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Tag Archives: Mobility

Via partners with troubled May Mobility for autonomous shuttle pilot in Arlington

November 18, 2020   Big Data
 Via partners with troubled May Mobility for autonomous shuttle pilot in Arlington

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Via today announced a partnership with troubled autonomous vehicle startup May Mobility to develop a platform that integrates on-demand shared rides, public transportation, and transit options for passengers with accessibility needs. May says it will adopt Via’s autonomous fleet platform to power booking, routing, passenger and vehicle assignment and identification, customer experience, and fleet management. The longer-term strategy involves multiple public transit deployments in 2021, starting with Arlington, Texas.

By all appearances, May Mobility was a scrappy success story. But a VentureBeat investigation revealed that May engineers struggled to maintain and upgrade the company’s vehicle platform, at one point spending months attempting to install an air conditioning system in the height of summer. Leadership’s ambition often outstretched May’s ability to deliver, which upset vendors, some of whom went unpaid for stretches of time. And not a single one of the company’s commercial routes approached full autonomy.

Despite this, Via plans to forge ahead with the deal. In collaboration with the city of Arlington and supported by a $ 1.7 million U.S. Federal Transit Administration Integrated Mobility Innovation Program grant, on-demand autonomous vehicle rides from May will be incorporated into Via’s existing public transit service in the city. This service has been operational since 2017 and was extended in October 2020.

“Via is a leading provider in on-demand transit services, with a software stack to create efficient, highly-optimized on-demand autonomous vehicle solutions,” a spokesperson told VentureBeat via email. “May Mobility selected Via as a partner to support the company’s shift from a focus on fixed route AV services to on-demand, and will leverage Via’s experience and technology to further develop its suite of autonomous vehicle capabilities in a new way.”

The one-year Via and May pilot program in Arlington, called Arlington Rideshare, Automation, and Payment Integration Demonstration (RAPID), is expected to launch for the public in March 2021. The companies say it will serve downtown Arlington and the University of Texas at Arlington campus, providing students and faculty with free rides during the test phase, all integrated into Via’s app.

Beyond Arlington, Via and May plan to expand access to full-scale autonomous transit networks in 2021, in coordination and partnership with public transit systems in a number of locations across the U.S. “Via’s partnership with May Mobility will integrate flexible, autonomous vehicle fleets into public transit today and will provide insights to support cities as they transform public transit infrastructure for the future,” Via cofounder and CEO Daniel Ramot said.

May’s post-deployment road has been bumpier than most, but some of its rivals haven’t fared much better. In February, the National Highway Traffic Safety Administration (NHTSA) partially suspended U.S. operations of France’s EasyMile after a passenger in Columbus, Ohio was injured while riding in one of the company’s driverless shuttles. And in 2018, the NHTSA suspended a separate Transdev program in Florida that sought to replace school buses with EasyMile vehicles.

The Department of Transportation two years ago published a prescient report on the autonomous shuttle sector that highlighted the limited vehicle autonomy, procurement challenges, and regulatory unpredictability shuttle startups have yet to address. The industry isn’t without apparent success stories, like that of Optimus Ride. But May’s setbacks illustrate the nascent technology’s limited applicability, particularly when stretched beyond its capabilities.


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ProBeat: Robots need to solve mobility before we find their killer app

September 20, 2020   Big Data
 ProBeat: Robots need to solve mobility before we find their killer app

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This week we published our interview with Boston Dynamics CEO Robert Playter. We discussed his first year as CEO; the company’s profitability target after three decades (Boston Dynamics was founded in 1992); Spot, Pick, Handle, and Atlas; and the company’s broader roadmap, including which robots are next.

The interview comes on the heels of Boston Dynamics opening sales for its quadruped robot Spot in the U.S. for $ 74,500. Last week, the company expanded Spot sales to Canada, the EU, and the U.K. at the same price point. Playter shared early sales numbers with us and promised Spot would get a robot arm next year. After we had finished talking about the company’s plans for logistics robots, the conversation shifted to what it always does in 2020, and the most important feature of Boston Dynamics’ robots. An edited transcript of the tail end of our conversation is below.

VentureBeat: How has the pandemic impacted day to day operations?

Playter: I think we adapted more quickly than I ever would have expected. And more positively. There’s no way we are at 100% productivity because by their nature these machines, sometimes you have to be close to them. But the neat thing about Spot is we already had the manufacturing lined up and running when the pandemic really hit and we sent everybody home to work. And a lot of the engineers got to go home with a robot and basically continue their work at home. So that was really remarkable. Now we can’t do that with some of our logistics robots. And so, some of that development definitely slowed down. We did more work in simulation. Once we started doing limited and controlled access back to our facilities, we put the people back in the buildings who really had to be with the robots to do experiments.

But overall, I’ve been really pleased at just how productive people can be working remotely. Now I think we’re losing something in the long run, and I’m anxious for us to be able to start to spend some time together again in a controlled fashion. And it’s also just being around robots is inherently kind of exciting and motivating. You need to be around them, I think, to kind of keep the energy level high. But really it’s gone surprisingly well, I would say.

VentureBeat: Has the pandemic impacted your thinking about where the company should focus, the roadmap, and broader mission?

Playter: It hasn’t really changed what we were thinking about doing in terms of developing and launching these products. What I think it might have done is change the sense of urgency that the market might feel and about exploring these things. March, April, sales kept going but they weren’t growing. It was sort of slow and I think that’s because all of our customers were at home too. Everybody was adapting to what the heck is going on.

Now we did adapt quickly and do some kinds of rapid development. The whole idea of Dr. Spot, our telemedicine robot. That was really born out of us trying to think, ‘Well what is it that we can do that addresses this pandemic directly? Jeez, this seems like a case where robots ought to be relevant. If suddenly being with other people is dangerous, is there an application that’s useful?’ We explored things like remote learning. Being able to experiment with or program a robot remotely, maybe that’s interesting. We decided not to pursue that.

But we had several inbound inquiries about using a robot to essentially do intake monitoring for patients. Allowing the medical personnel to stay remote from the patient, to not have to change out their protective equipment, which of course was in short supply. The patients felt safer, potentially, by not being exposed to somebody who was just talking to another potentially sick patient. And if you could do this remote vital sign sensing — which by the way was a hard problem; nobody had really pulled all these pieces together for the remote vital sign measurement. So we did a rapid development, teaming with MIT and Brigham and Women’s Hospital. And we were able to get something going pretty quickly, mostly because Spot is a platform and it’s been configured from the beginning to handle new sensors, new payloads, and we were able to sort of create some working prototypes, which had been tested and we actually have more than one customer for.

But in the end, it’s not going to be a giant market. I don’t think that’s the killer app for robots. But we definitely did some rapid exploration. There’s other kinds of exploration, like disinfecting robots. We’ve done a little bit of work there. But I think in the end it’s not going to be one of those direct applications that help Spot take off. It’s going to be the things we were imagining originally: managing a complex industrial site, a utility, an oil and gas site, a construction site, a manufacturing site. Those are the things that we thought originally were going to be important. Those are the things where I’d say the majority of our customers are pulling from. But I think there might be a little bit greater sense of urgency because suddenly those are essential services. Keeping the electricity on. Keeping the manufacturing lines running. Keeping the warehouses running. And doing that without over exposing people to each other — suddenly that created a little extra sense of urgency for maybe exploring the role of robotics, I think.

VentureBeat: Did anything surprise you during the pandemic, other than hospitals apparently asking for Spots?

