Facing the possibility of an economic recession, one of the world’s leading professional services companies felt the urgency to improve its grasp on spend management – the practice of fully understanding and managing supplier relations and company purchasing.

With 738,000 employees and $3.8 billion in services contracts, it was crucial for Accenture to not only identify every dollar being spent but also assess whether the organization was fully exploiting each expenditure.

But a sense of frustration pervaded the company, as procurement teams complained about limited visibility into contract terms and challenges tracking statement of work (SOW) agreements, pacts specifying goals, and deadlines expected of external employees.

The capacity to generate the SOW contracts and effectively manage services spend depended upon the region since each was reliant on different processes and documentation requirements.

Inadequate services spend visibility also increased exposure to local legal and regulatory risks.

Likewise, customers were unsatisfied with a procurement process that was disjointed and inflexible when quick changes were needed.  

Improvements were needed and the deadline was tight.

“Procurement functions require a lot of time and effort working with suppliers to negotiate the best contract with the best terms,” said Patricia Miller, Accenture’s interim Chief Procurement Officer (CPO), “but if we are not able to compare the delivered service against that agreement in a systematic way, how can we assure that the hard-earned negotiated terms were applied?” 

To relieve this quandary, Accenture launched a campaign to build a vigorous, dynamic procurement function to unlock more value by providing extraordinary visibility into services spend. 

The global standard at lightning speed

Based in Dublin, Ireland, Accenture specializes in digital, cloud, and security technology strategies, consulting, and operations, serving more than 40 industries in more than 120 countries.

Now, as it conceptualized a new platform to effectively manage services spend, it was forced to change its deployment system.

Previously, deployment planning was laborious, requiring substantial time and investment.  The lengthy process slowed feedback on solution design, as well as delivery times on changes.

Yet, Accenture had a dependable, long-term partner in enterprise resource planning (ERP) software pioneer SAP, first adopting the company’s solutions in 2004.

As it faced its latest challenge, Accenture chose SAP Fieldglass, a vendor management system for services procurement and external workforce organization, to provide reporting and analytics.

In addition to implementing a global standard template – rather than a variety of country-specific prototypes – the solution would be customized to meet local invoicing, legal, and regulatory requirements.

From submission to payment, not only would turnaround time be reduced, but collaboration and communication with suppliers were about to reach unprecedented levels.

Meeting changing markets and business demands

The function was deployed back in 2020 in the first of many country-by-country rollouts.

Although the typical technology deployment had taken an average of one year per nation, the expedited timeline enabled 14 countries to begin using the solution within 12 months.

A global management team was also formed to support the effort.

Given the importance of the implementation, constant feedback was needed, and the enhanced technology amplified the level of dialogue, streamlining both testing activities and the ability to deliver required changes.

Today, Accenture’s procurement arm is better equipped to meet changing market and business demands than ever before.

For the first time, Accenture has a heightened understanding of the “hidden” workforce associated with its service business.  Since external workers may not always fit traditional profiles, users are able to cull contract information to link specific employees to their individual skill sets.

Explained Jane M. Kennedy, Global External Management Director for Accenture, “Today, we have much-proved…visibility for management (due to) an online solution that aligns to each worker’s type of engagement.” 

Suppliers noted the ease of transitioning to SAP Fieldglass, and the pace at which entire companies were able to adopt the platform.

Currently, 2,000 suppliers have implemented the system, while $ 1 billion in services spend are managed through the function each year, resulting in a more transparent supply chain and significant cost savings.

That includes the reduced fees for document storage in regions where procurement practices were primarily paper based.

Users report 99% greater accuracy, as well as 7% error reduction per 10,000 SOWs.

For creating a global standard procurement process through its development of a novel solution, Accenture was distinguished as a finalist at the 2023 SAP Innovation Awards, a yearly ceremony honoring organizations using SAP technologies to improve business and society. You can read their pitch deck to see what they accomplished to earn this honor.

Digital Transformation

Enterprise resource planning (ERP) software vendor IFS has agreed to acquire Falkonry, the developer of an AI-based time-series data analytics tool, to boost its enterprise asset management (EAM) services portfolio.

