MOFF-EN questions - Microsoft Operations Framework Foundation Updated: 2024

Formerly known as Microsoft Operations Manager v3, System Center Operations Manager 2007 provides end-to-end event, service and application monitoring and reporting.

The platform supports Service Model Language (SML) for monitoring IT and software services -- required for service-level agreements -- and features audit collection services for compliance auditing and a customizable reporting tool.

At the Microsoft Management Summit, which started Tuesday in San Diego, the Redmond, Wash., software giant also announced a technology licensing agreement with EMC that will bolster the network management capabilities of System Center Operations Manager 2007. As part of the deal, Microsoft said it will integrate EMC's Smarts network discovery and health monitoring software into a future version of Operations Manager.

In addition, Microsoft, EMC and Cisco unveiled a pact to develop a set of network common models that exploit the SML to simplify network management. As part of the arrangement, the companies have submitted SML -- which is based on Microsoft's System Definition (SDM) Model -- for adoption as a standard to the W3C. That would allow partners and customers to manage software and hardware, as well as Windows systems, on the System Center platform.

Operations Manager 2007 is just one of several System Center products Microsoft is preparing for release this year.

System Center Configuration Manager 2007, formerly referred to as Systems Management Server v4, is scheduled to ship this summer. To add more value to the software configuration and deployment platform, Microsoft plans to roll out an add-on for Configuration Manager 2007 after it ships that will support Intel's next-generation vPro client management technology, code-named Weybridge, which is also due for a midyear release.

Microsoft also highlighted its progress in virtualization, backup and service management.

System Center Virtual Manager, formerly code-named Carmine, will move into Beta 2 testing in the next 45 days, the company said. And the second version of System Center Data Protection Manager -- which will provide backup and recovery for SharePoint 2007, Virtual Server 2005, Windows XP and Windows Vista -- will move into Beta 2 testing in the next 30 days.

Microsoft also announced System Center Service Manager, the formal name of its former Service Desk offering, and said plans to release the first beta in the next 30 days.

In addition, Microsoft announced an update for partners and customers awaiting Systems Management Server Service Pack 3. SMS Service Pack 3 with AssetMetrix software asset-management capabilities will be released to manufacturing this spring, the company said.

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At its worldwide partner conference last month, Microsoft unveiled System Center Remote Operations Manager 2007, a solution that uses Microsoft Operations Manager 2007 (MOM) to provide remote managed services to midmarket and SMB customers that have a System Center Essentials 2007 server installed at their premises.

Remote Operations Manager licensing is available only through Microsoft's Service Provider License Agreement (SPLA). Monthly recurring costs for each server managed are $13.85 per month, or $166 per year, and each client managed is priced at 55 cents per month.

For System Center Essentials, which the VAR can either purchase or resell directly to the end user, the price tag is $2,000 plus Software Assurance, which covers 10 servers and 50 clients, with additional servers priced at $100 for a perpetual license.

One Microsoft Gold partner said the fact that many SMB customers have multiple sites could make Microsoft's MSP offering prohibitively expensive.

"Over a five year lifecycle, the upfront cost of System Center Essentials may not be a big deal, but Microsoft is forgetting that many partners end up ditching whatever platform they're on every few years, which means first year expenses are very important to profitability," said the source, who requested anonymity.

In contrast, MSP Zenith Infotech's model of $10 per server per month includes an antivirus license, and for $37 per month, Zenith will actually resolve any server issues that come up, the source said.

But John Joyner, senior architect at ClearPointe Technology, a Microsoft partner in Little Rock, Ark., and an early tester of System Center Remote Operations Manager 2007, says the pricing isn't unreasonable in light of the capabilities it offers to partners.

For example, Remote Web Workplace, software that's installed at the customer's location, gives service providers the ability to remotely control customers PCs without requiring a VPN or direct connection to the customer's network, said Joyner.

"We feel the software is priced fairly. Our current customers that are paying for a seat in a MOM infrastructure are going to pay about the same, or even a little less, with System Center Remote Operations Manager 2007," Joyner said.

System Center Remote Operations Manager 2007 is part of Microsoft's push to bring technologies that were previously available only to enterprises down to small and midmarket customers, said Jeff Campbell, director of product management at Microsoft.

