Tag Archives: Software

Software Performance Issues? It Might be Your Architecture.

Here at Sisense we support high-availability, multi-server deployments for scalability and flexibility. In fact, these deployments are ready to go, out of the box and are common at most of our customer’s sites.

While this type of deployment meets the performance demands of most customers, we recently had a large customer come to us wanting to get even more out of their system. We decided to customize a solution using out of the box Sisense capabilities to meet their specific requirements.

Here’s what we did.

Step 1: Investigate

If we take a look at a common architecture schema with a high availability environment, you may find, for example, a database layer, a build layer with one build node, a query and web layer with two query nodes and two web nodes, and a load balancer. Just like the image below:

scen1HA Software Performance Issues? It Might be Your Architecture.

In an environment like this, an end user sends a request through the load balancer to one of the two web nodes, with no discretion to which they are using. By default, the web nodes then run the query on one of the two query nodes and return the response to the request to the end user.

It’s important to keep in mind that each query node stores every query in the machine’s memory. So, let’s say that each of the query nodes has 500GB of RAM. Once the node gets to a predetermined threshold of RAM space left, the server automatically starts to clean up the queries to free up available RAM.

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Step 2: Brainstorm

Therein lies our question: Why is there lag time in answering a query if the query nodes clear their cache once RAM reaches a maximum capacity? How can we reduce frequency without purchasing more RAM space?

started by mapping and roughly measuring the dashboards and how much RAM was utilized when queried. Because both of the query nodes have ~500GB of RAM in our example, I wanted to understand how much of it will be utilized and how often the cleaning process will occur. For example:

Dashoard Number Type Capacity
1 Customer Churn 100 GB
2 Finance 50 GB
3 Sales 35 GB
4 Help Desk Tickets 100 GB
5 Executive 50 GB
6 Leads Analysis 60 GB
7 Lead Generation 400 GB
8 Customer Satisfaction 200 GB

After listing out the dashboards and realizing that the total capacity is less than 1TB, I needed to look at the actual functionality of the different nodes. Each web node has the same metadata and each query node has the same ElastiCube (Sisense’s super-fast data stores). So, when one end user asks a question and it’s directed to query node A, the answer gets “stored” there. However, if another end user asks the same question and it gets directed to query node B, it will be “stored” there too.

Ah-ha! This is not efficient. We’re storing the same answers twice on two different query nodes. This means, for example, that 5GB RAM query can take up a total of 10GB when stored on both query nodes. Moreover, this expedites the time interval for when the RAM will have to be flushed. Let’s try and reconfigure the architecture to fix it and find out.

Step 3: Test and Expand

To eliminate having the same queries saved on both query nodes’ RAM, I needed to create a structure that told the web nodes which query node to use based on which dashboard was being used.

If we use the example list of dashboards from above, I made sure that if dashboard 1, 3, 4, 6, and 8 were being used, the queries should be sent to query node A. If dashboards 2, 5, or 7 were being used, then the question should be sent to query node B. This means breaking the ElastiCube set and directing each dashboard to a dedicated query node. Doing so would eliminate our redundancy on the query layer.

For reliability purposes, if one of the query nodes is down, we want to have a fallback option that ensures all queries will succeed, even at the expense of performance. The solution was creating new ElastiCube sets like this:

Set 1: The cube on query node A is default, the cube on query node B is the fallback.

Set 2: The cube on query node B is default, the cube on query node A is the fallback.

The fallback cube does not participate in the ElastiCube Set round-robin routing and is not typically used. The fallback cube is only used when none of the other cubes in the set are available.

Now, specific queries are always routed to the same caches. Because the queries are not duplicated in both caches the available RAM across both caches is better utilized to store a larger amount of queries.

After testing this architecture and ensuring it works for all scenarios with two query nodes we expanded the capabilities to allow more than two query nodes if needed. Success!

So, What’s The Big Deal?

To put it simply: the ability to boost performance without having to add additional hardware reduces total cost of ownership. Most people can meet their performance demands with a standard high-availability set up. But for those who can’t, and who have the abilities to manage this new solution, this is an exciting discovery.

banner blog 3 Software Performance Issues? It Might be Your Architecture.

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Data as a Feature: The New Differentiator for Software Builders

iStock 639637200 e1517933445411 Data as a Feature: The New Differentiator for Software Builders

It is a great time to be alive if you are a technology consumer. The era of “there’s an app for that” has quickly evolved into the era of “there are 10 apps for that”, meaning users have more choice than ever over which applications they adopt. Lower barriers to developing and providing an application have lowered the common denominator for software builders.

With an influx of new applications, product managers are having to find creative new ways to differentiate their offerings from the pack. User experience has proven to be one of the new differentiators and, in many in cases, is perceived as more important to users than core features and capabilities. In the new era of software, the best applications—the ones that stick—are those that pair great user experience with the powerful potential that lies within data. The best applications treat data as a feature of their product or service.