IFS has an eye on the growing number of connected machines in factories, and will add Falkonry’s self-learning Time Series AI Suite, which can help enterprises manage and maintain manufacturing equipment, to its existing enterprise simulation and AI-based scheduling and optimization capabilities.  

EAM can be considered a subset of ERP software, providing tools and applications to manage the lifecycle of physical assets in an enterprise, in order to maximize their value. The global EAM market is expected to grow at a compound annual growth rate (CAGR) of 8.7% to reach $5.5 billion by 2026, from $3.3 billion in 2020, according to research from MarketsandMarkets.

Cupertino-headquartered Falkonry, which was founded in 2012 by CEO Nikunj Mehta, has customers across North America, South America, and Europe, including the US Navy and Air Force, Ternium, North American Stainless, and Harbour Energy, among others. It has raised $13.3 million in funding from investors including Zetta Venture Partners, SparkLabs Accelerator, Polaris Partners, Presidio Ventures, Basis Set Ventures, Fortive, and Next47. IFS expects to complete the acquisition of Falkonry by the fourth quarter of 2023. In June, it announced the acquisition of Poka — a connected worker software services provider — in order to boost the productivity of an overall factory. And last year it scooped up Netherlands-based Ultimo to help meet demand for cloud-based enterprise asset management technology.

Asset Management Software, Enterprise Applications, Mergers and Acquisitions

Anxious to meet international standards, satisfy investors, and profit from a growing array of sustainable products, financial services firms are intensifying their focus on environmental, social, and governance (ESG) goals. While the incentives for ESG are compelling, managing programs and demonstrating success are fraught with challenges. But by adhering to the right standards and using technology to better organize programs, financial firms can gain a clearer vision of their ESG operations and speed up progress toward their goals. 

Doing well by doing good 

Many financial institutions are striving to align ESG programs with the United Nations’ 2030 Agenda for Sustainable Development, which lists 17 goals designed to end global poverty and promote an equitable transition to a sustainable world.  

“Companies across the globe are adopting the 2030 Agenda and UN SDGs Framework to ensure sustainable investments and operations,” says Kishan Changlani, Partner for strategic initiatives – sustainable banking, at Tata Consultancy Services (TCS).  

Financial services firms can use the 2030 Agenda and UN SDGs Framework as a guide for allocating ESG funds, such as creating a “green economy” team dedicated to helping companies that produce environmentally friendly goods and services. Leadership teams are also learning that ESG initiatives can boost business performance. One 2022 study found that organizations placing greater emphasis on ESG over the previous three years saw revenues increased by almost 10%, compared to 4.5% revenue growth from businesses showing a lower commitment to ESG.  

Overcoming data challenges 

Despite their growing commitment to ESG, financial firms have learned the path to sustainability and prosperity can be rocky. 

“ESG data quality is the biggest challenge. Quality at the least is about consistent data across asset classes, effective data for scenario planning, and harmonized ESG ratings amongst other aspects,” Changlani says. However, there are many other challenges as well, including regulatory requirements, human capital, stakeholder engagement, alignment of materiality and performance, and the need to embed ESG into an existing ERM (Enterprise Risk Management) framework. 

“The ESG regulatory landscape resembles an alphabet soup where the number of ESG standard-setters, data aggregators, analysis providers, ESG raters, and indices is increasing,” says Changlani.  

Financial services companies may also find it challenging to keep up with a broad scope of reporting requirements, resulting in a complex set of documents and deliverables that can lead to questions about a program’s validity or perception of greenwashing. 

Technology can help banks and other financial institutions overcome these hurdles. For example, TCS has developed a suite of solutions on Microsoft Cloud to unify and integrate ESG metrics and accurately measure performance. Changlani also recommends that companies limit data vendors to two or three and establish their own ESG benchmarks, instead of relying solely on external providers.  

Emerging technologies will further speed ESG progress. AI and machine learning algorithms can monitor compliance in real time. With natural language processing, organizations can analyze millions of reports quickly, helping them avoid pitfalls associated with greenwashing and other discredited activities. 

Blockchain technology can track assets across the supply chain, promoting transparency and credibility.  

“Technology is the key to helping the financial services industry move toward the greater good,” says Changlani. “It is what will make achieving the UN 2030 agenda possible.”  

Learn more about how TCS and Microsoft are powering the sustainable enterprise.  