As such, Microsoft will continue to look at the pricing model as it relates to the lower end of the market, Campbell said.

"The monthly cost of $13.85 for ROM is [priced] right. The System Center Essentials pricing, as you scale down to smaller clients, starts to get a little bit out of whack, and that's definitely something we are looking at internally," said Campbell.

Stephen Moss, COO of NSPI, a security solution provider in Roswell, Ga., is excited that Microsoft is stepping up with an MSP tool for partners, but said the strategy needs more refinement.

"The problem is, they haven't developed a plan for how to come after service providers, because this is a different type of sale than just a license sale," he said. "For solution providers trying to make margin, Microsoft will have to find the right pricing model."

System Center Remote Operations Manager 2007 was released to manufacturing in July and will be generally available this fall.

Detailed information on System Center Remote Operations Manager 2007 has been scarce, available only on a cryptically titled and sporadically updated TechNet blog titled "Remote Managed Services", run by Dustin Jones, program manager at Microsoft.

We’ve moved beyond the hype—generative AI works, and the telecommunications industry is feeling its true impact. Microsoft recently commissioned a study which showed that for every United States dollar that a company invests in AI, it realizes an average return of USD3.50. We just launched a special Work Trend Index report that showed a massive increase in employee productivity; it also showed that 77% of Microsoft Copilot users said that once they used Copilot, they didn’t want to provide it up. Those are real benefits that telcos are seeing today, and they are eager to explore what’s next—how can they do more with generative AI and their data investments, their intelligent applications, and their businesses?

The big impact of generative AI

Discussions about the potential of generative AI on the telco industry are everywhere. “IDC is projecting that generative AI will add nearly USD10 trillion to global GDP over the next 10 years.”¹ Other analysts are projecting telco productivity increases in the billions for customer service, marketing, sales, app development, network insights, and operations. At Microsoft, we’ve already seen the benefits of generative AI across the company. The Microsoft global customer support team streamlined operational efficiency while delivering exceptional customer satisfaction with Copilot in Dynamics 365 Customer Service. There was a 31% increase in first call resolution and a 12% increase in customer satisfaction. Learn more about modernizing your customer service experience with Microsoft Dynamics 365 Customer Service. The Microsoft Customer and Partner Solutions organization used Microsoft Copilot for Sales to simplify workflows and help its sellers more efficiently build relationships with clients.

What does generative AI do for telco?

Generative AI empowers telco to work with vast amounts of data, identify patterns, and generate novel solutions, promising to transform traditional practices and foster industry-wide innovations. By embracing generative AI, telco companies can overcome challenges, unlock new revenue streams, Boost operational efficiency, and deliver exceptional customer experiences. It’s a key ingredient in accelerating the transformation from telco to techco. And with so many potential applications for generative AI, it’s important to identify what has worked so far. To provide some inspiration, here are a few success stories that show us generative AI’s potential to transform the industry and drive substantial value.

Elevating customer experiences

Indonesian telco company Telkomsel introduced Veronika—a virtual assistant that integrates Microsoft Azure OpenAI Service. Veronika is rooted in natural language processing and machine learning, and according to Vice President of Customer Journey and Digital Experience at Telkomsel, Danang Andrainto, “Veronika continues to innovate by integrating the best AI technology to infuse intelligence into its functions, resulting in the delivery of solutions that are progressively more accurate.” Veronika recommends telco packages based on customers’ needs, and it can quickly and accurately address customer concerns. Here’s more of the story of Veronika and how generative AI is making it better.

And Veronika isn’t the only one. Bots are becoming more popular and effective in providing a digital-first customer experience. They can handle complex queries, Boost customer engagement, and reduce operational costs. They can reduce the average handling time and save millions of dollars per month. These bots can help customers with various tasks, such as checking balances, paying bills, troubleshooting issues, and finding the best deals. They can build personalized scripts for next-best offers based on real-time data and insights. They can enhance end-to-end call center engagements from customer inquiry summarization, providing real-time information to resolve questions for sales agents, to analyze live sentiment, and to suggest personalized scripts for next-best offers; and they can create post-call analyses on agent performances. They can also create customer-sentiment analysis to help monitor and Boost customer experiences across multiple touchpoints. Bots are transforming customer care strategies for many businesses around the world.