What exactly is “data as a feature”? It is the act and process of treating data as a core component of an application in a way that delivers value to the end user. One of the primary drivers for any product manager is to build a product that helps users achieve a goal or set of goals. When designed and packaged in the right way, data is a potent asset that allows users to reach goals and appreciate the full value of an application.

Need proof? Look at consumer applications like Mint.com and Strava—two of the most successful apps in their respective domains. Mint.com took the traditionally difficult task of deciphering financial information and made it easy for virtually any user to intelligently manage their finances. Strava accomplished the same feat in the world of personal fitness by allowing users to train smarter and reach cycling and running goals. Both applications provide highly visual interfaces that allow users of any competency to intuitively interact with data. Having these data experiences within the context of the application allows users to not only consume helpful insights, but act on those insights at the point of consumption.

And although data as a feature started in consumer products, business applications are capitalizing on the same practice as well. The HR & Finance application, Workday, uses thoughtfully designed charts and visualizations to give its non-technical, non-analyst users the power to make data-driven decisions around recruiting and workforce management.

Software product managers are a rare breed. Not many people have the creative vision, technical chops, and pragmatic decision-making skills that come with the job of product management. To meet demands of the next generation of application users, product managers must employ all of these weapons and look for new ways to differentiate their products from an increasingly crowded market. With a surplus of data at our disposal, many software builders are unknowingly sitting on gold mines of untapped data that can be unlocked for their users. By treating data as a feature, product managers can make stickier applications by helping users reach goals faster and more confidently with data.

To explore the concept of data as a feature and learn key considerations around embedded analytics, download the complimentary new O’Reilly eBook, Data as a Feature: A Guide for Product Managers.

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G2 Crowd Names NetSuite a Leader in PSA Software

By Jack Bryant, Services Industry Marketing Lead

Tally up one more for NetSuite. After garnering most of the accolades from independent analysts at the end of 2017, NetSuite has started the year off strong by being named a Leader in the G2 PSA Winter 2018 Report.

G2 Crowd is a leading peer-to-peer review platform for business software. Their research reports and vendor comparisons are based on user ratings and social data.

NetSuite%20PSA%20Infographic%20Final 2 G2 Crowd Names NetSuite a Leader in PSA Software

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Sequoia China leads $40 million round in DataVisor’s fraud detection software

 Sequoia China leads $40 million round in DataVisor’s fraud detection software

DataVisor, which provides fraud detection software, announced today that it has raised $ 40 million in a round led by Sequoia Capital China. Existing investors New Enterprise Associates (NEA) and GSR Ventures also joined.

The software analyzes client data and uses machine learning to identify fraudulent transactions, spam and abuse, identity theft, application fraud, insider abuse, money laundering, and more. It is sold on a subscription basis and can be deployed either on the cloud or in a private datacenter.

The Mountain View, California-based startup uses a technique known as unsupervised machine learning to detect those fraudulent transactions. Unsupervised learning aims to detect patterns within data without first being provided a set of labels for how to categorize that information.

Cofounders Yinglian Xie and Fang Yu spent several years working on computer security at Microsoft Research before founding DataVisor in December 2013.

They shared that the startup has more than 30 customers globally, including Alibaba Group, Cheetah Mobile, Pinterest, Tokopedia, and Yelp.

In this day and age of digital transactions and cloud-based data, cybersecurity is a big concern for companies around the world. Other startups trying to tackle this issue include Feedzai and Sift Science.

To date, DataVisor has raised a total of $ 54.5 million in disclosed funding. The Series B amount led by Genesis Capital is undisclosed.

DataVisor will use the fresh injection of capital to increase sales and marketing efforts, hire more engineers, and build out product lines to address new use cases.

Rock Wang, managing director at Sequoia China, will join DataVisor’s board of directors. Sequoia Capital’s China arm, which was founded in 2005, is reportedly raising up to 15 billion yuan ($ 2.37 billion) in its fifth fund to invest in local startups. It is also actively tapping potential Chinese investors for Sequoia Capital’s next big global fund.

Legendary Sequoia partner Michael Moritz certainly seems to admire China’s entrepreneurial zeal, something he made quite clear in a recent op-ed he wrote in the Financial Times. The piece has stirred quite a debate in Silicon Valley.

DataVisor currently has 75 employees across its Mountain View headquarters and offices in Shanghai and Beijing.

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Field Service Mobile Forms and Checklists with FIELDBOSS Software

CRM Blog Field Service Mobile Forms and Checklists with FIELDBOSS Software

Despite the technological advances that have led to the widespread adoption of mobile devices in the field service industry, many field service businesses still rely on paper forms and checklists. Replacing paper-based forms and checklists for maintenance, service, and inspections with customized field service mobile forms and checklists empowers you to drive the standardization of processes and procedures across the whole organization. This way the technician can follow and document approved maintenance or service procedures, including the performance of tests and collection of data, while on-site and automatically send it back to the office or the customer.