Financial Services Industry, Green IT

Multi-cloud environments offer significant business benefits from increasing agility to improving efficiency. The challenge, however, is that each cloud sits in an isolated silo with its own development and operating model, taxonomy, services, APIs and management tools. This lack of consistency across clouds forces companies to manage their multi-cloud environments through a patchwork of off-the-shelf, custom-built and native cloud service provider tools, which often require specialized developer and operator teams and skill sets to use. The lack of consistency across clouds also increases security risks.

Early on, VMware recognized the need to unify cloud environments. That’s why we created VMware Cross-Cloud services, our portfolio of services for application development, cloud management, cloud and edge infrastructure, security and networking, and Anywhere Workspace solutions. These services are built on a seamless abstraction layer that spans clouds, enabling organizations to build, deploy, run, manage, secure and access apps and infrastructure in a consistent way.

Understanding Multi-Cloud Services

VMware and other software vendors have seen the same industry challenges of multi-cloud environments, and in response have released services to address various aspects of these challenges. For instance, earlier this year VMware CTO Kit Colbert discussed this very issue with the head of strategic partnerships at Snowflake, which is tackling the issue of managing data in a multi-cloud environment.

Multi-cloud services is our proposed nomenclature to address comprehensive multi-cloud challenges. As we define it, a multi-cloud service provides a consistent API, object model, identity management and other core functions across clouds, and it runs in one or more of the following scenarios: 

On a single cloud but supports interactions with at least two different clouds.On multiple clouds and supports interactions with at least two different clouds.On any cloud or edge, even in disconnected mode, and basic operations are fully automated.

VMware sees five categories of multi-cloud services: application services, infrastructure services, security services, end-user services and data plane services. These are broad categories, and over time we expect that our industry, collectively, will define more granular service categories as well as entirely new services.  


In the multi-cloud services model, data centers, private clouds, public clouds and edge locations are verticals, and multi-cloud services are horizontals, providing functionality across these locations. These horizontal capabilities integrate with and complement the native services of each cloud while providing the consistency and standardization that development, operations and security teams need.

Benefits of Multi-Cloud Services

Organizations can use multi-cloud services to abstract and standardize cloud infrastructure and operations, development and security capabilities into one platform to reduce or eliminate the complexity of individually building or consuming the equivalent native services from multiple clouds. Some of the benefits include:

The business can realize quicker time to market and quantifiable improvements in app performance, efficiency and security. Operators can deploy, manage and monitor apps and container infrastructure in the same way for every cloud. This can minimize the need for specialized teams and skill sets when working with specific clouds.Developers can write apps using their preferred framework without worrying about the infrastructure or the cloud on which it runs.Security teams can apply policies consistently to every cloud and app. Companies in regulated industries can meet their unique sovereign cloud requirements and maintain jurisdictional control while achieving cutting-edge transformation at scale.

Learn More About Multi-Cloud Services

For a deeper dive into multi-cloud services, read VMWare’s white paper.For additional information please click here.


Accenture on Tuesday said that it was acquiring Flutura, an internet of things (IoT) and data science services firm, for an undisclosed sum to boost the industrial AI services that it sells under the umbrella of Applied Intelligence.

The acquisition assumes significance as the Asia-Pacific region constitutes 70% of Accenture’s Applied Intelligence market, according to Gartner. EMEA, North America and Latin America account for 15%, 10% and 5% of the softwares sales, respectively.

“Flutura’s acquisition will power industrial AI-led transformation for our clients globally and particularly in Australia, South-East Asia, Japan, Africa, India, Latin America and the Middle East,” Senthil Ramani, senior managing director at Accenture, said in a press note.

Accenture also leads the industrial AI services market followed by Deloitte, according to a Gartner analysis conducted in 2022. The market research firm, which clubs these services as data and analytics (D&A) services, expects its market to reach $232 billion globally by the end of 2024.

As part of its Applied Intelligence services, Accenture offers data-led transformation services along with AI-based solutions that it brands as Solutions.AI. Other services include consulting and ensuring deployment of responsible AI solutions.

Accenture plans to bring Flutura’s capabilities to clients in the energy, chemicals, metals, mining, and pharmaceutical industries, the companies said in a joint statement.