Bots are helping employees too. South African telco group MTN launched SiYa—an employee bot that can assist workers with inquiries, information on company policies, and employee-to-company interactions. And ultimately, MTN hopes SiYa can help customers with purchases, advice, and service. “By harnessing the power of AI and APIs, we are not only future-proofing our operations but ensuring that our customers, both internal and external, can look forward to a more streamlined, efficient, and data-driven experience,” MTN South Africa CEO Charles Molapisi says.

Aimee is BT Group’s new digital assistant. Kevin Lee, Chief Digital Officer for Consumer Division of BT Group, says, “Our pilots with generative AI with Microsoft are designed to see if we can more rapidly make Aimee the most personal, customer-focused, intelligent digital assistant delivering value through every interaction.” But Lee says he doesn’t want Aimee to replace human-to-human interactions; he wants Aimee to help customers meet their needs more efficiently and accurately. Aimee is meant to be a support, and her role is unlimited.

Accelerate network operation

If we look to the technical side of things, generative AI can Boost network operations for operators too. Three UK leveraged Azure Operator Insights by creating and optimizing network configurations, policies, and parameters based on the data collected from the network performance, traffic, and user behavior. Generative AI can learn from the existing network settings and generate new ones that can enhance the network’s efficiency, reliability, and security. For example, generative AI could help design and deploy optimal network slices for different use cases and customers or adjust the network parameters to cope with changing demand and conditions. Generative AI can also help to automate network management tasks like fault detection, diagnosis, and resolution by generating and executing appropriate actions based on the network state and the desired outcomes. It can use natural language processing and generation to enable more human-like interactions between network operators and the network systems, using voice commands to control the network functions or receiving natural language explanations of the network status and its issues. Generative AI applications for network operation include:

• Generative AI can be used to optimize Radio Access Network Configuration Optimization parameters based on the network performance data and the operators.
• Generative AI can generate and execute network policies, configurations, and actions based on the network data and the operator’s goals.

Organizations can be more efficient

Generative AI can help make knowledge management more efficient with the ability to increase the productivity of HR, finance, legal, and customer service departments. By using bots, organizations can provide faster and more accurate answers to their employees and customers. For example, Finland’s largest telco and tech company, Elisa, has used Microsoft Copilot for Microsoft 365, which helps knowledge workers with various tasks, such as finding documents, scheduling meetings, and creating reports. Katja Bäckström, Elisa’s Senior Vice President, Customer Service and Customer Service with Copilot, says, “With Copilot, traditional data entry is eliminated, and customer data can be accessed directly from customer discussions. Copilot can easily be asked about the latest actions with the customer and a proposal for creating the next agenda. In the end, Copilot improves both the employee experience and the customer experience.”

Multinational tech and telco company Lumen uses Copilot. Lumen’s customer service teams surface relevant policies with Copilot, they summarize tickets, and they easily find repair instructions from manuals. They can quickly create presentations, new business proposals, and statements of work. “Our people are seeing immediate productivity improvements with Copilot, allowing them to focus on more value-added activities each day,” Kate Johnson, president and CEO of Lumen Technologies, Inc. says.

Marketing and sales benefit from generative AI

But can generative AI help your marketing and sales departments?

Generative AI can help create appealing and customized content for different audiences and channels, such as blog posts, social media posts, landing pages, email campaigns, and more. For example, a telco operator could use generative AI to create titles, summaries, keywords, or captions for their online content based on the target audience’s interests and actions. 

Generative AI can also help classify and segment customers based on their attributes, desires, preferences, and actions, using data from various sources, like web analytics, customer relationship management platforms, or social media. A telco operator could use generative AI to group their customers into different profiles, for example, such as the innovators, the loyalists, and the value seekers. They could then adjust their messages and offers accordingly. 

Generative AI can help recommend appropriate and personalized products or services to customers based on factors such as their previous purchases, web history, and feedback. For example, a telco operator could use generative AI to suggest the best bundle, plan, or add-on for each customer, based on their budget, needs, and usage patterns. 