FIELDBOSS’s automated field service mobile forms and checklists enable your field team to easily capture required information, add notes and pictures and go completely paperless while streamlining workflow for inspections and maintenance schedules with an easy to follow to-do list.

The benefits of mobile forms and checklists:

    Every business is unique and so too are their forms and checklists. Configuration is not only industry-specific but also individual checklists for different kinds of service calls can be created, allowing for even greater configuration and customization.
    Additional questions or actions are prompted based on the technician’s answers.
    With so many different pieces of equipment, rules, and ever-changing regulations, it can be hard to stay on top of what needs to be done. Automated checklists mean no step is ever skipped and you will always be compliant. No violations. No fines.
    Have checklists automatically applied to inspection or maintenance work orders so technician has easy access?
    Mandatory fields ensure no part of the inspection or procedure is missed before a work order is closed out.
    Removing the need for a technician to return to the office to hand in paperwork allows for more time spent with customers in the field.
    With the ability to customize forms and utilize automatic calculations, submitted data is always accurate and instantaneous. Technicians can also note when each task is completed, and follow up with pictures and notes.
    Allows crucial field data to be synched in real-time and easily accessed across your organization by various team members, departments, and their systems.

FIELDBOSS’s mobile forms and checklists bring greater efficiency to the technician’s time and ensure that important checklists and inspection reports are not lost in the shuffle of papers. It also means faster turnaround times for jobs to be completed and the customer to be invoiced Creating a streamlined and efficient environment lowers mistakes created in the field and brings the maintenance and inspection process into real-time allowing for all details to enter the system quickly and accurately.

Contact FIELDBOSS or request a demo to see how mobile forms and checklists can save your field service company time and money.

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Four Reasons Software Suites Enable Device Flexibility And Mobility

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.

SAP Q417 DigitalDoubles Feature3 Image3 1024x572 Four Reasons Software Suites Enable Device Flexibility And Mobility

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.

SAP Q417 DigitalDoubles Feature3 Image7 1024x572 Four Reasons Software Suites Enable Device Flexibility And Mobility

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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Digitalist Magazine

The impact of self-learning software now and in the foreseeable future

 The impact of self learning software now and in the foreseeable future

We’ve spent so long wringing our hands and worrying about artificial and virtual intelligence that we forgot to roll out the welcome mat when they finally arrived.

Now, when major tech companies give their annual keynotes, they can’t help but pepper the narrative with phrases like “machine learning.” What does it all mean, though? Should we crank up the worry now that it looks like every tent-pole feature of self-learning software could also be a critical flaw?

The future is here — and it’s equal parts excitingand terrifying. Now that our world is populated with computer programs that can teach themselves new tricks, how will things change? What’s still worth worrying about?

Self-learning software for business and personal use

With 2018 upon us, the worlds of both business and personal software are ramping up to make the next few years something of an artificial intelligence arms race. On the consumer side of things, machine learning and AI make our lives easier in small ways. Case in point: many of us now have a smart speaker like an Amazon Echo or Google Home sitting on our countertops.

While these kinds of AI applications are helpful and entertaining, their self-learning capabilities are limited, to say the least.

In the world of business, there’s more immediate potential for self-learning software.

“We are drowning in information,” says Vita Vasylyeva of Artsyl Technologies. “The biggest bottlenecks in any business process involve the handling of documents and manual input of data from those documents. At the heart of those bottlenecks is the transformation of unstructured content into structured data.”

Nevertheless, both the business and consumer worlds have distinct needs and roles to play, and I fully expect machine learning in both realms to grow more sophisticated and capable.

Briefly, here are three very different applications for self-learning software:

1. Smartphones: Machine learning is turning smartphones into veritable supercomputers. From learning what your face looks like by poring through your photos to delivering more timely and relevant app and location suggestions, our devices are learning who we are and what we want.

More critically, machine learning is also training modern smartphones to become better at identifying and quarantining known threat vectors such as malware and viruses. It’s not all about fun and games.

2. Medicine: Diagnostic medicine is a difficult branch of science. Some types of cancer scans currently require as many as four specialists to study and come to a consensus on treatment.

With machine learning, physicians can practice this type of diagnostic medicine much faster, more accurately, and with fewer people-hours required.

3. Marketing and business management: The marketing applications of self-learning software perfectly marry the promises and the privacy worries of machine learning.

Some industry experts predict that within 10 years, even the humblest small businesses will engage in machine learning to improve their reach.

Another critical application is the promise of easier bookkeeping and organization. Newer document- and data-capture software suites take cues from the user to automatically identify and categorize types of documents and transactions, and in the process, significantly cut down on the labor and expense of staying organized and profitable.

Naturally, this is an abridged version of the emerging opportunities machine learning represents. Nearly every industry will likely come to rely on self-learning software in the future to make modern life more efficient.

The opportunities

So why the controversy? Why are folks like Elon Musk and Stephen Hawking doing their best Chicken Little impressions about AI and machine learning? Whether or not you subscribe to their possible doomsday scenarios, it’s fairly clear by now that the vast opportunity SLS offers is counterbalanced by some legitimate concerns.

