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F5 Networks’ acquisition of Volterra foreshadows a fight for the network edge

January 9, 2021 Big Data

A battle for control over emerging edge computing applications is heating up as enterprise IT organizations begin to move toward processing and analyzing data as close as possible to where it is being generated and consumed. The latest salvo in that contest is F5 Networks’ approximately $ 500 million acquisition of Volterra. Volterra provides a platform for managing application deployments on IT platforms. F5 Networks announced the deal yesterday.

With Volterra in its stable, F5 Networks will spend the next 12 to 18 months positioning itself as an alternative to proprietary content delivery networks for delivering application code to edge computing platforms, F5 Networks CEO François Locoh-Donou said during a conference call with analysts.

A forthcoming open Edge 2.0 platform from F5 Networks based on the Volterra platform will enable IT organizations to deploy applications to edge computing platforms without becoming locked into a specific content delivery network (CDN). “This transaction is a fundamental change to the game at the edge,” Locoh-Donou said.

At the core of Volterra’s service is VoltStack, a distribution of Kubernetes curated and managed by Volterra. Developers engage with VoltStack at the edge via Kubernetes application programming interfaces (APIs). Those Kubernetes instances are then integrated using VoltMesh, a service mesh instance Volterra built on top of open source Contrail software-defined networking (SDN) software, now known as Tungsten Fabric.

Volterra’s software-as-a-service (SaaS) platform provides the console that enables IT teams to manage those distributed computing environments.

Of course, F5 Networks is not the only IT vendor with edge computing ambitions. CDN providers ranging from Akamai, Fastly, and Cloudflare, along with cloud service providers and telecommunications carriers that now offer similar services, seek to dominate edge computing.

The challenge IT organizations face is that cloud computing services and local datacenters are simply too far away to process data in near real time. There’s too much network latency between a zone in the cloud or even a local datacenter to deliver the level of application experience required by, for example, an augmented or virtual reality application. As a result, service providers are now racing to deploy IT infrastructure in points of presence around the globe to process and analyze data in near real time.

It’s not clear at what rate organizations are currently pushing application logic out to the edge. F5 Networks expects Volterra to contribute less than $ 10 million in additional revenue this year, Locoh-Donou said. The bulk of the opportunity Volterra enables will manifest itself in 2022, he added.

F5 Networks expects to be able to compete aggressively at the edge because the Volterra approach relies primarily on open source software such as Kubernetes running on industry-standard hardware, rather than proprietary networking equipment, Locoh-Donou said.

Yesterday, the company also revealed that it estimates revenue for its first-quarter fiscal year 2021 financial results will be in the range of $ 623 million to $ 626 million, thanks in part to an approximately 68% growth in software revenue. F5 Networks also reiterated a commitment to return $ 1 billion of capital over the next two years, starting with a $ 500 million accelerated share repurchase in fiscal year 2021.

Each IT organization will have to evaluate the best path for pushing application logic out to the edge to enable user experiences in near real time. And given the amount of compute and networking horsepower being made available, they will have no shortage of options. The return on all that capital investment being made by service providers, however, may not be seen for at least several more years.

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Big Data – VentureBeat

Why TIBCO Spotfire is the Ideal Tool for Network Analytics

November 15, 2020 TIBCO Spotfire

Reading Time: 3 minutes

Any type of network downtime has a significant impact on today’s businesses. According to a recent study by Statista the average cost of IT downtime is between $ 350,000 and $ 400,000 per hour.

For this reason, IT teams rely on network analytics tools to identify key trends and patterns occurring in a network to ensure their networks perform at an optimal level.

Today, with a steep increase in network complexity and the added pressure of demand for improved reliability, there’s a need for an evolution in approach to network monitoring. IT teams need richer analytics along with monitoring to surface issues before they become problems. TIBCO Spotfire is a proven solution. Using search and recommendations powered by a built-in artificial intelligence (AI) engine, Spotfire enables you to more easily visualize new discoveries about your network.