Playter: I mean, that that was a little surprising to us. I hadn’t contemplated those applications before. I think when we went into our early adopter program we expected construction sites and maybe oil and gas sites to be interesting targets. Some of the lessons that came out of that, though, were that just managing nuclear power plants, electric utilities — those were not something we had anticipated, but in some ways, they might be the best opportunities for launching a comprehensive solution based on Spot. So basically the early adopter program taught us to go focus a little bit more narrowly on some of those utilities I think that we expected going in.

VentureBeat: Is there anything that we missed in our discussion or that you feel the press is missing in general?

Playter: We’ve always thought that mobility was a key functionality that hasn’t really been available in a robot yet. There’s been lots of wheeled robots. And they stay at a certain limited kind of mobility, but they couldn’t really get around. And so, I guess there’s sort of a bigger idea, which is that true mobility in a robot is a more transformational capability than I think people appreciate. I sort of suggested earlier that a mobile picking robot is more valuable than one that’s bolted to the floor. A mobile robot like Spot takes an asset like a sensor or an arm, or maybe even a remote person who’s located someplace else but can dial in through a camera and see what the robot is seeing. That mobility really amplifies the value of whatever the robot is carrying around. If it’s an arm, it’s more valuable because it can be distributed, if it’s a sensor, or if it’s a person who’s located around the world. In some ways I feel like these robots are kind of a superpower that lets a person come in and be anywhere that they need to be. And it might be in a dangerous place or just a place that’s difficult to get to. Maybe it would take three days to get there, but you could have a robot that’s there instantaneously. I think mobility is an amplifier of value and of people and assets that the robot carries. I guess I just think that’s going to be true across a whole range of industries.

VentureBeat: My read on it is the industry focused on “static” robots because mobile was just not feasible for so long. And you could achieve quite a fair bit if you have a robotic arm in a factory, for example. Once mobility started to be possible, it was still very difficult to achieve and certainly in an affordable way. It seems like it’s starting to happen, now it’s just a question of figuring out how do you apply it effectively. It opens up so many doors, but which door do you go through or which door do you invest in? You have a mobile robot. OK, but what’s the thing that it will do most effectively? And how do you then develop the software and the tools and the process for it to do that thing that you’ve prioritized on your list.

Playter: I think you’re exactly right. I guess the trick that we have to navigate is finding the application that’s valuable enough that lets this product grow. But the whole concept of having a platform, which is really where Spot started was that we want to be able to pivot at a later time to some other application if it arises. In fact, we have this conversation all the time inside the company. Do we prioritize the platform and let a thousand seeds grow in terms of getting robots in the innovator class’ hands and see what they do with it, or do we focus on an industry where we think we can get enough value? And frankly we need to find a way to straddle and do both. To have a successful product, I think we need to scale to thousands of units, and we’re going to do that by focusing on more narrowly on a set of industries. But we also think there’s things we haven’t thought of yet. And that others are going to think of. And we want to have a platform that makes those things available to them.

VentureBeat: Yeah, it’s definitely something you have to balance. If I had to prioritize, I guess I would try to get as many units out as possible because people can always hack it. But yeah, of course, you got to make sure that if someone does try to put something on it, or makes a different payload, you have to make sure that’s even achievable. You have to make it modular from the get go. Otherwise, you’re very limited in what it can do and what people can try to do with it.

Playter: Exactly, yeah.

VentureBeat: Thank you for taking the time.

Playter: It was nice to talking to you. Thanks for your interest.

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Intel acquires urban mobility startup Moovit for $900 million

May 4, 2020   Big Data

Intel has confirmed that it’s buying Israeli urban mobility startup Moovit, in a deal worth $ 900 million. Reports of the impending acquisition were first published by local Israeli publication Calcalist on Sunday, and in a press release today, Intel noted that it was buying Ness Ziona-based Moovit to help make Mobileye a “complete mobility provider,” which will eventually include driverless taxi services.

Chip giant Intel has a recent track record of acquiring Israeli startups. Just a few months back it paid around $ 2 billion for Habana Labs, which develops programmable AI and machine learning accelerators for datacenters. But back in 2017, Intel doled out an eye-popping $ 15.3 billion for Mobileye, a computer vision firm specializing in autonomous cars. Mobileye’s advanced driver-assistance systems (ADAS) are currently used in 60 million vehicles, and as the technology moves further toward full autonomy, Moovit’s arsenal of data will help Mobileye turn on “cost- and demand-optimized driverless” car services.

When the deal closes, Moovit will become part of the Mobileye business but will continue to operate under its own brand and run its existing partnerships. It’s also worth noting that Intel had previously invested in Moovit via its venture capital arm Intel Capital, meaning that the value of the acquisition is actually pegged at $ 840 million, net of Intel Capital equity gain.

The story so far

Founded in 2012, Moovit is best known for its consumer-facing app that’s used by more than 40 million active users globally to see the best ways to traverse a city using a combination of transport options, and even includes nifty augmented reality (AR) directions. However, the company has pivoted its core business to focus on licensing its back-end platform to third parties through a “mobility-as-a-service” (MaaS) offering. Through this, Moovit provides municipalities with data and analytics to improve city transport infrastructure, while corporations such as TomTom and Microsoft also leverage Moovit’s data to offer third-party developer access to real-time transport data to include in their own apps.

 Intel acquires urban mobility startup Moovit for $900 million

Above: NYC: Moovit’s AR-powered “way finder” feature

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The value here for a company like Intel and its Mobileye subsidiary is data, which Moovit aggregates from myriad transit partners and corporations, as well as from its 40 million active users who generate more than 6 billion data points each day around traffic flow and user demand. Mobileye has made no secret of its plans for so-called “robotaxis,” and Moovit’s data will prove vital as it pushes into the driverless MaaS sphere.

Indeed, Intel and Mobileye intend to sell and lease self-driving vehicles for other companies and organizations to operate, while they also plan to deploy their own robotaxi services. But having the technology to operate fleets of driverless vehicles at scale is only part of the picture, and data and “customer-facing infrastructure” will also be required, according to Mobileye CEO Amnon Shashua.

In other words, Moovit gives Mobileye the knowledge it needs as it gears up to commercialize autonomous vehicle services in key markets around the world. Through the Moovit mobile app, Mobileye can push its robotaxi services as part of the broader trip planner offering, meaning that a commuter may see that the best way to get to their office is to take a driverless taxi from their home to the station two miles away, and then get a train the rest of the way.

The timing of Intel’s acquisition is notable, as it comes during a period of great uncertainty for companies such as Moovit — the global COVID-19 crisis has meant that public transport has been in low demand as people have stayed at home. Moovit itself publishes data regarding the impact of COVID-19 on public transit usage in key cities around the world, showing that it’s down by as much as 80% in some areas.

Above: Moovit data showing decline in public transit during COVID-19

As with other companies during the COVID-19 crisis, Moovit has sought new ways to keep business going. Last month it launched an emergency mobilization platform that makes it easier for transit organizations to redeploy their unused vehicle fleets to create new on-demand transport services for frontline workers. Corporations can also use the platform to arrange dedicated pickup services to get their essential employees safely to their place of work.

It’s not clear what role — if any — the COVID-19 crisis played in Moovit’s decision to sell now, but under the wings of a tech behemoth such as Intel, Moovit can worry just that little bit less about revenues in the coming months and years as society adjusts to what could become a “new normal” that leans heavily on remote working. The terms of the deal also seem like a decent exit for Moovit, which had raised around $ 131 million since its inception, including the $ 50 million series D cash injection led by Intel Capital in 2018.