“Flutura democratizes AI for engineers, enabling manufacturing and other asset-intensive companies with the carbon intelligence to reduce emissions, energy consumption and lost output due to unplanned downtime of industrial assets, said Ramani.

Flutura’s capabilities includes AI platform Cerebra that supports self-service analytics from disparate IT systems or data sources, solutions for process, asset management and energy efficiency.

Flutura also offers connected assets, connected processes, Vision Intelligence, Engineer’s Workbench as its core product offerings.

Bengaluru-based Flutura, which was incorporated in 2012, was founded by Derick Jose, Krishnan Raman, and Srikanth Muralidhara. The company, which has raised $8.5 million in investment, was part of Microsoft Accelerator in Bengaluru. Its lead investors include HPE Digital Catalyst program, Vertex Ventures, Hitachi High-Technologies and Lumis Partners.

Artificial Intelligence, Internet of Things, IoT Platforms

OpenAI has landed billions of dollars more funding from Microsoft to continue its development of generative artificial intelligence tools such as Dall-E 2 and ChatGPT. A move that is likely to unlock similar investments from competitors — Google in particular — and open the way for new or improved software tools for enterprises large and small.

Microsoft stands to benefit from its investment in three ways. As a licensee of OpenAI’s software it will have access to new AI-based capabilities it can resell or build into its products. As OpenAI’s exclusive cloud provider it will see additional revenue for its Azure services, as one of OpenAI’s biggest costs is providing the computing capacity to train and run its AI models. And as an investor it can expect some return on its capital, although this will be limited by OpenAI’s status as a capped-profit company governed by a nonprofit.

The deal, announced by OpenAI and Microsoft on Jan. 23, 2023, is likely to shake up the market for AI-based enterprise services, said Rajesh Kandaswamy, distinguished analyst and fellow at Gartner: “It provides additional impetus for Google to relook at its roadmap. It’s the same for other competitors like AWS,” he said.

Ritu Jyoti, IDC’s global AI research lead, sees more than just AI bragging rights at stake here. “There is a big battle brewing between the three hyperscalers — Amazon, Google, and Microsoft — and it’s not just about AI. It’s going to drive who’s going to be supreme in the cloud because this requires tons and tons of compute, and they’re all fighting with each other. It’s going to get ugly,” she said.

Employees are already experiencing some of that ugly: Since the start of the year, Microsoft, Amazon, and Google parent Alphabet have all announced massive layoffs as they seek to refocus on growth markets and invest in AI.

Billion-dollar brain

Rumors that Microsoft could invest as much as $10 billion to grow its AI business broke in early January. The company has been a supporter of OpenAI’s quest to build an artificial general intelligence since its early days, beginning with its hosting of OpenAI experiments on specialized Azure servers in 2016. In July 2019 it became OpenAI’s exclusive cloud provider and invested $1 billion in the company to support its quest to create “artificial general intelligence.” In 2020, Microsoft became the first to license OpenAI’s Generative Pre-trained Transformer (GPT) AI software for inclusion in its own products and services. Up to that point, OpenAI had only allowed enterprises and academics access to the software through a limited API.

Enterprises already have access to some of that technology via Microsoft’s Azure OpenAI service, which offers pay-as-you-go API access to OpenAI tools, including the text generator GPT 3, the image generator Dall-E 2, and Codex, a specialized version of GPT that can translate between natural language and a programming language. Microsoft is also offering Codex as a service in the form of GitHub Copilot, an AI-based pair programming tool that can generate code fragments from natural language prompts. And it will soon offer Microsoft 365 subscribers a new application combining features of PowerPoint with OpenAI’s Dall-E 2 image generator. That app, Microsoft Designer, is currently in closed beta test. And, of course, they can check out ChatGPT, the interactive text generator that has been making waves since its release in November 2022.

GPT-3.5, the OpenAI model on which ChatGPT is based, is an example of a transformer, a deep learning technique developed by Google in 2017 to tackle problems in natural language processing. Others include BERT and PaLM from Google; and MT-NLG, which was co-developed by Microsoft and Nvidia.

Transformers improve on the previous generation of deep learning technology, recurrent neural networks, in their ability to process entire texts simultaneously rather than treating them sequentially, one word after another. This allows them to infer connections between words several sentences apart, something that’s especially useful when interacting with humans who use pronouns to save time. ChatGPT is one of the first to be made available as an interactive tool rather than through an API.

