How AT&T migrated 40,000 users to IBM’s IoT solutions

Any telecom provider must always try to avoid network downtime. But to stay competitive these companies also must constantly upgrade their software and systems. So when AT&T decided to migrate more than 40,000 users to comprehensive IBM IoT solutions—to support internal software development and replace its existing disparate solutions—the company knew it was facing a long slog.

Naturally, service outages were not an option during this protracted transition. That’s a primary reason why, over the course of about three years, the company used an agile business planning model and IoT-enabled solutions from IBM to complete this monumental project. AT&T agile tool product owner and team lead Tiina Seppalainen detailed how it all unfolded at the recent IBM Continuous Engineering Summit in New Orleans.

Seppalainen CE Summit re IoT solutions

AT&T’s Tiina Seppalainen describes her company’s use of IBM’s IoT solutions.

Deliberate and sequential planning

Seppalainen said the keys to success lied in broad buy-in from all levels of the company. This included a meticulously planned process for executing and managing the changes at various stages. “We had an aggressive and changing schedule, and we did this without any kind of formal training; we were given the tools and told to have at it, so that’s what we did,” she explained, adding that the project involved about 3,000 applications, about 100 project areas and 57 servers.

Careful and sequential planning were key.  Seppalainen and her colleagues set up about 10 scrum teams, a total of about 100 people, who were primarily dedicated to the project. “This allowed us to be nimble and change as needed, which was frequently,” Seppalainen recalled. “We regularly adjusted either what we were doing or when we were doing it. And we had a team to engage user groups and keep people apprised of the progress.” She said the company’s leaders actively supported the endeavor via internal communications, webcasts and town halls so “it would be very clear from the top down that this was going to happen, and quickly, and everybody needed to support it.”

In keeping with the agile model, the migration teams rolled out the new solutions in phases. They received feedback from early adopters and adjusted accordingly. Of course, large organizations like AT&T have many stakeholder groups with different wants and needs for their respective operations. Seppalainen reported that while they couldn’t fulfill everyone’s wish list, they were able to prioritize and deliver the most critical requests.

Coordinating the calendar

The volume of users necessitated scheduled releases and automated updates. The agile team spread these across the calendar to avoid overwhelming everyone with the changes. (Seppalainen applauded IBM’s crucial assistance in the project area design work, calling it “a key to our success.”) “We had a lot of concurrent and dependent activities and multiple work streams, and they all had to be managed,” she added. “It was a major challenge to coordinate interdependent and overlapping work efforts.”

This meant having frequent meetings, almost all of them virtual, including check-ins at the beginning and end of every work day. “It was a very agile mindset,” Seppalainen said. “That’s what made this happen; just doing that day in day out.”

Testing and training of IoT solutions

Once new roll-outs were in place, AT&T conducted extensive testing. It established training courses that included certifications, and created “small-bite” videos so users could quickly refresh their skills as needed.

Now that the heavy lifting has concluded, Seppalainen contends that her company views this massive endeavor as a success. “Using the agile approach was one of the key factors because it’s team oriented, very iterative and gives you the ability to adjust to changing needs,” she explained. “Our strong program and project management is what brought this three-year odyssey to fruition.”

To see how you can streamline operations and improve productivity for organizations of all sizes with IBMs Continous Engineering and IoT solutions, visit our landing page. And join us at Think 2018, March 19-22 in Las Vegas.

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IoT weekly round-up: Thursday 7th December 2017

It’s been a little turbulent for all things internet and IoT-related this week. Fake feedback comments may delay the net neutrality vote, Volocopter aims to launch its flying taxis by 2020 and there’s a new service to help predict an impending Bitcoin crash. Read on for the latest from the connected world.

Bitcoin Bubble Burst warns you of a coming crash

Bitcoin believers and sceptics alike may benefit from Bitcoin Bubble Burst. It’s a service that alerts you in real-time to factors that might precipitate the crash everyone seems to be expecting. Bitcoin Bubble Burst’s machine learning system is trained to spot potential crisis points and give you a chance to sell before the panic truly sets in. It keeps watch for relevant news stories and major shifts in Bitcoin price, then passes on the information as a kind of digest. Future plans include the ability for users to set their own risk thresholds, determining how often they receive alerts.

Ionic, the Fitbit smartwatch, to incorporate 60 new apps

Fitbit is adding 60 new apps to its Ionic smartwatch, according to a blog posted on Tuesday. The apps include Yelp, Uber, Nest and TripAdvisor, with music service Deezer to join next year. You can expect 100 new watch faces to choose from, too.

