earfuls on generative AI and other Oracle technical innovations, but those attendees in the back office will likely need a few weeks/months evaluating which advanced technologies they’ll bring online and when. It’s actually a great thing for software customers to be on the receiving end of lots of new capabilities instead sitting idle for months or years waiting for something new to show up.
Next year’s event should be even more interesting as the product use cases will be more customer (not vendor) driven. I look forward to seeing what customers will ask for.