Generative AI can help create interested and qualified leads for the sales team by finding and contacting potential customers who match the ideal customer profile, using data from various sources like third-party databases, social media, or web analytics. For example, a telco operator could use generative AI to create leads for their business solutions by identifying and reaching out to prospects who are searching for similar services, have high intent, and meet the criteria of decision makers.

Amdocs, in partnership with Microsoft, launched a unified Customer Engagement Platform, leveraging the power of generative AI. Integrated with Microsoft Dynamics 365, it is an all-encompassing AI-powered marketing, sales, commerce, and customer service platform serving consumer and enterprise customers on a single, open, telco, and cloud-native platform.

Developer productivity

With GitHub Copilot for Business, 46% of new code is now written by AI, and developer productivity has increased by over 55%. AT&T uses Azure OpenAI Service in a few ways. It moves legacy code into modern code using generative AI, which helps the developers focus on creating modern tools and experiences for workers and customers. AT&T employees can ask generative AI questions about their insurance plans or getting hardware for a new employee. And AI helps with storage problems or computer issues company wide. Read more about AT&T’s developers and generative AI.

GitHub Copilot simplifies the creation and consumption of TM Forum Open APIs by generating the required code that complies to the API guidelines in the development language of your choice.

Accelerate your own generative AI journey with Microsoft

Partner with Azure OpenAI Service to transform your telco organization with AI-driven solutions for enhanced operations, innovative services, and exceptional customer experiences. The service offers many opportunities to explore AI-driven solutions for your organization. We hope to see you at Mobile World Congress 2024 as well. We’ll be there talking about how AI is accelerating the telco industry’s transformation.

About the study
The IDC study, commissioned by Microsoft, is based on results from 2,109 enterprise organizations totaling more than 13 million employees worldwide across 16 countries globally. Through the questionnaire, respondents were identified as the decision maker for AI within their organization.   

¹Official Microsoft Blog, New study validates the business value and opportunity of AI, November 2023. 

Government regulators will be tasked in 2024 with pursuing definitive answers to questions posed by powerful generative artificial intelligence technology, including a pair of issues that could dictate the next phase of AI adoption and the intellectual property they use and produce.

Namely: Will the likes of US-based OpenAI Inc. and UK-based Stability AI Ltd. require licenses to train their models on copyrighted material? And will the outputs of these models receive their own copyright protections?

The answers will shape the technology industry’s investment priorities in the booming global AI market, and help to determine where creative industries, such as film and graphic design, put their new offices to protect their IP. So far, the global spectrum of answers is expansive and includes ongoing copyright litigation and explicit legislative solutions.

One matter is clear though: The AI industry is keenly awaiting formal regulations to establish guardrails. Perhaps none have been as explicit in tying regulation to progress as Microsoft Corp., which told the US Copyright Office that there will be no next phase of AI without regulations.

“Countries that provide the greatest clarity to support AI development will enable the greatest adoption of responsible AI technology,” Burton Davis, Microsoft’s Deputy General Counsel for IP wrote to the Copyright Office in October. “Without clarity, no company will be able to confidently develop AI systems.”

The comment was in response to the US office’s ongoing rulemaking and plan to release a study in the first half of 2024 examining the relationship between copyright law and AI.

Here is a look at the current state of where regulators around the world stand on the intersection of AI and intellectual property law:

Copyrighting AI Content

With only a few keywords and the click of a button, AI text-to-image models such as Midjourney and Stable Diffusion can produce intricate and sophisticated artistic renderings that would ordinarily receive copyright protection if they were produced entirely by a human artist.

Some argue that AI art generators are more akin to the advent of the camera, technology that is now recognized as a tool used to capture creative human expression. Others take the view that generative AI tools are more like autonomous programs that make artistic decisions without human involvement.

In the United States, courts have determined that only human authors can receive copyright protection for their work. A federal district court in Washington, D.C., this summer ruled that an AI-generated image called “A Road to Paradise” couldn’t receive a copyright registration because the computer scientist who prompted the AI, Stephen Thaler, provided no artistic decisions. Thaler has appealed the ruling, which will be heard in the new year.

The US Copyright Office has taken a strict stance, requiring applicants to disclose the use of AI in their registrations. It has rejected at least three applications for AI-generated images, even when the human artist described using dozens of text prompts and additional edits. In another application of an AI-generated comic book, the office rejected registration for the AI-generated images but granted registration for the author’s arrangement of the images into a book.