Robots in disguise

The text ChatGPT generates reads like a rather pedantic and not always well-informed human, and part of the concern about it is that it could be used to fill the internet with human-sounding but misleading or meaningless text. The risk there — aside from making the internet useless to humans — is that it will pollute the very resource needed to train better AIs.

Conversing with ChatGPT is entertaining, but the beta version available today is not terribly useful for enterprise purposes. That’s because it has no access to new information or services on the Internet — the dataset on which it was trained was frozen in September 2021 — and although it can answer questions about the content of that dataset, it cannot reference its sources, raising doubts about the accuracy of its statements. To its credit, it regularly and repeatedly reminds users of these limitations.

An enterprise version of ChatGPT, though, refined to cope with an industry-specific vocabulary and with access to up-to-date information from the ERP on product availability, say, or the latest updates to the company’s code repository, would be quite something.

In its own words

ChatGPT itself, prompted with the question, “What uses would a CIO have for a system like ChatGPT?” suggested it might be used for automating customer service and support; analyzing data to generate reports; and generating suggestions and recommendations based on data analysis to assist with decision-making.

Prompted to describe its limitations, ChatGPT said, “Its performance can be affected by the quality and quantity of the training data. Additionally, it may not always be able to understand or respond to certain inputs correctly.” Nicely illustrating its tendency to restate the same point in multiple ways, it went on: “It is also important to monitor the performance of the model and adjust the training data as needed to improve its accuracy and relevance.”

As for Microsoft’s plans for OpenAI’s generative AI tools, IDC’s Jyoti said she expects some of the most visible changes will come on the desktop. “Microsoft will completely transform its whole suite of applications: Word, Outlook, and PowerPoint,” she said, noting that the integration of OpenAI could introduce or enhance features such as image captioning, and text autocompletion and the recommendation of next actions.

Gartner’s Kandaswamy said that he expects Microsoft, in addition to updating its productivity suite, to add new OpenAI-based capabilities to Dynamics and even properties such as LinkedIn or GitHub.

It’s important for CIOs to adopt these tools for the incremental value that they bring, he said, but warned: “Be very careful not to get blindsided by the disruption AI can produce over the longer term.”

Chief AI officers

Jyoti pinned some of the responsibility for AI’s effects on enterprises themselves. “People always tend to blame the technology suppliers, but the enterprises also have a responsibility,” she said. “Businesses, right from the C-suite, need to put together their AI strategy and put the right guardrails in place.”

For now, AI tools like ChatGPT or Dall-E 2 are best used to augment human creativity or decision-making, not replace it. “Put a human in the loop,” she advised.

It won’t be the CIO’s decision alone because the questions around which tools should be used, and how, are ethical as well as technical. Ultimately, though, the job will come back to the IT department. “They cannot ignore it: They have to pilot it,” she said.

Build, don’t buy

With few generative AI tools available to buy off the shelf for now, there will be a rebalancing of the build vs. buy equation, with forward-thinking CIOs driven to build in the short term, Jyoti said. Limited developer resources could achieve that sooner with coding help from tools like GitHub Copilot or OpenAI’s Codex.

Later, as ISVs move in and build domain-specific solutions using generative AI tools provided by OpenAI, Microsoft, and the other hyperscalers, then the pendulum may swing back to buy for enterprises, she said.

That initial swing to customization (rather than configuration) could spell big trouble for Oracle, SAP, and other big ERP developers, which these days rely on making enterprises conform to the best practices they embody in their SaaS applications.

“They have hardened the processes over so many years, but today AI has become data-driven,” Jyoti said: While the ERP vendors have been embedding AI here and there, “They’re not as dynamic […] and this will require a fundamental shift in how things can work.”

Artificial Intelligence, Chatbots, Microsoft, Technology Industry

To create innovative products that meet the various finance requirements of the market, Piramal Capital & Housing Finance opened the Piramal Innovation Lab in Bengaluru on Dec. 15, 2022. The 36,000-square-foot innovation hub will be led by the company’s CTO, Saurabh Mittal, and Markandey Upadhyay, head of business intelligence unit for Piramal.