Let’s have a look at some of the capabilities of TIBCO Spotfire that makes it an ideal tool for Network Analytics.

1. Smart, Immersive Visual Analytics

Spotfire offers a user-friendly interface providing visual tools for easy data exploration so you can quickly get insights from your data. The rich and interactive dashboards, brushlinking, and point-and-click data exploration provide powerful analytics capabilities.

Why TIBCO Spotfire is the Ideal Tool for Network Analytics

Powered by AI, Spotfire automatically recommends various visualizations for different relationships in your data, making it far faster and easier to get insights. AI recommendations help in loading, linking, categorizing, and navigating data for an overall faster analysis.
Spotfire makes it easy for analytics and business leaders to build analytical applications through a guided workflow.

2. Location Analytics

Location Analytics in Spotfire provides spatial analytics for everyone. Its depth and analytical capabilities make it easier to understand predictions and optimization through locations. Spotfire automatically adds location context to your analysis that would not be possible using traditional charts and tables.
Multi-layer maps allow you to drill down, within, and between layers to add more context to your maps for location-based insights. This can be further enriched by including other data sources and adding multiple layers to the data.

3. Real-Time Analytics

Understanding what is happening in real-time is imperative for Network Analytics. TIBCO Spotfire natively supports real time streaming data to provide real-time views into the network, enabling real time analysis.
Spotfire data streams are designed for demanding network enterprise environments with tens of millions of events a day per network, and thousands of continuous, streaming queries.

Why Your Investment in Network Analytics Demands Spotfire’s Capabilities

According to an IDC FutureScape Report, there will be an acceleration to cloud-centric technologies and edge deployments will be a top priority. These are the top two trends we could see in the near future; what weaves them together is the network health of your business. To make your business operations resilient and drive competitive advantage, you need network analytics that bring the most valuable insights to you.

The bottom line: You have to know why your network behaves the way it does. You need to be able to compare historic data with real-time data in a single environment for the most current, comprehensive view of IT networks, and for the insights into behavior that matter most. Network Analytics empowers your IT teams with information about network health, helps your leaders determine performance trends, and provides historical network data that can provide benefits for the entire enterprise.

From traffic to business initialization with application sharing, IT teams need insights to solve business problems. Network analytics pinpoints specific issues determining what, when, and how. Predictive analytics assists to potentially prevent future performance network issues if a repeated event is suggested by the data. And Spotfire shines in immersive, smart, real-time analytics, enabling predictive and even prescriptive analytics.

Powered by AI, Spotfire automatically recommends various visualizations for different relationships in your data, making it far faster and easier to get insights. Click To Tweet

Forward-thinking IT organizations are increasingly adopting solutions like TIBCO Spotfire, because of the value provided through instant AI solutions to solve real-time requirements with intelligent and automated network insights. To learn more about how to implement Network Analytics for your businesses, please contact us.

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The TIBCO Blog

DeepMind open-sources the FermiNet, a neural network that simulates electron behaviors

October 20, 2020 Big Data

In September, Alphabet’s DeepMind published a paper in the journal Physical Review Research detailing Fermionic Neural Network (FermiNet), a new neural network architecture that’s well-suited to modeling the quantum state of large collections of electrons. The FermiNet, which DeepMind claims is one of the first demonstrations of AI for computing atomic energy, is now available in open source on GitHub — and ostensibly remains one of the most accurate methods to date.

In quantum systems, particles like electrons don’t have exact locations. Their positions are instead described by a probability cloud. Representing the state of a quantum system is challenging, because probabilities have to be assigned to possible configurations of electron positions. These are encoded in the wavefunction, which assigns a positive or negative number to every configuration of electrons; the wavefunction squared gives the probability of finding the system in that configuration.

The space of possible configurations is enormous — represented as a grid with 100 points along each dimension, the number of electron configurations for the silicon atom would be larger than the number of atoms in the universe. Researchers at DeepMind believed that AI could help in this regard. They surmised that, given neural networks have historically fit high-dimensional functions in artificial intelligence problems, they could be used to represent quantum wavefunctions as well.