Flying taxis are only two or three years away, says Volocoper

Volocoper, a German-based company, expects to provide flying taxis in just two or three years. Speaking at TechCrunch’s Disrupt event in Berlin, CIO and co-founder Alex Zosel said that the first commercial applications could be up and running by 2020. It’s likely the service will start life as a solution to ease traffic congestion in built-up areas, and develop into a shuttle service later down the line.

IBM’s POWER9 chip is built for AI

IBM has a new chip in town: POWER9. The POWER9 processor has four times the bandwidth of its predecessor and is built to handle intensive AI and machine learning workloads. Its start-of-the-art I/O subsystem technology includes next generation NVIDIA NVLink, PCle Gen4, and OpenCAPI: interfaces that will give data scientists more accurate insights more quickly than ever before. There’s also a new server offering AI processing speeds of up to 300 petaflops: the IBM Power Systems AC922.

New York Attorney General calls for delay on net neutrality vote

A couple of weeks ago, we wrote about Ajit Pai’s controversial plan to scrap current net neutrality rules – a proposal that will be put to the vote on 14th December. The net neutrality feedback process prompted over 23 million comments, of which one million may be linked to stolen identities, according to the office of New York Attorney General Eric Schneiderman. Schneiderman has joined 27 senators in calling for a delay to the vote, while the source of the fraudulent comments is investigated.

Keep up-to-date with the connected world

Bookmark the IoT weekly round-up series page to keep up with what’s going on in the wider world of IoT.

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Spotlight on ‘Lawtech’: how machine learning is disrupting the legal sector

Ask a lawyer to describe their daily work, and you’ll probably hear the words ‘document-intensive’ in response. It’s an apt description. The legal profession is overburdened with paperwork. Legal rulings, past cases, contracts and myriad other papers contribute to a data proliferation that is hard to keep on top of.

Unfortunately, failing to keep on top of it is not an option. The thankless task of sifting, reviewing and summarizing often falls to the lot of new associates, who spend between 31 and 35 percent of their time conducting research, according to ‘New Attorney Research Methods Survey’, a study from the Research Intelligence Group.

It’s costly, time-consuming, and (probably) extremely dull. But this way of working is beginning to change. A new sector is emerging in response to the ever-growing burden of data and the resulting high price points for clients. ‘Lawtech’ is bridging the gap between this most traditional of professions and a hitherto untapped source of help: cognitive computing, machine learning, and artificial intelligence.

The convergence point: human expertise meets AI

Over the course of this blog, we’ll look at two broad use cases for cognitive computing, machine learning and artificial intelligence in the legal profession:

  •       Technology-aided review
  •       Smart document creation

Let’s be clear: the idea is not to replace human lawyers with search bots, but to set them free to do more interesting and high-level work by eliminating the miserable grind. Artificial intelligence is not good at writing briefs, appearing in court, or negotiating with clients. This work remains the proviso of highly skilled human beings, and rightly so. However, it is good at document review and data extraction, and has the potential to realize enormous benefits for the legal sector.

Let’s look at some use cases.

Technology-aided review (TAR)

Cognitive computing, artificial intelligence and machine learning are three pillars of something known as TAR – or technology-aided review. This is the process of extracting relevant data points from unstructured data sets, like legal documents or contracts.

It’s in the ability to work with unstructured data sets that AI and cognitive-powered tools come into their own. While it is relatively simple to mine a nice, orderly spreadsheet for information, it’s much more difficult to extract it from more convoluted or scattered sources. TAR tools are capable of ingesting vast data sets of any specification – including data from the Internet of Things. Even more significant, perhaps, is their capacity to learn. These tools go far beyond just programming – instead, they refine their skills and knowledge with each interaction or query, developing and learning as they go.

One such tool is ROSS Intelligence, built on the Watson cognitive computing platform. Its natural language understanding capabilities mean it can understand and interpret nuanced questions more accurately than a simple keyword search. To answer a question, ROSS sifts through multiple text documents until it comes up with the relevant information. The volume of data it can handle is staggering: up to a billion text documents per second. The sheer speed means huge benefits in terms of reduced labor and costs.

TAR tools like ROSS have multiple use cases. They could be invaluable for consultancy work – extracting data such as contract start and end points, or payment dates, from large numbers of documents. The tool then presents these findings in a handy dashboard form, where it provides the base point for human analysis, theorizing or negotiation.

It could also be used to analyze target companies in mergers and acquisitions deals. Machine learning can perform searches on particular companies and identify wording that differs from the norm in global sales contracts, to spotlight potential new deals.

Smart contracts and document creation

While research and review is the obvious use case, automation through machine learning has the potential to perform more complex tasks, too. One of these is document generation.