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How Technology Combats Reduced Mobility for Air Travel

March 10, 2020   TIBCO Spotfire
IATAHackathon e1583524934707 696x365 How Technology Combats Reduced Mobility for Air Travel

Reading Time: 4 minutes

TIBCO recently was a sponsor for the IATA Air Hackathon in Seattle where participants gathered to build innovative solutions to help those with reduced mobility travel more easily. The first solution was centered around enhancing the booking experience for passengers traveling with mobility aids (such as wheelchairs). With enhanced booking experience to account for mobility aids, visibility is increased at the earliest stage so aircraft capabilities can be matched as early as possible in the process. Participants could also create a solution around tracking mobility aids throughout the travel journey using blockchain or artificial intelligence (AI).

When it comes to air travel, oftentimes, many who have full mobility think that there are virtually no barriers in terms of who can fly, when, and where. But that is not the case. Traveling is a privilege, one not often experienced by those with reduced mobility due to not being able to navigate their journey to, through, and from the airport. 

The regulation (EC) 1107/2006 of the European Parliament and of the Council concerning the rights of disabled persons and persons with reduced mobility when traveling by air is already addressing this. In the United States, the Air Carrier Access Act prohibits any discrimination of disabled persons or persons with reduced mobility on the basis of disability in air travel. The idea is that no matter your condition, the sky should not be the limit. Groups are taking active steps to break down any digital barriers one may face, allowing anyone to travel anywhere in the world in the most seamless way. 

So what can prevent those with reduced mobility from traveling? There are a number of barriers, including:

  • Online ticket purchase: Only some airline companies provide an email address to send special needs related information to fully describe their mobility aid
  • Assistance request: Assistance is required by law to start within 48 hours before take-off, but most start much later than that, leaving little time to meet accommodations 
  • Flights with a layover: There is a complicated and long process to get one’s wheelchair post-flight during short layovers
  • Assistance at the airport: Lack of skilled personnel who know how to stow a wheelchair or power wheelchair 
  • Transport: High risk of wheelchairs being damaged by airlines and the claim process is not always clear especially when multiple carriers are involved (who’s responsible?)
  • Boarding: Some airlines don’t have the proper infrastructure such as ramps to make it easy to board the plane
  • Onboard: Oftentimes, the seat’s armrest can’t be lifted, making it hard to get into one’s seat and feel comfortable on the plane; some airplanes are not equipped with an accessible toilet; the seat is decided once onboard and the travel companion may have to sit somewhere else

The right technology can certainly solve some of the above pain points.

With the growing number and variety of different barriers, airports and airlines should care now more than ever. Easyjet declared: “We will fly around 100 million passengers this year and of those, over 659,000 required and were provided with assistance during their travels”. In fact, the airline saw a 27 percent increase in passengers requiring special assistance in 2018 from the previous year. 

Additionally, the World Health Organization stated that between 2015 and 2050, the proportion of the world’s population over 60 years old will nearly double from 12 percent to 22 percent.  

Technology to improve the journey

If we think of a “seamless” travel journey, this typically means on-time flights with short delays and all the tools we need at our fingertips. But, for those with reduced mobility, this isn’t always the case. We need to think of multiple types of travelers, each having specific needs that require a personalized seamless travel experience to go from A to B given their specific needs. 

The overall goal is to communicate in an asynchronous manner at every single point across the entire traveler’s journey to send the right information when an event happens.

To do this, airports and airlines turn to APIs, which can interact with all parties involved such as the airline site, the airport, the baggage handler, and the layover airport if applicable. For example, when booking transportation to the airport, the API could exchange information with the airport to request assistance on arrival. Or when booking a flight and creating a traveler profile with information on the specific wheelchair or power wheelchair. This passenger information could give valuable information to the airlines across the end-to-end journey, being able to offer the right transportation to the airport.

By introducing a microservice-based API architecture as opposed to a monolithic architecture, you can create many small highly-specialized, loosely-coupled services. These lightweight and flexible services can be individually deployed and scaled up or down, and support the orchestration and choreography needed to exchange information. The ultimate goal is to model your APIs to introduce the necessary flexibility to create a fully personalized customer journey and therefore remove any possible digital barriers. 

Going forward, air travel providers need to be inclusive when it comes to their customers and their experience so they don’t leave anyone behind. They can leverage microservices and API management solutions to overcome certain barriers. These smart technology choices can help accelerate success while shifting the mindset from a service economy to an experience economy. 

Learn more about how we can help your organization create personalized and seamless travel journeys to put your customers and their individual needs at the center. 

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Better, Safer, Cleaner: Mobility And Detroit

April 27, 2019   SAP
 Better, Safer, Cleaner: Mobility And Detroit

The industry that is often synonymous with smoking tailpipes and rusting factories is undergoing some radical changes. The automotive industry is experiencing the pace of innovation that we’ve come to expect from the tech sector.

Because the transport of people and goods affects us all in countless ways, these changes are reshaping the world we share – for the better. Here’s how:

1. It’s changing its focus from the vehicle to the business model

What we used to call the “automotive industry” is reinventing itself. It has become the mobility industry, and the change is much more than a rebranding exercise. While companies in this sector once focused on manufacturing vehicles, they’re now focused on creating experiences for citizens, for cities, and for societies. It’s a bigger mission. It’s not just about making great cars.

What’s driving this change? The traditional paradigms of buying and leasing are morphing into mobility-as-a-service. Historically, owning and leasing meant having a relationship of sorts with a single vehicle. With mobility, we don’t really care as much about the vehicle. What matters is how we get from Point A to Point B. In this new world, automakers still need the manufacturing and supply chain expertise that made them stalwarts of the industrial economy – but the vehicles they make are now a smaller part of a larger vision.

To keep pace with this evolution, traditional automakers are launching mobility startups within their operations. They’re forming strategic alliances with technology and communications companies to fill in any strategic gaps. And because they see the tremendous opportunity in developing the autonomous fleets that will transform the shipping and distribution industries, they’re scrambling to ensure that they’ll have a place at the table.

So, the transition will be challenging for mobility industry players, but consumers and communities will see significant benefits. As a recent McKinsey report puts it: “Radical improvements in cost-effectiveness, convenience, experience, safety, and environmental impact will, taken together, disrupt myriad business models on an almost inconceivable scale.”

2. It’s becoming more diverse and collaborative

It’s no surprise that a fundamental rethinking of the industry’s business model will call for different talents, new skills, and unorthodox perspectives — and that’s exactly what we’re seeing with the shift to mobility. You don’t need to look any further than the top of GM’s org chart and CEO Mary Barra for the evidence that the industry is becoming more diverse. And diversity is also on the rise in the ecosystem of companies involved in making mobility a reality.  Innovation is just as likely to occur in Silicon Valley as it is in Detroit, and small startups can have as big an impact as a Fortune 500 enterprise. Because of this shift, an innovative idea that used to take years to go from drawing board to assembly line now moves at Internet speed.

Mobility companies are also recognizing that their ability to collaborate within a more diverse ecosystem is a prerequisite to success. Municipalities, utilities, automakers, insurance companies, and telco providers all need one another to deliver on their shared vision, and they’re working together like never before to make the transition to renewable energy, smart cities, and a green economy. There’s now widespread acknowledgment that the future of mobility depends on the cooperation of manufacturers, regulators, governments, and technology companies. And that means the industry needs people who can listen, negotiate, and compromise.