For example, a major opportunity available now is the use of smarter machines to allocate resources more efficiently. For a smaller-scale look at what this means, consider the benefits of using self-learning software to make micro-variation adjustments to the way server farms consume electricity.

The result, according to researchers, is something almost eerily alive: a kind of silicon brain switching parts of itself on and off as needed to conserve basic resources. It’s the sort of thing that could help us come to terms with global warming and the sixth mass extinction in progress.

Removing the error-prone human element from the operation of automobiles is another huge opportunity made possible by machine learning. According to firsthand reports, the uncanniness of flying down a highway at 65 mph while an algorithm does the piloting wears off after a short while. Self-driving cars, in other words, are the future.

Alongside improved battery technology, we stand to benefit by dramatically slashing or eliminating our use of fossil fuels by making our commutes and traffic jams more efficient, and nonexistent, respectively. Cars of the future will be able to communicate with each other and pool data on things like road construction, obstructions, weather, and emerging incidents that could affect the drive.

The risks

Every one of the features above represents some type of privacy concern. Siri, Bixby, Cortana, and Google can’t perform their magic tricks without gathering data about their users.

Every tech giant that oversees these virtually intelligent personal assistants seems to take a different tack on user privacy. Your smartphone will send various types of personal data to distant server farms for processing each time you make an inquiry. What that company does with the information from there — and who they sell it to — is the stuff of terms of service fine print.

Beyond privacy, the other very real concerns about self-learning software are all about the consequences of removing human judgment — and in some cases emotion — from critically human experiences and interactions.

Wells Fargo and other major financial institutions wish to use artificial intelligence to dispassionately come to conclusions about their customers’ creditworthiness, for example — an idea that will either eliminate or greatly worsen preexisting cultural biases.

As far as self-driving cars go, a major learning curve is making ourselves comfortable with a world where our cars can solve the grisly “trolley problem” to our satisfaction. Are we comfortable writing software for a car that instructs the vehicle to end a human life to save five others?

Humans have historically had to bear the weight of that moral calculus — or didn’t have time to perform it at all in the vital split-seconds before a car crash. For better and worse, it seems machines can now do some of our ethical moralizings for us.

As you can see, determining the direction of where AI innovation will take us is a complex issue — but one that’s chock-full of potential.

The trick is getting scientists, philosophers, business leaders, citizens, and politicians on the same page.

Kayla Matthews is Senior Writer for MakeUseOf. Her work has also appeared on VICE, The Next Web, The Week, and TechnoBuffalo.

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Big Data – VentureBeat

Gaming companies outsmart DDoS attack with new software security solutions

 Gaming companies outsmart DDoS attack with new software security solutions

New releases in the online gaming industry are highly anticipated events. Millions of gamers anxiously waiting to leap onto a shiny new game service is an irresistible target for hackers—with bragging rights being the prize. But for the gaming companies, suffering a DDoS attack is a disaster with immediate loss of revenue, mitigation costs and long-term consequences for their brand. Fortunately, new approaches to security based on multi-dimensional analytics and traffic modeling using big data are changing how this game is played.

The DDoS danger

Global gaming companies build excitement with big, heavily-marketed release dates. This brings millions of players online at the exact same time. During these traffic surges, gaming companies also see a surge of distributed denial of service (DDoS) attacks. Being able to surgically shutting down the attacks without disrupting service is critical.

Successful DDoS attacks can have immediate revenue implications, but more importantly, they hurt their customer base—and even a small number of grumpy gamers can do a lot of damage to the brand online. Growing the player base is essential for having a healthy game launch, especially in the highly competitive gaming industry. So losing customers due to an inaccessible service or bad PR can have serious consequences for any game — just look at Diablo 3, which took years to recover from its self-inflicted “Error 37” fiasco.

Gaming companies generally operate worldwide, serving millions of users. To avoid latency, they distribute their platforms onto multiple region-based servers. DDOS attacks can attack all or some of these servers concurrently, or can focus the attack on different layers of the service to weaken it to the point of being unusable.

A multi-vector attack might, for instance, use hijacked Internet of Things (IoT) devices reprogrammed to participate in the attack as well as hundreds of cloud servers with 10 Gbps uplinks to launch a simultaneous TCP/IP attack, as occurred in last year’s infamous DYN attack.

The outdated defense

Hardware mitigation solutions were not designed for the cloud and IoT era and are, unfortunately, too simplistic to keep up with these types of sophisticated threats.

When gaming companies suffer these DDoS attacks, the current common defense is to backhaul all traffic suspected of being infected to a scrubbing center where racks of purpose-built mitigation machines clean it in a single pass through. Attack detection starts with a baseline measure for what constitutes “normal” and then looks for anomalies, such as sudden large spikes in traffic. The affected traffic is then re-directed and backhauled to the scrubbers.