Contract generation software enables contracts to be automatically produced by asking a series of questions, such as: ‘when does the agreement begin?’ or ‘is the tenant undertaking work on the property?’ The questions generate a decision tree that determines the form the contract will take, ensuring all bases are covered. It’s a little like setting up formulae in an excel spreadsheet, to determine the rules by which the content therein will be governed.

Specialized document software of this kind can also enhance document organization by ensuring that all internal cross-references apply language consistently – even if multiple people have been involved in drafting them. This means consistent terminology across the document and minimized risk of misinterpretation. Document comparison tools can also check for undefined terms and identify missing conditions or clauses, to ensure a water-tight result.

Interestingly, the demand for solutions like these is creating a brand new ‘Lawtech’ sector, and new jobs with it. ‘Legal technicians’, or ‘legal engineers’, many of them ex lawyers themselves, have the job of designing automation solutions and helping law firms to implement them, without the need for a centralized IT system.

Software operating on a cloud-based platform is agile enough to grow and adapt to firms’ growing needs. Cognitive computing and artificial intelligence means the platform is ever-learning, self-improving and immune to the threat of becoming obsolete, because it is always updating its knowledge.

The future of ‘Lawtech’

The emergence of ‘Lawtech’ and its accompanying job opportunities marks an interesting convergence point between mankind and machine. Large organizations that have invested in automation software are already seeing significant returns, in the shape of reduced operating costs, swift, accurate data extraction and better opportunities for their staff to take on high level work.

Attorneys have more time to engage in the creative side of legal representation – keeping clients better informed throughout the legal process, and exploring strategies and outcomes fully with the benefit of trustworthy data. The value of cognitive computing in the legal sector is already apparent – and it’s not going anywhere.

Learn more

To find out more about how ROSS and IBM Watson are creating value for the legal sector, take a look at this blog post, or explore our other solutions for legal professionals.

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It’s alive!! 5 ways buildings are taking advantage of the IoT

After spending a few days at TRIMax immersing myself in all things around facilities management and buildings of the future, one thing was clear. I need to take my building out for a coffee and pick its brain. Our buildings carry so much information about how they are used and we’ve only just begun to scratch the surface of the possibilities of what we can do with that data. It’s time to bring our buildings alive!

For many years, we’ve relied on our own interpretations of our observations. As we walk around a building, we may notice that our co-worker, Johnny, doesn’t come into the office very often even though he has his own corner office. We may get annoyed when we go to book a conference room but everything is taken – though they all appear empty most of the time. The frustration is real when you drag yourself out of bed at 6am to hit the hotel gym only to find all three machines are taken. What if we could improve that visibility and get the most accurate data possible?

Bringing your buildings alive

As we saw in the Kone video, it is possible for our buildings to either interrupt or improve the flow of our days. The applications span far beyond elevators and doors. Sensors can be infused in ice cream coolers, coffee machines, bathrooms, conference rooms, parking lots, and much more. Using the ice cream cooler as an example, consider the impact on a retailer if their ice cream cooler goes down on a hot day in July. That’s going to be a bad day for that retailer. But had they used IoT sensors and capabilities, this breakdown could have been predicted and prevented. In essence, we want our buildings to speak to us and the technology exists to make this possible.

“My sole focus is to bring your buildings alive” – John Smart, Program Director, Cognitive Building & Retail Solutions, IBM

Voice is the next big thing for smart buildings

“What if your building could listen and respond to your needs and wants? Voice is the next big thing in smart buildings.”  – John Smart, Program Director, Cognitive Building & Retail Solutions, IBM

Not only can our buildings talk to us, but we will also be able to talk to our buildings. Using the power of voice, we develop a whole new set of experiences for the employee. Imagine if you need a whiteboard for your meeting. You will be able to simply ask for it, your voice will be captured, and a service request is automatically generated.

Putting Watson in the walls

To fully optimize the capabilities of Watson, he really needs a place to stay. Since you will be optimizing your unused space, the only place left will be the walls. When we say Watson in the walls, we’re not talking about a new blockbuster hit, but rather the partnership we are working on with HARMAN.  IBM is working with Harman on My Personal Concierge, powered by Watson assistant. This is intended to optimize hotel stays and follow you wherever you are on your journey. Need to check if that elliptical in the gym is free without walking down? Check. Ran out of towels? Watson has your back.  Want to make a reservation for dinner at 7pm at the hotel lounge? No problem.

Update room vacancies in real-time

We’ve all been there. We need a conference room but everything is booked. We’re also all guilty of booking a conference room and then not needing it or using it. Do we take the time to cancel the room reservation? If you do, you’re a better person than I am. Most often, there is just a big discrepancy between what rooms are on hold and which are actually being used.