3. It’s becoming cleaner and safer

Speaking of Mary Barra, her announcement of GM’s vision to achieve a future with zero crashes, zero emissions, and zero congestion shows how the entire industry is moving toward a cleaner and safer future. Twenty years ago, this type of announcement would have seemed impossibly audacious. Today, it seems inevitable.

While the internal combustion engine is a reality for the foreseeable future, the real innovation is occurring with electric and autonomous vehicles. The growing momentum of these technologies is leading to a world with less congestion through better traffic management. Fewer distracted drivers drowsing off or texting will reduce fatalities. We’re seeing these changes happen now. Traditional players like Magna, Borg Warner, and Delphi/Aptiv are learning to create business models in the electric/autonomous world. The change won’t happen overnight. Big, powerful, gas-burning vehicles are still money makers for the traditional industry players, and electric vehicles with lithium batteries have their own environmental impact, but the needle is moving. And it’s pointing to a greener, safer future.

Profound change can be either disruption or opportunity. For the automotive industry, the transition to mobility is turning out to be a period of reinvention and new possibilities. It’s an exciting time to be a part of an industry that’s changing the world for the better.

Get to know the preconfigured processes, capabilities, and delivery approach that can help your business flourish now and for years to come. Explore SAP Model Company services for Automotive.

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Target Global announces $100 million fund to target mobility startups

June 5, 2018   Big Data
 Target Global announces $100 million fund to target mobility startups

Berlin-based venture capital firm Target Global announced today it has launched a new fund to target startups working to disrupt transportation.

The fund has raised $ 100 million, but will continue to raise money with the intention of passing $ 300 million. The fund will be evergreen, rather than having a fixed endpoint, because the partners say it’s critical to be able to take a long-term investment view when it comes to mobility startups rather than having to worry about returning money to investors by a certain deadline.

“We saw a lot of disruption happening in this space, and we decided to double down on the segment,” said Alex Frolov, general partner at Target Global.

Target Global is a family of different funds that in total have $ 600 million in assets under management. The company has already invested in some mobility startups through those funds, including Auto1, Delivery Hero, and GoEuro.

Frolov explained that while a growing number of VCs are starting to target transportation and mobility, many of them have ties to traditional vehicle manufacturers. He believes Target will stand out by remaining independent while still being able to partner with a wide range of industry players.

The investments will focus on the widest possible range of the transportation ecosystem being disrupted. As car ownership declines and vehicles become more of a service, Frolov believes the changes are going to be immense. But Target will also look at areas like freight and logistics, along with other industries that are affected by the mobility revolution.

For the moment, the new fund will concentrate on investments in Europe, Russia, and Israel.

The company also announced that Ben Kaminski will join Target Global as a partner based in Israel. Kaminski was previously employed at Goldman Sachs, where he worked with a wide range of mobility companies, including Israel’s Mobileye, which was acquired by Intel in 2017.

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Four Reasons Software Suites Enable Device Flexibility And Mobility

January 15, 2018   BI News and Info

When members of Lowe’s Innovation Labs first began talking with the home improvement retailer’s senior executives about how disruptive technologies would affect the future, the presentations were well received but nothing stuck.

“We’d give a really great presentation and everyone would say, ‘Great job,’ but nothing would really happen,” says Amanda Manna, head of narratives and partnerships for the lab.

The team realized that it needed to ditch the PowerPoints and try something radical. The team’s leader, Kyle Nel, is a behavioral scientist by training. He knows people are wired to receive new information best through stories. Sharing far-future concepts through narrative, he surmised, could unlock hidden potential to drive meaningful change.

So Nel hired science fiction writers to pen the future in comic book format, with characters and a narrative arc revealed pane by pane.

The first storyline, written several years before Oculus Rift became a household name, told the tale of a couple envisioning their kitchen renovation using virtual reality headsets. The comic might have been fun and fanciful, but its intent was deadly serious. It was a vision of a future in which Lowe’s might solve one of its long-standing struggles: the approximately US$ 70 billion left on the table when people are unable to start a home improvement project because they can’t envision what it will look like.

When the lab presented leaders with the first comic, “it was like a light bulb went on,” says Manna. “Not only did they immediately understand the value of the concept, they were convinced that if we didn’t build it, someone else would.”

Today, Lowe’s customers in select stores can use the HoloRoom How To virtual reality tool to learn basic DIY skills in an interactive and immersive environment.

SAP Q417 DigitalDoubles Feature3 Image2 Four Reasons Software Suites Enable Device Flexibility And MobilityOther comics followed and were greeted with similar enthusiasm—and investment, where possible. One tells the story of robots that help customers navigate stores. That comic spawned the LoweBot, which roamed the aisles of several Lowe’s stores during a pilot program in California and is being evaluated to determine next steps.

And the comic about tools that can be 3D-printed in space? Last year, Lowe’s partnered with Made in Space, which specializes in making 3D printers that can operate in zero gravity, to install the first commercial 3D printer in the International Space Station, where it was used to make tools and parts for astronauts.

The comics are the result of sending writers out on an open-ended assignment, armed with trends, market research, and other input, to envision what home improvement planning might look like in the future or what the experience of shopping will be in 10 years. The writers come back with several potential story ideas in a given area and work collaboratively with lab team members to refine it over time.

The process of working with writers and business partners to develop the comics helps the future strategy team at Lowe’s, working under chief development officer Richard D. Maltsbarger, to inhabit that future. They can imagine how it might play out, what obstacles might surface, and what steps the company would need to take to bring that future to life.

Once the final vision hits the page, the lab team can clearly envision how to work backward to enable the innovation. Importantly, the narrative is shared not only within the company but also out in the world. It serves as a kind of “bat signal” to potential technology partners with capabilities that might be required to make it happen, says Manna. “It’s all part of our strategy for staking a claim in the future.”

Companies like Lowe’s are realizing that standard ways of planning for the future won’t get them where they need to go. The problem with traditional strategic planning is that the approach, which dates back to the 1950s and has remained largely unchanged since then, is based on the company’s existing mission, resources, core competencies, and competitors.

Yet the future rarely looks like the past. What’s more, digital technology is now driving change at exponential rates. Companies must be able to analyze and assess the potential impacts of the many variables at play, determine the possible futures they want to pursue, and develop the agility to pivot as conditions change along the way.

This is why planning must become completely oriented toward—and sourced from—the future, rather than from the past or the present. “Every winning strategy is based on a compelling insight, but most strategic planning originates in today’s marketplace, which means the resulting plans are constrained to incremental innovation,” says Bob Johansen, distinguished fellow at the Institute for the Future. “Most corporate strategists and CEOs are just inching their way to the future.” (Read more from Bob Johansen in the Thinkers story, “Fear Factor.”)

Inching forward won’t cut it anymore. Half of the S&P 500 organizations will be replaced over the next decade, according to research company Innosight. The reason? They can’t see the portfolio of possible futures, they can’t act on them, or both. Indeed, when SAP conducts future planning workshops with clients, we find that they usually struggle to look beyond current models and assumptions and lack clear ideas about how to work toward radically different futures.

Companies that want to increase their chances of long-term survival are incorporating three steps: envisioning, planning for, and executing on possible futures. And doing so all while the actual future is unfolding in expected and unexpected ways.

Those that pull it off are rewarded. A 2017 benchmarking report from the Strategic Foresight Research Network (SFRN) revealed that vigilant companies (those with the most mature processes for identifying, interpreting, and responding to factors that induce change) achieved 200% greater market capitalization growth and 33% higher profitability than the average, while the least mature companies experienced negative market-cap growth and had 44% lower profitability.