CIO.com caught up with Mittal to know more about his plans for the innovation lab, as well as the technology strategy for the financial services company.

CIO.com: What solutions will come up at the innovation lab and which technologies would you be leveraging for developing them?

Mittal: As a company, we have taken a ‘tech first’ approach, which reflects in the thinking, functions, and business processes across the organization. Our philosophy is to identify problems or opportunities, size them, and build technology solutions to address them. Sometimes we will see success, sometimes we will require a few iterations, but that’s the approach that we will pursue. The purpose of this innovation lab, therefore, will be to identify problems and create solutions for them.

Some of the key problems that we are working on include creating an underwriting solution for our customers in tier 2 and 3 cities. Unlike salaried people in tier 1 cities, most people in smaller cities may be self-employed and engaged in small businesses. An underwriting infrastructure will allow us to leverage information, available across these wide sets of customers, by feeding it into certain projection models that will enable us to take credit decisions at scale.

There still isn’t a place in the industry where you can get a home loan in minutes. So, we are working on reducing turn-around times for our home loan customers, and instant decisions and disbursements for our unsecured loan customers.

Another interesting area we are focusing on is that of bank statement analysis. We receive all kinds of bank statements in various formats but there isn’t a single solution in the industry that can help derive the income of the customer.

To develop these products, we will heavily use data, artificial intelligence, and machine learning. Through the new state-of the-art innovation centre, we intend to attract skilled resources in the areas of product management, data sciences, user experience, and software engineering. The company aims to build a team of more than 300 technology professionals by the end of FY23.

But for a relatively new entrant in the market, it is also important to leverage technology and quickly create a competitive differentiator for the company. How have you done that?

We are just about two years old and are catching up with the best in certain areas. However, at the same time, there are a whole lot of areas where we are ahead of others. For instance, we had a paper-based process to sign up DSAs [direct sales agents], go in the field and source business for us. The process, which was long and frustrating, took seven days to onboard a channel partner. We reimagined that process and converted it to a completely digital journey. Now DSAs get signed up in an average of 12 minutes. I’m told that’s an industry first.

Then we’ve got embedded finance partners. Think of them as various kinds of consumer tech or fintech companies, who want to give loans in partnership with us, seeking access to our customers. To enable this, we have turned to APIs. The API stack at the back end enables customers to interact with the lenders. The Embedded Finance business has allowed us to get 22 of our partners to launch over 24 programs in collaboration with leading digital consumers and merchant engagement platforms. The fastest that we’ve gone live with a partner has been about four weeks, which is also an industry-first capability. We are far ahead in our API thinking.

Our credit managers meet potential customers and ask various questions as part of a personal discussion. Based upon the outcome of this personal discussion, the credit manager takes a decision whether the customer should be extended a loan or not. We have embedded intelligence into this process of personal discussion. As the credit manager asks questions, he gets feedback because of the dynamic scoring happening at the back end. Based on the scoring happening in real-time, the credit manager can pause and reject or approve a customer. I don’t think that such a personal discussion tool has been developed by any other player yet.

I think we got a bit lucky as being a young company we didn’t have a whole lot of legacy systems to deal with other than what we got from the DHFL acquisition. When we acquired DHFL, we had an on-prem data center that has been migrated to the cloud.

These solutions and the others in the pipeline will add to the company’s top line. How are you boosting the bottom line through technology?

Let me illustrate this with the example of collections. Collections could happen purely in an offline manner. To drive efficiencies in this area, we have built an intelligent app called Collection Central. Through AI and ML models, the app tells us that a particular customer will pay if you send a message to him or her or need to make a phone call or a field visit to a certain customer. This ensures we’re not making a field visit for every customer. Such solutions, supported by intelligence powered by the data, drive efficiencies. It’ll be hard for me to say whether we collect more because of such solutions but I can confidently say that we collect faster and with lesser cost because of them.

Blockchain holds promise for financial service companies as it can lead to cheaper and faster transactions, enhanced security, and automated contracts. How are you maximizing it for Piramal?