There is nothing elegant about this approach; it is slow and it suffers from a lot of false positives, meaning the unnecessary backhauling of large amounts of uninfected traffic. The detection hardware lacks the raw compute power required to perform the additional analytics needed to separate out the false positives. And, as the scale of DDoS attacks escalates, these inefficiencies become increasingly costly to gaming companies, since the system has to spend resources fighting phantom attacks, instead of identifying and dealing with other attack vectors.

A more efficient solution

A more elegant and faster approach exists using software-based multi-dimensional analytics, making detection more precise. They combine real-time network telemetry with advanced network analytics and other data such as DNS and BGP (among others) to see down to the source of attack traffic in real time.

Multi-dimensional analytics provide visibility into cloud applications and services and can instantly identify where the traffic is originating, determining whether it is friend or foe. Additionally, big data approaches to traffic modeling can help compare a potential event to past attack profiles and be more precise about what degree of variability from ‘normal’ is OK.

Armed with this kind of analysis, it becomes possible to create simple, effective filters at the peering edge of the network for the zombie PCs, IoT devices and/or cloud servers that are carrying out the attack. The offending traffic doesn’t have to be sent to the scrubbers; it is simply blocked at the edge. And every vector of the attack can be identified, pinpointing the attack endpoints and allowing for surgically precise mitigation. The ability to identify the endpoints of the attack in real-time means that rapidly changing attack vectors can also be identified and counteracted as the attackers attempt to play cat and mouse with network security operations.

This is a high stakes game that is escalating with the spread of inexpensive, insecure cloud services (<10 GB) and IoT devices. DDoS botnets have evolved beyond infecting PCs and now use IoT devices and Linux servers in the cloud. This new arsenal of weapons is giving hackers a completely different level of power than they’ve had before.

Fortunately, software security solutions built around deep network analytics and big data techniques are also game changers. For those gaming companies that have employed them, they can meet the threats with confidence, for now, with the winning approach.

Naim Falandino is Chief Scientist at Nokia Deepfield with expertise in real-time analytics, machine learning, and information visualization.

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Big Data – VentureBeat

How CRM Software Can Save Time And Money

In the tech world in 2017, several trends emerged as signals amid the noise, signifying much larger changes to come.

As we noted in last year’s More Than Noise list, things are changing—and the changes are occurring in ways that don’t necessarily fit into the prevailing narrative.

While many of 2017’s signals have a dark tint to them, perhaps reflecting the times we live in, we have sought out some rays of light to illuminate the way forward. The following signals differ considerably, but understanding them can help guide businesses in the right direction for 2018 and beyond.

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When a team of psychologists, linguists, and software engineers created Woebot, an AI chatbot that helps people learn cognitive behavioral therapy techniques for managing mental health issues like anxiety and depression, they did something unusual, at least when it comes to chatbots: they submitted it for peer review.

Stanford University researchers recruited a sample group of 70 college-age participants on social media to take part in a randomized control study of Woebot. The researchers found that their creation was useful for improving anxiety and depression symptoms. A study of the user interaction with the bot was submitted for peer review and published in the Journal of Medical Internet Research Mental Health in June 2017.

While Woebot may not revolutionize the field of psychology, it could change the way we view AI development. Well-known figures such as Elon Musk and Bill Gates have expressed concerns that artificial intelligence is essentially ungovernable. Peer review, such as with the Stanford study, is one way to approach this challenge and figure out how to properly evaluate and find a place for these software programs.

The healthcare community could be onto something. We’ve already seen instances where AI chatbots have spun out of control, such as when internet trolls trained Microsoft’s Tay to become a hate-spewing misanthrope. Bots are only as good as their design; making sure they stay on message and don’t act in unexpected ways is crucial.

SAP Q417 DigitalDoubles Feature1 Image3 How CRM Software Can Save Time And MoneyThis is especially true in healthcare. When chatbots are offering therapeutic services, they must be properly designed, vetted, and tested to maintain patient safety.

It may be prudent to apply the same level of caution to a business setting. By treating chatbots as if they’re akin to medicine or drugs, we have a model for thorough vetting that, while not perfect, is generally effective and time tested.

It may seem like overkill to think of chatbots that manage pizza orders or help resolve parking tickets as potential health threats. But it’s already clear that AI can have unintended side effects that could extend far beyond Tay’s loathsome behavior.

For example, in July, Facebook shut down an experiment where it challenged two AIs to negotiate with each other over a trade. When the experiment began, the two chatbots quickly went rogue, developing linguistic shortcuts to reduce negotiating time and leaving their creators unable to understand what they were saying.

The implications are chilling. Do we want AIs interacting in a secret language because designers didn’t fully understand what they were designing?

In this context, the healthcare community’s conservative approach doesn’t seem so farfetched. Woebot could ultimately become an example of the kind of oversight that’s needed for all AIs.

Meanwhile, it’s clear that chatbots have great potential in healthcare—not just for treating mental health issues but for helping patients understand symptoms, build treatment regimens, and more. They could also help unclog barriers to healthcare, which is plagued worldwide by high prices, long wait times, and other challenges. While they are not a substitute for actual humans, chatbots can be used by anyone with a computer or smartphone, 24 hours a day, seven days a week, regardless of financial status.