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Looking Outside the Margins

“Most organizations lack sufficient capacity to detect, interpret, and act on the critically important but weak and ambiguous signals of fresh threats or new opportunities that emerge on the periphery of their usual business environment,” write George S. Day and Paul J. H. Schoemaker in their book Peripheral Vision.

But that’s exactly where effective future planning begins: examining what is happening outside the margins of day-to-day business as usual in order to peer into the future.

Business leaders who take this approach understand that despite the uncertainties of the future there are drivers of change that can be identified and studied and actions that can be taken to better prepare for—and influence—how events unfold.

That starts with developing foresight, typically a decade out. Ten years, most future planners agree, is the sweet spot. “It is far enough out that it gives you a bit more latitude to come up with a broader way to the future, allowing for disruption and innovation,” says Brian David Johnson, former chief futurist for Intel and current futurist in residence at Arizona State University’s Center for Science and the Imagination. “But you can still see the light from it.”

SAP Q417 DigitalDoubles Feature3 Image4 Four Reasons Software Suites Enable Device Flexibility And MobilityThe process involves gathering information about the factors and forces—technological, business, sociological, and industry or ecosystem trends—that are effecting change to envision a range of potential impacts.

Seeing New Worlds

Intel, for example, looks beyond its own industry boundaries to envision possible future developments in adjacent businesses in the larger ecosystem it operates in. In 2008, the Intel Labs team, led by anthropologist Genevieve Bell, determined that the introduction of flexible glass displays would open up a whole new category of foldable consumer electronic devices.

To take advantage of that advance, Intel would need to be able to make silicon small enough to fit into some imagined device of the future. By the time glass manufacturer Corning unveiled its ultra-slim, flexible glass surface for mobile devices, laptops, televisions, and other displays of the future in 2012, Intel had already created design prototypes and kicked its development into higher gear. “Because we had done the future casting, we were already imagining how people might use flexible glass to create consumer devices,” says Johnson.

Because future planning relies so heavily on the quality of the input it receives, bringing in experts can elevate the practice. They can come from inside an organization, but the most influential insight may come from the outside and span a wide range of disciplines, says Steve Brown, a futurist, consultant, and CEO of BaldFuturist.com who worked for Intel Labs from 2007 to 2016.

Companies may look to sociologists or behaviorists who have insight into the needs and wants of people and how that influences their actions. Some organizations bring in an applied futurist, skilled at scanning many different forces and factors likely to coalesce in important ways (see Do You Need a Futurist?).

Do You Need a Futurist?

Most organizations need an outsider to help envision their future. Futurists are good at looking beyond the big picture to the biggest picture.

Business leaders who want to be better prepared for an uncertain and disruptive future will build future planning as a strategic capability into their organizations and create an organizational culture that embraces the approach. But working with credible futurists, at least in the beginning, can jump-start the process.

“The present can be so noisy and business leaders are so close to it that it’s helpful to provide a fresh outside-in point of view,” says veteran futurist Bob Johansen.

To put it simply, futurists like Johansen are good at connecting dots—lots of them. They look beyond the boundaries of a single company or even an industry, incorporating into their work social science, technical research, cultural movements, economic data, trends, and the input of other experts.

They can also factor in the cultural history of the specific company with whom they’re working, says Brian David Johnson, futurist in residence at Arizona State University’s Center for Science and the Imagination. “These large corporations have processes and procedures in place—typically for good reasons,” Johnson explains. “But all of those reasons have everything to do with the past and nothing to do with the future. Looking at that is important so you can understand the inertia that you need to overcome.”

One thing the best futurists will say they can’t do: predict the future. That’s not the point. “The future punishes certainty,” Johansen says, “but it rewards clarity.” The methods futurists employ are designed to trigger discussions and considerations of possibilities corporate leaders might not otherwise consider.

You don’t even necessarily have to buy into all the foresight that results, says Johansen. Many leaders don’t. “Every forecast is debatable,” Johansen says. “Foresight is a way to provoke insight, even if you don’t believe it. The value is in letting yourself be provoked.”

External expert input serves several purposes. It brings everyone up to a common level of knowledge. It can stimulate and shift the thinking of participants by introducing them to new information or ideas. And it can challenge the status quo by illustrating how people and organizations in different sectors are harnessing emerging trends.

The goal is not to come up with one definitive future but multiple possibilities—positive and negative—along with a list of the likely obstacles or accelerants that could surface on the road ahead. The result: increased clarity—rather than certainty—in the face of the unknown that enables business decision makers to execute and refine business plans and strategy over time.

Plotting the Steps Along the Way

Coming up with potential trends is an important first step in futuring, but even more critical is figuring out what steps need to be taken along the way: eight years from now, four years from now, two years from now, and now. Considerations include technologies to develop, infrastructure to deploy, talent to hire, partnerships to forge, and acquisitions to make. Without this vital step, says Brown, everybody goes back to their day jobs and the new thinking generated by future planning is wasted. To work, the future steps must be tangible, concrete, and actionable.

SAP Q417 DigitalDoubles Feature3 Image5 Four Reasons Software Suites Enable Device Flexibility And MobilityOrganizations must build a roadmap for the desired future state that anticipates both developments and detours, complete with signals that will let them know if they’re headed in the right direction. Brown works with corporate leaders to set indicator flags to look out for on the way to the anticipated future. “If we see these flagged events occurring in the ecosystem, they help to confirm the strength of our hypothesis that a particular imagined future is likely to occur,” he explains.

For example, one of Brown’s clients envisioned two potential futures: one in which gestural interfaces took hold and another in which voice control dominated. The team set a flag to look out for early examples of the interfaces that emerged in areas such as home appliances and automobiles. “Once you saw not just Amazon Echo but also Google Home and other copycat speakers, it would increase your confidence that you were moving more towards a voice-first era rather than a gesture-first era,” Brown says. “It doesn’t mean that gesture won’t happen, but it’s less likely to be the predominant modality for communication.”

How to Keep Experiments from Being Stifled

Once organizations have a vision for the future, making it a reality requires testing ideas in the marketplace and then scaling them across the enterprise. “There’s a huge change piece involved,”
says Frank Diana, futurist and global consultant with Tata Consultancy Services, “and that’s the place where most
businesses will fall down.”

Many large firms have forgotten what it’s like to experiment in several new markets on a small scale to determine what will stick and what won’t, says René Rohrbeck, professor of strategy at the Aarhus School of Business and Social Sciences. Companies must be able to fail quickly, bring the lessons learned back in, adapt, and try again.

SAP Q417 DigitalDoubles Feature3 Image6 Four Reasons Software Suites Enable Device Flexibility And MobilityLowe’s increases its chances of success by creating master narratives across a number of different areas at once, such as robotics, mixed-reality tools, on-demand manufacturing, sustainability, and startup acceleration. The lab maps components of each by expected timelines: short, medium, and long term. “From there, we’ll try to build as many of them as quickly as we can,” says Manna. “And we’re always looking for that next suite of things that we should be working on.” Along the way certain innovations, like the HoloRoom How-To, become developed enough to integrate into the larger business as part of the core strategy.

One way Lowe’s accelerates the process of deciding what is ready to scale is by being open about its nascent plans with the world. “In the past, Lowe’s would never talk about projects that weren’t at scale,” says Manna. Now the company is sharing its future plans with the media and, as a result, attracting partners that can jump-start their realization.

Seeing a Lowe’s comic about employee exoskeletons, for example, led Virginia Tech engineering professor Alan Asbeck to the retailer. He helped develop a prototype for a three-month pilot with stock employees at a Christiansburg, Virginia, store.