DeepMind open sources the FermiNet, a neural network that simulates electron behaviors

Above: Simulated electrons sampled from the FermiNet move around a bicyclobutane molecule.

By way of refresher, neural networks contain neurons (mathematical functions) arranged in layers that transmit signals from input data and slowly adjust the synaptic strength — i.e., weights — of each connection. That’s how they extract features and learn to make predictions.

Because electrons are a type of particle known as fermions, which include the building blocks of most matter (e.g., protons, neutrons, quarks, and neutrinos), their wavefunction has to be antisymmetric. (If you swap the position of two electrons, the wavefunction gets multiplied by -1, meaning that if two electrons are on top of each other, the wavefunction and the probability of that configuration will be zero.) This led the DeepMind researchers to develop a new type of neural network that was antisymmetric with respect to its inputs — the FermiNet — and that has a separate stream of information for each electron. In practice, the FermiNet averages together information from across streams and passes this information to each stream at the next layer. This way, the streams have the right symmetry properties to create an antisymmetric function.

Above: The FermiNet’s architecture.

The FermiNet picks a random selection of electron configurations, evaluates the energy locally at each arrangement of electrons, and adds up the contributions from each arrangement. Since the wavefunction squared gives the probability of observing an arrangement of particles in any location, the FermiNet can generate samples from the wavefunction directly. The inputs used to train the neural network are generated by the neural network itself, in effect.

“We think the FermiNet is the start of great things to come for the fusion of deep learning and computational quantum chemistry. Most of the systems we’ve looked at so far are well-studied and well-understood. But just as the first good results with deep learning in other fields led to a burst of follow-up work and rapid progress, we hope that the FermiNet will inspire lots of work on scaling up and many ideas for new, even better network architectures,” DeepMind wrote in a blog post. “We have … just scratched the surface of computational quantum physics, and look forward to applying the FermiNet to tough problems in material science and condensed matter physics as well. Mostly, we hope that by releasing the source code used in our experiments, we can inspire other researchers to build on our work and try out new applications we haven’t even dreamed of.”

The release of the FermiNet code comes after DeepMind demonstrated its work on an AI system that can predict the movement of glass molecules as they transition between liquid and solid states. (Both the techniques and trained models, which were also made available in open source, could be used to predict other qualities of interest in glass, DeepMind said.) Beyond glass, the researchers asserted the work yielded insights into general substance and biological transitions, and that it could lead to advances in industries like manufacturing and medicine.

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Big Data – VentureBeat

Z-Wave Long Range protocol supports up to 2,000 smart devices on a mesh network

September 9, 2020 Big Data

The Z-Wave Alliance today detailed a new specification intended to accommodate setups with thousands of devices in environments stretching hundreds of feet. The Alliance says that Z-Wave Long Range (Z-Wave LR), which supports things like door locks, garage door sensors, thermostats, and smart lightbulbs, is backward-compatible with both existing Z-Wave networks and previously installed Z-Wave devices.

Z-Wave, which was born out of Danish company Zensys and came to the U.S. in 2000, is a wireless mesh protocol for smart home, multi-unit, and hospitality use cases. It’s popular — there are an estimated 100 million Z-Wave devices installed worldwide — but ensuring complete home, building, or yard coverage historically required a repeater (or several).

Z-Wave LR eliminates this need with up to four times greater range than regular Z-Wave signals. Z-Wave LR boasts a range of 400 meters and bumps the number of supported devices to 2,000 on a single network, up from the previous limit of 232, while still operating on such low power that some sensors will last 10 years on a coin cell battery.

Gearbrain reports that three major Z-Wave Alliance companies are in alpha testing with the new specification. A Z-Wave LR beta will launch sometime in Q4 2020 so that other partners can begin developing products ahead of a general release in 2021.