Finding the right governance for AI development won’t happen overnight. But peer review, extensive internal quality analysis, and other processes will go a long way to ensuring bots function as expected. Otherwise, companies and their customers could pay a big price.

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Elon Musk is an expert at dominating the news cycle with his sci-fi premonitions about space travel and high-speed hyperloops. However, he captured media attention in Australia in April 2017 for something much more down to earth: how to deal with blackouts and power outages.

In 2016, a massive blackout hit the state of South Australia following a storm. Although power was restored quickly in Adelaide, the capital, people in the wide stretches of arid desert that surround it spent days waiting for the power to return. That hit South Australia’s wine and livestock industries especially hard.

South Australia’s electrical grid currently gets more than half of its energy from wind and solar, with coal and gas plants acting as backups for when the sun hides or the wind doesn’t blow, according to ABC News Australia. But this network is vulnerable to sudden loss of generation—which is exactly what happened in the storm that caused the 2016 blackout, when tornadoes ripped through some key transmission lines. Getting the system back on stable footing has been an issue ever since.

Displaying his usual talent for showmanship, Musk stepped in and promised to build the world’s largest battery to store backup energy for the network—and he pledged to complete it within 100 days of signing the contract or the battery would be free. Pen met paper with South Australia and French utility Neoen in September. As of press time in November, construction was underway.

For South Australia, the Tesla deal offers an easy and secure way to store renewable energy. Tesla’s 129 MWh battery will be the most powerful battery system in the world by 60% once completed, according to Gizmodo. The battery, which is stationed at a wind farm, will cover temporary drops in wind power and kick in to help conventional gas and coal plants balance generation with demand across the network. South Australian citizens and politicians largely support the project, which Tesla claims will be able to power 30,000 homes.

Until Musk made his bold promise, batteries did not figure much in renewable energy networks, mostly because they just aren’t that good. They have limited charges, are difficult to build, and are difficult to manage. Utilities also worry about relying on the same lithium-ion battery technology as cellphone makers like Samsung, whose Galaxy Note 7 had to be recalled in 2016 after some defective batteries burst into flames, according to CNET.

SAP Q417 DigitalDoubles Feature1 Image5 How CRM Software Can Save Time And MoneyHowever, when made right, the batteries are safe. It’s just that they’ve traditionally been too expensive for large-scale uses such as renewable power storage. But battery innovations such as Tesla’s could radically change how we power the economy. According to a study that appeared this year in Nature, the continued drop in the cost of battery storage has made renewable energy price-competitive with traditional fossil fuels.

This is a massive shift. Or, as David Roberts of news site Vox puts it, “Batteries are soon going to disrupt power markets at all scales.” Furthermore, if the cost of batteries continues to drop, supply chains could experience radical energy cost savings. This could disrupt energy utilities, manufacturing, transportation, and construction, to name just a few, and create many opportunities while changing established business models. (For more on how renewable energy will affect business, read the feature “Tick Tock” in this issue.)

Battery research and development has become big business. Thanks to electric cars and powerful smartphones, there has been incredible pressure to make more powerful batteries that last longer between charges.

The proof of this is in the R&D funding pudding. A Brookings Institution report notes that both the Chinese and U.S. governments offer generous subsidies for lithium-ion battery advancement. Automakers such as Daimler and BMW have established divisions marketing residential and commercial energy storage products. Boeing, Airbus, Rolls-Royce, and General Electric are all experimenting with various electric propulsion systems for aircraft—which means that hybrid airplanes are also a possibility.

Meanwhile, governments around the world are accelerating battery research investment by banning internal combustion vehicles. Britain, France, India, and Norway are seeking to go all electric as early as 2025 and by 2040 at the latest.

In the meantime, expect huge investment and new battery innovation from interested parties across industries that all share a stake in the outcome. This past September, for example, Volkswagen announced a €50 billion research investment in batteries to help bring 300 electric vehicle models to market by 2030.

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At first, it sounds like a narrative device from a science fiction novel or a particularly bad urban legend.

Powerful cameras in several Chinese cities capture photographs of jaywalkers as they cross the street and, several minutes later, display their photograph, name, and home address on a large screen posted at the intersection. Several days later, a summons appears in the offender’s mailbox demanding payment of a fine or fulfillment of community service.

As Orwellian as it seems, this technology is very real for residents of Jinan and several other Chinese cities. According to a Xinhua interview with Li Yong of the Jinan traffic police, “Since the new technology has been adopted, the cases of jaywalking have been reduced from 200 to 20 each day at the major intersection of Jingshi and Shungeng roads.”

The sophisticated cameras and facial recognition systems already used in China—and their near–real-time public shaming—are an example of how machine learning, mobile phone surveillance, and internet activity tracking are being used to censor and control populations. Most worryingly, the prospect of real-time surveillance makes running surveillance states such as the former East Germany and current North Korea much more financially efficient.