Mittal: We don’t have active investments in blockchain yet. One of the areas where blockchain can play a vital role is that of a property registrar. It’s hard work to identify the genuineness of property documents and then tracing its legacy all the way from the first buyer till now. Building an industry-neutral property registration platform, enabled by blockchain, that gives us assurance that the property title is valid is crucial but use cases like these would be more of industry-wide opportunities. Some of these, therefore, would have to be taken up within the Digital Lenders Association or other forums where you must garner support from other players.

Most financial services companies have data siloed in multiple business units. How do you ensure that data is democratized to deliver personalized CX?

We have a single multi-product platform that internally branches out into different flows depending on what product in being used. We have a single app that all business units use for all the products, but it plays out differently depending on which product they are starting the journey for.

We have ensured that all our data is generated and stored in a single place in a manner such that anybody can consume and use it. Every single piece of data from the platform flows into a data warehouse that provides accessibility of data to whoever needs it, either for a report or for visualization analytical needs or for building projection and machine learning models on top of that.

We have mandated that any new microservices or applications will not be put into production if they are not pushing the required data elements into the data warehouse. To facilitate this, we have created a ‘push case architecture’ that allows any new application to push data to the data warehouse directly, making it very easy for developers and application owners to do so.

As a CTO, what are some of the biggest challenges that you face?

Mittal: The biggest challenge has been hiring the kind of talent we would like to have. About a year and a half back, we didn’t have a single software development engineer in the company. We started by defining the job description, roles, responsibilities, and attracting talent. We had our success in the last year and a half, but the innovation lab will now accelerate it.

The other big challenge relates to constraints that we face while working with third-party systems. We have cloud native and have designed everything keeping cloud in mind. For instance, from day one, we use serverless computing and cloud-managed databases. Besides the benefits of on-demand provisioning, elasticity, and deep observability, it helps us to focus on the core business.

However, third-party systems may not have been designed for the cloud, which creates bottlenecks for our strategy and operations. We keep thinking how we can bring in the cloud native thinking there to improve the setup.

Going forward, what will be the top business and technology trends in this industry?

Mittal: In the lending world, account aggregator is one thing that is likely to see exponential growth next year. It is especially relevant for the large segment of customers we serve, who are new to credit base. We don’t have a civil record for such customers and need to have their reliable bank statements. So, account aggregator to get authenticated, verified, and reliable bank statements with very low friction is the need of the hour. The push from various regulators is already there, and on this account, we strongly believe that account aggregator will be a major thing next year in the lending world.

The other technology that will go to a different orbit altogether is machine learning. While all lenders build ML models based on internal and industry data, the mind is opening to newer possibilities. With ChatGPT, DALL.E, and other innovations around us, there is a completely different set of opportunities emerging and unthinkable experiences can be offered to customers and internal users using machine learning.

Digital Transformation

As part of its ongoing strategy to expand its roster of public cloud regions and catch up with larger cloud service providers such as AWS, Microsoft and Google, Oracle has launched a new cloud region in Chicago to cater to enterprises operating out of the US Midwest.

The Chicago region, which will be Oracle’s fourth public cloud region in the US and 41st globally, will primarily cater to manufacturing and financial services firms among other industries operating in that part of the country, said Leo Leung, vice president of products and strategy at Oracle.  

The Midwest region, according to Oracle, is home to more than 60% of all US manufacturing firms and houses the world’s largest financial derivatives exchange.

“This is just going to give them (enterprise customers in the region) the capability of running their workloads closer to their headquarters versus other parts of the country,” Leung said, adding that the demand in the region is fueling the company’s growing bookings for Oracle Cloud Infrastructure (OCI).

CEO Safra Catz, during an earnings call for its quarter ended November, had said that the company had triple-digit bookings growth across its infrastructure-as-a-service (IaaS) services for the past two quarters and basis this growth, the company planned to invest $2.4 billion approximately every quarter for the next few quarters.

The new region in Chicago will offer over 100 OCI services and applications, including Oracle Autonomous Database, MySQL Heatwave, OCI Data Science, Oracle Container Engine for Kubernetes, and Oracle Analytics, the company said.  

Oracle has three other regions in the US, situated in Ashburn, Virginia; San Jose, California; and Phoenix, Arizona.

Globally, the company has a total of 55 cloud regions including national security regions.

Nine new regions are currently being built, Catz had said during the earnings call, according to a transcript from Motley Fool.