Other countries have taken a more lenient approach. The Beijing Internet Court in China ruled in November that an AI image of a woman created with Stable Diffusion could receive copyright protection, meeting requisite originality and intellectual achievement standards under Chinese law.

“This stands in direct contrast to our US policy right now and I think this puts the US at a major disadvantage in terms of its creative industry,” said attorney Ryan Abbott of Brown Neri Smith & Khan LLP, who represents Thaler.

In the United Kingdom, a decades-old law could inadvertently support the copyrightability of modern AI-generated works. The Copyright, Designs and Patents Act of 1988 provides explicit protection for computer-generated works.

The law was a result of concerns that any creative work touched by a computer would lose copyright protection, according to Andres Guadamuz, who researches intellectual property at the University of Sussex.

“It’s a curious provision of the law,” said Chris Mammen of Womble Bond Dickinson. “It’s been sitting there for almost 35 years and has never really been litigated but it has new salience in this era of generative AI.”

Guadamuz said the US’s seemingly stricter policy toward the AI copyrightability question stands out and is partially a result of the US’s requirement that artistic works be registered before suing for infringement. That adds an additional layer of gatekeeping that could slow down creative uses of AI by artists, he said.

“I’m worried that lots of works that have a lot of human creativity are now being rejected just because there is a whiff of artificial intelligence,” Guadamuz said.

Training AI

Regulators are similarly divided over whether training AI models on copyrighted content is legal.

US courts haven’t reached a definitive conclusion about whether that falls under the “fair use” standard that allows copying without permission. With litigation still in the early stages, a final answer could be years away. AI companies and legal experts have argued that existing case law on fair use supports training in most cases.

In the UK, the High Court of Justice ruled in early December that Getty Images’ copyright case against Stability AI over model training could proceed to a trial overseen by a specialist judge.

Other countries with competitive tech industries have been more proactive in creating exemptions for AI training.

Japan amended its copyright law in 2018 to explicitly allow data scraping for the purpose of training machine learning models. The country has continued to endorse copyright policies that would favor AI developers.

Singapore adopted a new copyright law in 2021 that creates a similar exemption when copying for the purpose of “computational data analysis.”

The Israeli Ministry of Justice released guidance this summer recognizing that training a machine learning model would generally fall under the country’s fair use standards, citing US fair use court cases. The exemption wouldn’t apply in cases where an AI model was trained exclusively on the work of a single artist in an attempt to compete with the artist, the opinion said.

A draft version of the European Union’s forthcoming AI Act adopts the EU copyright law that grants exemptions for text and data-mining operations, but does include opt-out provisions for rights holders.

Shelley McKinley, chief legal office at Microsoft’s Github Inc., said she is optimistic that jurisdictions will recognize the principle that AI training is about extracting “uncopyrightable elements” from data. “I think the prevailing thought is to protect the ability for training on public data,” she said.

It’s not entirely clear whether an AI program trained in a country with lenient copyright rules can be deployed in a country with stricter rules. Regardless, AI companies will be keeping close watch on jurisdictions with favorable laws.

“Countries that have more lenient rules may become more welcoming to some AI companies,” Guadamuz said. “All it takes is a couple of rulings in favor of the companies.”

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Microsoft helps businesses reimagine how they bring together people, data, and processes to create value for their customers and maintain a competitive advantage in a digital-first world. We partner with more than 2,000 organizations that form part of our Microsoft Partner Network in Malaysia, to transform them into a digital company by developing new capabilities to engage better with their customers, empower their employees, optimize their operations, and transform their products.

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Our efforts include the Global Skilling Initiative that offers digital skills and pathways to open doors for local talents to greater economic opportunity, and the Digital Educational Learning Initiative Malaysia with the Ministry of Education to ensure equal access to technology solutions for 5.2 million students and educators nationwide. We recently launched Bersama Malaysia (Together with Malaysia) initiative, marking our long-term commitment to empowering Malaysia’s inclusive digital economy.

As our nation transitions towards a new digital economy, Microsoft is committed to building on its partnerships with Malaysia, towards a future that is innovative, inclusive, trusted and competitive.