According to a 2015 discussion paper by the Institute for the Study of Labor, a German research center, by the 1980s almost 0.5% of the East German population was directly employed by the Stasi, the country’s state security service and secret police—1 for every 166 citizens. An additional 1.1% of the population (1 for every 66 citizens) were working as unofficial informers, which represented a massive economic drain. Automated, real-time, algorithm-driven monitoring could potentially drive the cost of controlling the population down substantially in police states—and elsewhere.

We could see a radical new era of censorship that is much more manipulative than anything that has come before. Previously, dissidents were identified when investigators manually combed through photos, read writings, or listened in on phone calls. Real-time algorithmic monitoring means that acts of perceived defiance can be identified and deleted in the moment and their perpetrators marked for swift judgment before they can make an impression on others.

SAP Q417 DigitalDoubles Feature1 Image7 How CRM Software Can Save Time And MoneyBusinesses need to be aware of the wider trend toward real-time, automated censorship and how it might be used in both commercial and governmental settings. These tools can easily be used in countries with unstable political dynamics and could become a real concern for businesses that operate across borders. Businesses must learn to educate and protect employees when technology can censor and punish in real time.

Indeed, the technologies used for this kind of repression could be easily adapted from those that have already been developed for businesses. For instance, both Facebook and Google use near–real-time facial identification algorithms that automatically identify people in images uploaded by users—which helps the companies build out their social graphs and target users with profitable advertisements. Automated algorithms also flag Facebook posts that potentially violate the company’s terms of service.

China is already using these technologies to control its own people in ways that are largely hidden to outsiders.

According to a report by the University of Toronto’s Citizen Lab, the popular Chinese social network WeChat operates under a policy its authors call “One App, Two Systems.” Users with Chinese phone numbers are subjected to dynamic keyword censorship that changes depending on current events and whether a user is in a private chat or in a group. Depending on the political winds, users are blocked from accessing a range of websites that report critically on China through WeChat’s internal browser. Non-Chinese users, however, are not subject to any of these restrictions.

The censorship is also designed to be invisible. Messages are blocked without any user notification, and China has intermittently blocked WhatsApp and other foreign social networks. As a result, Chinese users are steered toward national social networks, which are more compliant with government pressure.

China’s policies play into a larger global trend: the nationalization of the internet. China, Russia, the European Union, and the United States have all adopted different approaches to censorship, user privacy, and surveillance. Although there are social networks such as WeChat or Russia’s VKontakte that are popular in primarily one country, nationalizing the internet challenges users of multinational services such as Facebook and YouTube. These different approaches, which impact everything from data safe harbor laws to legal consequences for posting inflammatory material, have implications for businesses working in multiple countries, as well.

For instance, Twitter is legally obligated to hide Nazi and neo-fascist imagery and some tweets in Germany and France—but not elsewhere. YouTube was officially banned in Turkey for two years because of videos a Turkish court deemed “insulting to the memory of Mustafa Kemal Atatürk,” father of modern Turkey. In Russia, Google must keep Russian users’ personal data on servers located inside Russia to comply with government policy.

While China is a pioneer in the field of instant censorship, tech companies in the United States are matching China’s progress, which could potentially have a chilling effect on democracy. In 2016, Apple applied for a patent on technology that censors audio streams in real time—automating the previously manual process of censoring curse words in streaming audio.

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In March, after U.S. President Donald Trump told Fox News, “I think maybe I wouldn’t be [president] if it wasn’t for Twitter,” Twitter founder Evan “Ev” Williams did something highly unusual for the creator of a massive social network.

He apologized.

Speaking with David Streitfeld of The New York Times, Williams said, “It’s a very bad thing, Twitter’s role in that. If it’s true that he wouldn’t be president if it weren’t for Twitter, then yeah, I’m sorry.”

Entrepreneurs tend to be very proud of their innovations. Williams, however, offers a far more ambivalent response to his creation’s success. Much of the 2016 presidential election’s rancor was fueled by Twitter, and the instant gratification of Twitter attracts trolls, bullies, and bigots just as easily as it attracts politicians, celebrities, comedians, and sports fans.

Services such as Twitter, Facebook, YouTube, and Instagram are designed through a mix of look and feel, algorithmic wizardry, and psychological techniques to hang on to users for as long as possible—which helps the services sell more advertisements and make more money. Toxic political discourse and online harassment are unintended side effects of the economic-driven urge to keep users engaged no matter what.

Keeping users’ eyeballs on their screens requires endless hours of multivariate testing, user research, and algorithm refinement. For instance, Casey Newton of tech publication The Verge notes that Google Brain, Google’s AI division, plays a key part in generating YouTube’s video recommendations.

According to Jim McFadden, the technical lead for YouTube recommendations, “Before, if I watch this video from a comedian, our recommendations were pretty good at saying, here’s another one just like it,” he told Newton. “But the Google Brain model figures out other comedians who are similar but not exactly the same—even more adjacent relationships. It’s able to see patterns that are less obvious.”