For the quarter ended November, the company’s total revenue grew 25% in constant currency, buoyed by revenue growth from its infrastructure and applications cloud businesses, which grew 59% and 45% respectively, in constant currency.

Cloud Computing, Finance and Accounting Systems, Manufacturing Industry, Technology Industry

No matter how reliable their sources, IT analysts’ technology adoption forecasts are fundamentally interpretive – opinions based on received data. This is particularly true when predicting deployment trends in tomorrow’s cloud market.

Predictive viewpoints from cloud service providers, meanwhile, are informed by direct interactions with client IT teams experienced in projecting their organizations’ technology needs.

“Predicting cloud requirements is now a core competency for IT strategists,” says Oscar Garcia, Global SVP of Strategy and Technology at NTT. Garcia’s role makes him well placed to cast perspective on cloud trends for 2023 – notably, upshifts in the areas of cloud verticalization, hyperscale edge computing, SaaS management and cloud sustainability.

First of these, the rise of cloud platforms pre-engineered for an industry or sector, reflects the continued adoption of multicloud in high-value organizations.

“When organizations want ‘horizontal’ clouds tailored for a business industry, reengineering is needed to prep the cloud for that industry’s requirements, such as foundational services and compliances,” Garcia explains. “This results in duplicated effort.”

Increasingly, organizations want clouds preconfigured for necessary compliances, says Garcia: “Clouds that come with sector-specific features don’t have to be set up from scratch each time, thus streamlining cloud onboarding. They save time and money, and have inbuilt continuity with a given industry’s standards.”

Hyperscale edge computing gains traction

Cloud trends are rarely attributable to one driving force. Take demand for managed hyperscale edge computing services, which Garcia tips for estimable growth.

“Across sectors, enterprises increasingly look to distribute their workloads,” Garcia reports. “This is resulting in a need for distributed compute and storage that bring instantaneous response times at the edge.”

Associated benefits include the reduction of data processed in centralized clouds. This avoids network latency and other operational overheads. It also improves data security by limiting its exposure across networks.

Edge as a Service options make it possible to implement networks, operations and edge computing that deliver real-time automation and processing,” adds Garcia. “Unified operating models simplify operations and allow IT chiefs to focus on business imperatives.”

SaaS management services demand

The number of businesses that have outsourced the management of their applications is on an upward trend that will steepen through 2023.

“The need for SaaS management is the result of enterprises moving workloads to SaaS applications and the emergence of new complexities associated with this delivery model,” Garcia says. “SaaS solutions are precisely charged for. When cost leakage due to ineffectively managed SaaS solutions is revealed, it can come as a shock.”

Another reason why more organizations are outsourcing their top-level application monitoring and management is to free-up their IT expertise to focus on tech-enabled business initiatives, Garcia adds.

Measurable cloud sustainability

A desire for improved cloud sustainability will form another 2023 trend.

“While moving to cloud might not automatically make an organization’s IT greener, cloud can create conditions that make transformation possible,” says Garcia. “This means transforming IT to be more environmentally high-performing, but also transforming business through IT, using IT to drive positive change in the organization.”

NTT works toward delivering a “sustainability budget” that quantifies sustainability in the form of values rather than direct costs.

“When we propose operational right-sizing for altering CPU usage scale-out, or projected requirements for storage, or other compute parameters, we scale the budgetary expenditure of a potential change to a sustainability impact,” Garcia explains.

IT decision-makers may not always recognize sustainability metrics presented as quantitative methodology benchmarks, but they will respond to financial indicators, adds Garcia: “They can say, ‘well, this isn’t the least costly option, but it delivers the best sustainability outcome’. They can then apply a ROI value. So, if it’s 10 percent more expensive, say, that 10 percent will be an investment in improving their organization’s sustainability posture.”

How Multicloud as a Service can help

Even the best-run cloud environments can prove complex, and multiple clouds bring multiple complexities. A Business Impact Brief from 451 Research found this complexity is driving organizations to service providers to implement effective multicloud management.

No service provider is better qualified to meet this requirement than NTT. Their multicloud solutions address those complexities from infrastructure to edge. It’s still cloud as you know it, but simplified, more connected, and delivered as a managed service.

Discover how Multicloud as a Service from NTT can enable you to get more from your strategic cloud investments.

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