The high-tech suit makes it easier to move heavy objects. Employees trying out the suits are also fitted with an EEG headset that the lab incorporates into all its pilots to gauge unstated, subconscious reactions. That direct feedback on the user experience helps the company refine its innovations over time.

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Make the Future Part of the Culture

Regardless of whether all the elements of its master narratives come to pass, Lowe’s has already accomplished something important: It has embedded future thinking into the culture of the company.

Companies like Lowe’s constantly scan the environment for meaningful economic, technology, and cultural changes that could impact its future assessments and plans. “They can regularly draw on future planning to answer challenges,” says Rohrbeck. “This intensive, ongoing, agile strategizing is only possible because they’ve done their homework up front and they keep it updated.”

It’s impossible to predict what’s going to happen in the future, but companies can help to shape it, says Manna of Lowe’s. “It’s really about painting a picture of a preferred future state that we can try to achieve while being flexible and capable of change as we learn things along the way.” D!


About the Authors

Dan Wellers is Global Lead, Digital Futures, at SAP.

Kai Goerlich is Chief Futurist at SAP’s Innovation Center Network.

Stephanie Overby is a Boston-based business and technology journalist.


Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.

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Why Enterprise Mobility Is More Transformational Than We Ever Thought

July 6, 2017   BI News and Info

Dan McCaffrey has an ambitious goal: solving the world’s looming food shortage.

As vice president of data and analytics at The Climate Corporation (Climate), which is a subsidiary of Monsanto, McCaffrey leads a team of data scientists and engineers who are building an information platform that collects massive amounts of agricultural data and applies machine-learning techniques to discover new patterns. These analyses are then used to help farmers optimize their planting.

“By 2050, the world is going to have too many people at the current rate of growth. And with shrinking amounts of farmland, we must find more efficient ways to feed them. So science is needed to help solve these things,” McCaffrey explains. “That’s what excites me.”

“The deeper we can go into providing recommendations on farming practices, the more value we can offer the farmer,” McCaffrey adds.

But to deliver that insight, Climate needs data—and lots of it. That means using remote sensing and other techniques to map every field in the United States and then combining that information with climate data, soil observations, and weather data. Climate’s analysts can then produce a massive data store that they can query for insights.

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Meanwhile, precision tractors stream data into Climate’s digital agriculture platform, which farmers can then access from iPads through easy data flow and visualizations. They gain insights that help them optimize their seeding rates, soil health, and fertility applications. The overall goal is to increase crop yields, which in turn boosts a farmer’s margins.

Climate is at the forefront of a push toward deriving valuable business insight from Big Data that isn’t just big, but vast. Companies of all types—from agriculture through transportation and financial services to retail—are tapping into massive repositories of data known as data lakes. They hope to discover correlations that they can exploit to expand product offerings, enhance efficiency, drive profitability, and discover new business models they never knew existed.

The internet democratized access to data and information for billions of people around the world. Ironically, however, access to data within businesses has traditionally been limited to a chosen few—until now. Today’s advances in memory, storage, and data tools make it possible for companies both large and small to cost effectively gather and retain a huge amount of data, both structured (such as data in fields in a spreadsheet or database) and unstructured (such as e-mails or social media posts). They can then allow anyone in the business to access this massive data lake and rapidly gather insights.

It’s not that companies couldn’t do this before; they just couldn’t do it cost effectively and without a lengthy development effort by the IT department. With today’s massive data stores, line-of-business executives can generate queries themselves and quickly churn out results—and they are increasingly doing so in real time. Data lakes have democratized both the access to data and its role in business strategy.

Indeed, data lakes move data from being a tactical tool for implementing a business strategy to being a foundation for developing that strategy through a scientific-style model of experimental thinking, queries, and correlations. In the past, companies’ curiosity was limited by the expense of storing data for the long term. Now companies can keep data for as long as it’s needed. And that means companies can continue to ask important questions as they arise, enabling them to future-proof their strategies.

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Prescriptive Farming

Climate’s McCaffrey has many questions to answer on behalf of farmers. Climate provides several types of analytics to farmers including descriptive services, which are metrics about the farm and its operations, and predictive services related to weather and soil fertility. But eventually the company hopes to provide prescriptive services, helping farmers address all the many decisions they make each year to achieve the best outcome at the end of the season. Data lakes will provide the answers that enable Climate to follow through on its strategy.

Behind the scenes at Climate is a deep-science data lake that provides insights, such as predicting the fertility of a plot of land by combining many data sets to create accurate models. These models allow Climate to give farmers customized recommendations based on how their farm is performing.

“Machine learning really starts to work when you have the breadth of data sets from tillage to soil to weather, planting, harvest, and pesticide spray,” McCaffrey says. “The more data sets we can bring in, the better machine learning works.”

The deep-science infrastructure already has terabytes of data but is poised for significant growth as it handles a flood of measurements from field-based sensors.

“That’s really scaling up now, and that’s what’s also giving us an advantage in our ability to really personalize our advice to farmers at a deeper level because of the information we’re getting from sensor data,” McCaffrey says. “As we roll that out, our scale is going to increase by several magnitudes.”

Also on the horizon is more real-time data analytics. Currently, Climate receives real-time data from its application that streams data from the tractor’s cab, but most of its analytics applications are run nightly or even seasonally.

In August 2016, Climate expanded its platform to third-party developers so other innovators can also contribute data, such as drone-captured data or imagery, to the deep-science lake.

“That helps us in a lot of ways, in that we can get more data to help the grower,” McCaffrey says. “It’s the machine learning that allows us to find the insights in all of the data. Machine learning allows us to take mathematical shortcuts as long as you’ve got enough data and enough breadth of data.”

Predictive Maintenance

Growth is essential for U.S. railroads, which reinvest a significant portion of their revenues in maintenance and improvements to their track systems, locomotives, rail cars, terminals, and technology. With an eye on growing its business while also keeping its costs down, CSX, a transportation company based in Jacksonville, Florida, is adopting a strategy to make its freight trains more reliable.

In the past, CSX maintained its fleet of locomotives through regularly scheduled maintenance activities, which prevent failures in most locomotives as they transport freight from shipper to receiver. To achieve even higher reliability, CSX is tapping into a data lake to power predictive analytics applications that will improve maintenance activities and prevent more failures from occurring.

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Beyond improving customer satisfaction and raising revenue, CSX’s new strategy also has major cost implications. Trains are expensive assets, and it’s critical for railroads to drive up utilization, limit unplanned downtime, and prevent catastrophic failures to keep the costs of those assets down.

That’s why CSX is putting all the data related to the performance and maintenance of its locomotives into a massive data store.

“We are then applying predictive analytics—or, more specifically, machine-learning algorithms—on top of that information that we are collecting to look for failure signatures that can be used to predict failures and prescribe maintenance activities,” says Michael Hendrix, technical director for analytics at CSX. “We’re really looking to better manage our fleet and the maintenance activities that go into that so we can run a more efficient network and utilize our assets more effectively.”

“In the past we would have to buy a special storage device to store large quantities of data, and we’d have to determine cost benefits to see if it was worth it,” says Donna Crutchfield, assistant vice president of information architecture and strategy at CSX. “So we were either letting the data die naturally, or we were only storing the data that was determined to be the most important at the time. But today, with the new technologies like data lakes, we’re able to store and utilize more of this data.”