SAP Q417 DigitalDoubles Feature1 Image9 How CRM Software Can Save Time And MoneyA never-ending flow of content that is interesting without being repetitive is harder to resist. With users glued to online services, addiction and other behavioral problems occur to an unhealthy degree. According to a 2016 poll by nonprofit research company Common Sense Media, 50% of American teenagers believe they are addicted to their smartphones.

This pattern is extending into the workplace. Seventy-five percent of companies told research company Harris Poll in 2016 that two or more hours a day are lost in productivity because employees are distracted. The number one reason? Cellphones and texting, according to 55% of those companies surveyed. Another 41% pointed to the internet.

Tristan Harris, a former design ethicist at Google, argues that many product designers for online services try to exploit psychological vulnerabilities in a bid to keep users engaged for longer periods. Harris refers to an iPhone as “a slot machine in my pocket” and argues that user interface (UI) and user experience (UX) designers need to adopt something akin to a Hippocratic Oath to stop exploiting users’ psychological vulnerabilities.

In fact, there is an entire school of study devoted to “dark UX”—small design tweaks to increase profits. These can be as innocuous as a “Buy Now” button in a visually pleasing color or as controversial as when Facebook tweaked its algorithm in 2012 to show a randomly selected group of almost 700,000 users (who had not given their permission) newsfeeds that skewed more positive to some users and more negative to others to gauge the impact on their respective emotional states, according to an article in Wired.

As computers, smartphones, and televisions come ever closer to convergence, these issues matter increasingly to businesses. Some of the universal side effects of addiction are lost productivity at work and poor health. Businesses should offer training and help for employees who can’t stop checking their smartphones.

Mindfulness-centered mobile apps such as Headspace, Calm, and Forest offer one way to break the habit. Users can also choose to break internet addiction by going for a walk, turning their computers off, or using tools like StayFocusd or Freedom to block addictive websites or apps.

Most importantly, companies in the business of creating tech products need to design software and hardware that discourages addictive behavior. This means avoiding bad designs that emphasize engagement metrics over human health. A world of advertising preroll showing up on smart refrigerator touchscreens at 2 a.m. benefits no one.

According to a 2014 study in Cyberpsychology, Behavior and Social Networking, approximately 6% of the world’s population suffers from internet addiction to one degree or another. As more users in emerging economies gain access to cheap data, smartphones, and laptops, that percentage will only increase. For businesses, getting a head start on stopping internet addiction will make employees happier and more productive. D!

About the Authors

Maurizio Cattaneo is Director, Delivery Execution, Energy, and Natural Resources, at SAP.

David Delaney is Global Vice President and Chief Medical Officer, SAP Health.

Volker Hildebrand is Global Vice President for SAP Hybris solutions.

Neal Ungerleider is a Los Angeles-based technology journalist and consultant.

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


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Digitalist Magazine

NetSuite Adds Container Management to Supply Chain Software

websitelogo NetSuite Adds Container Management to Supply Chain Software

Posted by Gavin Davidson, Product Marketing Director

Modern supply chain management invariably means dealing with multiple vendors, contract manufacturers and partners across multiple time zones and geographies. This often results in many of your assets ageing in-transit from one location / geography. Being able to track these is critical to maintaining your service level commitments. Consolidating your inbound shipments into common records that represent the containers they were packed into offers a number of benefits for NetSuite users and is the focus of the new Inbound Shipment Management feature that was unveiled in the 17.2 release. Inbound Shipment Management includes many enhancements that have been requested by our manufacturing, distribution and retail customers including:

  • Inbound Shipment Record
    • The new inbound shipment management record is the central element that will be used to capture all the related information. As its created and maintained, it will link the open purchase orders from potentially multiple vendors into a single record that can be used for simplified status updates until receipt.
  • Container Loading
    • Once a user generates the Inbound Shipment Management record they can easily identify the PO Items that have been loaded into the container and can filter by vendor and PO or Item while doing so. This process establishes the link between the PO Line and the container.
  • Status Updates
    • The transit time for the container can often be significant and the items contained within it might be required for multiple commitments: sales orders, further transit, assemblies etc. and so it’s important to be able to quickly and easily update the container status throughout the process. Changing the Inbound Shipment Status field on a regular basis makes everyone aware of exactly what’s happening.
  • Container Receiving
    • When the container finally reaches its destination, the entire contents can be received with a single click. Of course, if you need to make partial receipts, perhaps because unloading is scheduled to take place over a number of days, that’s also possible.
  • Landed Cost Management
    • Being able to properly apply landed costs to the items that were in the container is a critical piece of the puzzle and will continue to be enhanced over the coming releases.

All of this functionality can not only be manually updated, but it can also be automatically updated using .CSV imports, web services and SuiteScript where appropriate. All this goes to ensure our customers have complete visibility of all products at all times. Learn more about the latest NetSuite release, 17.2.

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