Watson Workplace Concierge can help update room vacancies in real-time. It uses the power of the device and the power of the IoT with little needed involvement by the employee. If you don’t show up to the room, you will get a notification on your phone asking if you still need the room. If you say no, it will automatically unlock the room for others to use. Similarly, if you leave a room mid-way through your reservation, Watson will ask if your meeting is complete and will free up the room.

Space occupancy tracking saves major headaches

The world of commercial real estate is very complex. There is a vast amount of space. In fact, there is 12B square feet in the U.S. alone; but only 67 percent is utilized.  How do we address this gap?

According to Susan Chace from Fidelity, having a strong space assessment depends on mobile tools and the ability to compare physical space to space information with TRIRIGA and make real-time updates as you walk the floor. Just walking around the building and observing is not enough and it is not accurate. Space needs can change daily and having technology in place to capture those changes can make all the difference in whether your space allocations are accurate.

Are you bringing your buildings to life?

The ability to capture key information from our buildings and use that data to optimize customer experiences, employee engagement, and your bottom line are very real. It was a hot topic at TRIMax this year and I look forward to seeing where 2018 will take us.

Don’t forget to catch up on all the activities you missed at TRIMax this year.

To see what others are doing with smart buildings, visit our buildings zone and facilities management hub.

To learn more about IBM TRIRIGA, visit the IBM Marketplace.

 

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How AT&T migrated more than 40,000 users to IBM’s IoT connected products

For any telecom provider, avoiding system downtime is usually job one. So when AT&T decided to migrate more than 40,000 users to IBM’s IoT-enabled connected products—with the goal of supporting internal software development and replace its existing disparate solutions—the company knew it was in for a long slog.

Over the course of about three years, the company used an agile business planning model to pull off this monumental project. AT&T agile tool product owner and team lead Tiina Seppalainen detailed how it all unfolded at the recent IBM Continuous Engineering Summit in New Orleans.

Seppalainen CE Summit

AT&T’s Tiina Seppalainen describes her company’s Rational migration at the 2017 CE Summit.

Connected products buy-in and planning

Seppalainen said the keys to success lied in broad buy-in from all levels of the company and a meticulously planned process for executing and managing the changes at various stages. We had an aggressive and changing schedule, and we did this without any kind of formal training,” she said. “We were given the tools and told to have at it, so that’s what we did.”AT&T had to account for about 3,000 applications that support different parts of the company. “We ended up [affecting] about 100 project areas and 57 servers. And they all needed to be built in time for the migrations to the Rational tools,” Seppalainen said. “It was all planned very carefully and sequentially because of the dependencies between our servers.”

This included setting up between five and 10 scrum teams with a total of about 100 people who were primarily dedicated to the project. “This allowed us to be nimble and change as needed, which was frequently,” Seppalainen said. “We regularly adjusted either what we were doing or when we were doing it, and we had a team to engage user groups and keep people apprised of the progress.”

She added that a critical component of the endeavor was strong leadership commitment at multiple levels and very active support. This included internal communications, webcasts and town halls. “It was very clear from the top down that this was going to happen, and quickly, and everybody needed to support it,” Seppalainen said.

In keeping with the agile model, the migration teams rolled out the new solutions in phases, received feedback from early adopters provided input, and adjusted accordingly. Naturally, such a large organization has many stakeholder groups that wanted different things. Seppalainen said they couldn’t fulfill everyone’s wish list, but they were able to prioritize the most critical requests.

Coordinating the calendar

The volume of users necessitated scheduled releases and automations, which the agile team spread out across the calendar so as not to overwhelm everyone with the build-outs and iterations. (Seppalainen said the crucial help IBM provided in the project area design work was “a key to our success.”) “We had a lot of concurrent and dependent activities and multiple work streams, and they all had to be managed,” she said. “It was a major challenge to coordinate interdependent and overlapping work efforts.”

This meant having frequent meetings, almost all of them virtual, including check-ins at the beginning and end of every work day. “It was a very agile mindset,” Seppalainen said. “That’s what made this happen; just doing that day in day out.”

Testing and training

Once new roll-outs were in place, AT&T conducted extensive testing, established training courses that included certifications, and created “small-bite” videos so users could quickly refresh their skills as needed.

Now that the heavy lifting has concluded, Seppalainen said her company views this massive endeavor as a success. “Using the agile approach was one of the key factors because it’s team oriented, very iterative and gives you the ability to adjust to changing needs,” she said. “Our strong program and project management is what brought this three-year odyssey to fruition.”

To see how you can streamline your organization’s operations and improve productivity with IBMs Continous Engineering and IoT solutions, visit our landing page. And join us at Think 2018, March 19-22 in Las Vegas.

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