CSX can now combine many different data types, such as sensor data from across the rail network and other systems that measure movement of its cars, and it can look for correlations across information that wasn’t previously analyzed together.

One of the larger data sets that CSX is capturing comprises the findings of its “wheel health detectors” across the network. These devices capture different signals about the bearings in the wheels, as well as the health of the wheels in terms of impact, sound, and heat.

“That volume of data is pretty significant, and what we would typically do is just look for signals that told us whether the wheel was bad and if we needed to set the car aside for repair. We would only keep the raw data for 10 days because of the volume and then purge everything but the alerts,” Hendrix says.

With its data lake, CSX can keep the wheel data for as long as it likes. “Now we’re starting to capture that data on a daily basis so we can start applying more machine-learning algorithms and predictive models across a larger history,” Hendrix says. “By having the full data set, we can better look for trends and patterns that will tell us if something is going to fail.”

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Another key ingredient in CSX’s data set is locomotive oil. By analyzing oil samples, CSX is developing better predictions of locomotive failure. “We’ve been able to determine when a locomotive would fail and predict it far enough in advance so we could send it down for maintenance and prevent it from failing while in use,” Crutchfield says.

“Between the locomotives, the tracks, and the freight cars, we will be looking at various ways to predict those failures and prevent them so we can improve our asset allocation. Then we won’t need as many assets,” she explains. “It’s like an airport. If a plane has a failure and it’s due to connect at another airport, all the passengers have to be reassigned. A failure affects the system like dominoes. It’s a similar case with a railroad. Any failure along the road affects our operations. Fewer failures mean more asset utilization. The more optimized the network is, the better we can service the customer.”

Detecting Fraud Through Correlations

Traditionally, business strategy has been a very conscious practice, presumed to emanate mainly from the minds of experienced executives, daring entrepreneurs, or high-priced consultants. But data lakes take strategy out of that rarefied realm and put it in the environment where just about everything in business seems to be going these days: math—specifically, the correlations that emerge from applying a mathematical algorithm to huge masses of data.

The Financial Industry Regulatory Authority (FINRA), a nonprofit group that regulates broker behavior in the United States, used to rely on the experience of its employees to come up with strategies for combating fraud and insider trading. It still does that, but now FINRA has added a data lake to find patterns that a human might never see.

Overall, FINRA processes over five petabytes of transaction data from multiple sources every day. By switching from traditional database and storage technology to a data lake, FINRA was able to set up a self-service process that allows analysts to query data themselves without involving the IT department; search times dropped from several hours to 90 seconds.

While traditional databases were good at defining relationships with data, such as tracking all the transactions from a particular customer, the new data lake configurations help users identify relationships that they didn’t know existed.

Leveraging its data lake, FINRA creates an environment for curiosity, empowering its data experts to search for suspicious patterns of fraud, marketing manipulation, and compliance. As a result, FINRA was able to hand out 373 fines totaling US$ 134.4 million in 2016, a new record for the agency, according to Law360.

Data Lakes Don’t End Complexity for IT

Though data lakes make access to data and analysis easier for the business, they don’t necessarily make the CIO’s life a bed of roses. Implementations can be complex, and companies rarely want to walk away from investments they’ve already made in data analysis technologies, such as data warehouses.

“There have been so many millions of dollars going to data warehousing over the last two decades. The idea that you’re just going to move it all into a data lake isn’t going to happen,” says Mike Ferguson, managing director of Intelligent Business Strategies, a UK analyst firm. “It’s just not compelling enough of a business case.” But Ferguson does see data lake efficiencies freeing up the capacity of data warehouses to enable more query, reporting, and analysis.

sap Q217 digital double feature3 images6 Why Enterprise Mobility Is More Transformational Than We Ever ThoughtData lakes also don’t free companies from the need to clean up and manage data as part of the process required to gain these useful insights. “The data comes in very raw, and it needs to be treated,” says James Curtis, senior analyst for data platforms and analytics at 451 Research. “It has to be prepped and cleaned and ready.”

Companies must have strong data governance processes, as well. Customers are increasingly concerned about privacy, and rules for data usage and compliance have become stricter in some areas of the globe, such as the European Union.

Companies must create data usage policies, then, that clearly define who can access, distribute, change, delete, or otherwise manipulate all that data. Companies must also make sure that the data they collect comes from a legitimate source.

Many companies are responding by hiring chief data officers (CDOs) to ensure that as more employees gain access to data, they use it effectively and responsibly. Indeed, research company Gartner predicts that 90% of large companies will have a CDO by 2019.

Data lakes can be configured in a variety of ways: centralized or distributed, with storage on premise or in the cloud or both. Some companies have more than one data lake implementation.

“A lot of my clients try their best to go centralized for obvious reasons. It’s much simpler to manage and to gather your data in one place,” says Ferguson. “But they’re often plagued somewhere down the line with much more added complexity and realize that in many cases the data lake has to be distributed to manage data across multiple data stores.”

Meanwhile, the massive capacities of data lakes mean that data that once flowed through a manageable spigot is now blasting at companies through a fire hose.

“We’re now dealing with data coming out at extreme velocity or in very large volumes,” Ferguson says. “The idea that people can manually keep pace with the number of data sources that are coming into the enterprise—it’s just not realistic any more. We have to find ways to take complexity away, and that tends to mean that we should automate. The expectation is that the information management software, like an information catalog for example, can help a company accelerate the onboarding of data and automatically classify it, profile it, organize it, and make it easy to find.”

Beyond the technical issues, IT and the business must also make important decisions about how data lakes will be managed and who will own the data, among other things (see How to Avoid Drowning in the Lake).

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How to Avoid Drowning in the Lake

The benefits of data lakes can be squandered if you don’t manage the implementation and data ownership carefully.

Deploying and managing a massive data store is a big challenge. Here’s how to address some of the most common issues that companies face:

Determine the ROI. Developing a data lake is not a trivial undertaking. You need a good business case, and you need a measurable ROI. Most importantly, you need initial questions that can be answered by the data, which will prove its value.

Find data owners. As devices with sensors proliferate across the organization, the issue of data ownership becomes more important.

Have a plan for data retention. Companies used to have to cull data because it was too expensive to store. Now companies can become data hoarders. How long do you store it? Do you keep it forever?

Manage descriptive data. Software that allows you to tag all the data in one or multiple data lakes and keep it up-to-date is not mature yet. We still need tools to bring the metadata together to support self-service and to automate metadata to speed up the preparation, integration, and analysis of data.

Develop data curation skills. There is a huge skills gap for data repository development. But many people will jump at the chance to learn these new skills if companies are willing to pay for training and certification.

Be agile enough to take advantage of the findings. It used to be that you put in a request to the IT department for data and had to wait six months for an answer. Now, you get the answer immediately. Companies must be agile to take advantage of the insights.

Secure the data. Besides the perennial issues of hacking and breaches, a lot of data lakes software is open source and less secure than typical enterprise-class software.

Measure the quality of data. Different users can work with varying levels of quality in their data. For example, data scientists working with a huge number of data points might not need completely accurate data, because they can use machine learning to cluster data or discard outlying data as needed. However, a financial analyst might need the data to be completely correct.

Avoid creating new silos. Data lakes should work with existing data architectures, such as data warehouses and data marts.

From Data Queries to New Business Models

The ability of data lakes to uncover previously hidden data correlations can massively impact any part of the business. For example, in the past, a large soft drink maker used to stock its vending machines based on local bottlers’ and delivery people’s experience and gut instincts. Today, using vast amounts of data collected from sensors in the vending machines, the company can essentially treat each machine like a retail store, optimizing the drink selection by time of day, location, and other factors. Doing this kind of predictive analysis was possible before data lakes came along, but it wasn’t practical or economical at the individual machine level because the amount of data required for accurate predictions was simply too large.

The next step is for companies to use the insights gathered from their massive data stores not just to become more efficient and profitable in their existing lines of business but also to actually change their business models.

For example, product companies could shield themselves from the harsh light of comparison shopping by offering the use of their products as a service, with sensors on those products sending the company a constant stream of data about when they need to be repaired or replaced. Customers are spared the hassle of dealing with worn-out products, and companies are protected from competition as long as customers receive the features, price, and the level of service they expect. Further, companies can continuously gather and analyze data about customers’ usage patterns and equipment performance to find ways to lower costs and develop new services.

Data for All

Given the tremendous amount of hype that has surrounded Big Data for years now, it’s tempting to dismiss data lakes as a small step forward in an already familiar technology realm. But it’s not the technology that matters as much as what it enables organizations to do. By making data available to anyone who needs it, for as long as they need it, data lakes are a powerful lever for innovation and disruption across industries.

“Companies that do not actively invest in data lakes will truly be left behind,” says Anita Raj, principal growth hacker at DataRPM, which sells predictive maintenance applications to manufacturers that want to take advantage of these massive data stores. “So it’s just the option of disrupt or be disrupted.” D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


About the Authors:

Timo Elliott is Vice President, Global Innovation Evangelist, at SAP.

John Schitka is Senior Director, Solution Marketing, Big Data Analytics, at SAP.

Michael Eacrett is Vice President, Product Management, Big Data, Enterprise Information Management, and SAP Vora, at SAP.

Carolyn Marsan is a freelance writer who focuses on business and technology topics.

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Marketing Car Sharing & Mobility 2.0 | Ep. 15 Rethink Podcast

March 19, 2017   CRM News and Info
Marketing Car Sharing Mobility  351x200 Marketing Car Sharing & Mobility 2.0 | Ep. 15 Rethink Podcast

What are Your Promotion Channels?

Nathan:

How do you communicate that to your different audiences? Because it seems traditional car advertising is done on big TV commercials and stuff like that. What are the marketing tactics and strategies – our audience tends to be marketers, and so this is what they’re curious about – how would they get their message out if they were marketing? If they were in charge, how would they be doing it?

Steve:

We try to do an interesting mix. You’re right, BMW is known for great commercials, beautiful cars, and that sort of traditional, almost stereotypical, automobile advertising. Beautiful people driving beautiful cars in beautiful places. And, again, it goes back to that aspiration idea that I just mentioned. We just released the new 5 series. We hired Clive Owen; we literally made a short film. And if you watch that film ‒ please go find it and watch it, because we end up blowing up cars. There are helicopters, and there are special effects, and there are bullet holes in the car, and it’s an action film in about 15 minutes. It’s amazing.

I don’t have that budget. I’m part of BMW. Remember, let’s go back to this: I’m a startup with a rich German uncle. That rich German uncle does not give me an unlimited marketing budget. I can’t just go buy customers. I’m just like any other startup in that respect. For us it is a combination. When we launch in a new city, we tend to do more things like out-of-home advertising and really trying to build awareness where people are, whether that’s near transit hubs, or near places where there are people who maybe are already used to using other forms of transportation and aren’t relying on their car every day. We look at how do we reach out to people via radio ads, maybe in a city, and try to be local.

Beyond that, we do a lot of digital. We’re doing more and more targeting of people who fit the profile. Say maybe they’ve liked or they’ve used mobile ads, maybe they’ve got other apps that fit into this mobility services category on their phone, and we’re really trying to find those people and introduce them to what we’re doing at ReachNow, and tell them why we might be something to fit in with their transportation needs. Because our competition is the other services you might think about. In Seattle, we just kicked off our own ReachNow ride service. It’s a pilot. But it’s a single app integrated with our car sharing app, and it means you can find a car and drive it yourself, or you can hit a button and I’ll send a professional driver in an X1 or a 330 to come pick you up and take you where you want to go, similar to services like an Uber or Lyft.

I’m competing with those guys. I’m competing with the other car sharing services. I’m competing with walking, and biking, and busing, and driving your own car. All of those are substitutes. And I’ve got to find a way to convince you that, for what you need in the moment, this is the right solution for you. And I think that’s something we’re working really hard to do.

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Micron on the Role of Memory in Digital Transformation, AI, VR, Mobility and IoT

March 3, 2017   Mobile and Cloud
hqdefault Micron on the Role of Memory in Digital Transformation, AI, VR, Mobility and IoT

Have any of you spent time considering how digital transformation, artificial intelligence, IoT, mobility and virtual and augmented reality are impacted by computer memory? Me neither until this week at GSMA’s Mobile World Congress 2017 in Barcelona.  I had the privilege of interviewing Micron Technologies’ Gino Skulick, II and getting educated on it.  Very cool information!!!


Download my latest tech trends report with charts and data sources here:  https://www.cognizant.com/FoW/twa-hyper-digital-transformation-codex2478.pdf
Follow Kevin Benedict on Twitter @krbenedict, or read more of his articles on digital transformation strategies here:
  1. Artificial Intelligence Out of Doors in the Kingdom of Robots
  2. How Digital Leaders are Different
  3. The Three Tsunamis of Digital Transformation – Be Prepared!
  4. Bots, AI and the Next 40 Months
  5. You Only Have 40 Months to Digitally Transform
  6. Digital Technologies and the Greater Good
  7. Video Report: 40 Months of Hyper-Digital Transformation
  8. Report: 40 Months of Hyper-Digital Transformation
  9. Virtual Moves to Real in with Sensors and Digital Transformation
  10. Technology Must Disappear in 2017
  11. Merging Humans with AI and Machine Learning Systems
  12. In Defense of the Human Experience in a Digital World
  13. Profits that Kill in the Age of Digital Transformation
  14. Competing in Future Time and Digital Transformation
  15. Digital Hope and Redemption in the Digital Age
  16. Digital Transformation and the Role of Faster
  17. Digital Transformation and the Law of Thermodynamics
  18. Jettison the Heavy Baggage and Digitally Transform
  19. Digital Transformation – The Dark Side
  20. Business is Not as Usual in Digital Transformation
  21. 15 Rules for Winning in Digital Transformation
  22. The End Goal of Digital Transformation
  23. Digital Transformation and the Ignorance Penalty
  24. Surviving the Three Ages of Digital Transformation
  25. The Advantages of an Advantage in Digital Transformation
  26. From Digital to Hyper-Transformation
  27. Believers, Non-Believers and Digital Transformation
  28. Forces Driving the Digital Transformation Era
  29. Digital Transformation Requires Agility and Energy Measurement
  30. A Doctrine for Digital Transformation is Required
  31. Digital Transformation and Its Role in Mobility and Competition
  32. Digital Transformation – A Revolution in Precision Through IoT, Analytics and Mobility
  33. Competing in Digital Transformation and Mobility
  34. Ambiguity and Digital Transformation
  35. Digital Transformation and Mobility – Macro-Forces and Timing
  36. Mobile and IoT Technologies are Inside the Curve of Human Time



************************************************************************

Kevin Benedict
Senior Analyst, Center for the Future of Work, Cognizant
View my profile on LinkedIn
Follow me on Twitter @krbenedict
Subscribe to Kevin’s YouTube Channel
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Join the Google+ Community Mobile Enterprise Strategies


***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.
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