In spite of the improvements, Z-Wave LR, which operates on the 800-900MHz radio frequency range, still falls short of competing protocols including Zigbee and the forthcoming Amazon Sidewalk. The 2.4GHz Zigbee supports up to 65,000 nodes at a range of up to 100 meters, while the 900MHz Sidewalk is reportedly capable of sending data up to a mile away.

But Z-Wave has the advantage of broad vendor support. The Z-Wave Alliance counts Ring, Assa Abloy, Silicon Labs, and Qolsys among its over 700 members, and an estimated 3,300 Z-Wave-enabled devices are available on the market.

The Z-Wave Alliance says the Z-Wave LR specification will be managed and certified under the Z-Wave Plus program and that technical details will be highlighted in a session at Silicon Labs’ virtual conference this week. Z-Wave Plus, which launched in 2004, included features like increased range, extended battery life, over-the-air updates, and additional radio frequency channels.

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Big Data – VentureBeat

TuSimple plans autonomous truck network backed by UPS

July 1, 2020 Big Data

Ahead of the commercial rollout of its driverless trucks by 2024, TuSimple today outlined the launch of what it’s calling the world’s first autonomous freight network. In partnership with UPS, Penske, U.S. Xpress, and McLane Company, the company plans to establish an “ecosystem” of autonomous trucks complemented by digitally mapped routes, strategically placed terminals, and a monitoring system dubbed TuSimple Connect.

TuSimple says it believes the autonomous freight network is the “safest” and “most efficient” way to bring self-driving trucks to market. As the pandemic drives unprecedented growth in the logistics and ground transportation market, Aurora, Waymo, and other rivals are investing increased resources in fully autonomous solutions.

TuSimple’s autonomous freight network will roll out in three phases. During the first — spanning this year to 2021 — TuSimple will offer delivery service between the cities of Phoenix, Tucson, El Paso, Dallas, Houston, and San Antonio. The second phase, which will begin in 2022 and end in 2023, will see an expansion in shipping from Los Angeles to Jacksonville that will connect the East with the West Coast. The third phase, starting in 2023, will grow TuSimple’s driverless operations nationwide, adding routes in 48 states and allowing customers to use TuSimple-equipped trucks on the freight network (with priority given to existing customers and companies with large orders).

Similar deployments in Europe and Asia will follow if all goes well, building upon TuSimple’s delivery pilot in Shanghai. There, as here, businesses will pay TuSimple to haul goods on their behalf.

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TuSimple already operates autonomously on seven different routes between Phoenix, Tucson, El Paso, and Dallas, and it intends to open a shipping terminal in Dallas in alignment with its freight network plans. For high-volume customers, TuSimple tells VentureBeat it will continue to map routes and deliver to distribution centers. And it says it will give clients of all sizes the ability to track freight in real time using TuSimple Connect.

To accelerate the network’s growth, TuSimple completed a series of 22-hour self-driving truck runs along the I-10, I-20, and I-30 corridors through Arizona, New Mexico, and Texas. Leading up to today, the company was completing 50 commercial runs per week, and it now plans to conduct 93 commercial runs per week in the U.S., using 40 trucks.

Penske, which operates more than 750 service facilities throughout North America, has agreed to scale TuSimple’s fleet operations and provide maintenance and over-the-road service. U.S. Xpress and UPS will give TuSimple runs to haul for them, guiding which routes open next and enabling the company to further refine its autonomous technology.

TuSimple — which is reportedly seeking $ 250 million in new funding — is proposing an ambitious timeline, but it’s arguably better-positioned than most to deliver. The company recently expanded a freight-hauling pilot program with UPS to 20 trips per week, with additional routes between Arizona and Texas and El Paso and Dallas, and its trucks are performing revenue-generating trips for over a dozen customers, including Fortune 100 companies and “household names.” Moreover, TuSimple has R&D and testing centers globally in hotspots like Beijing, San Diego, Shanghai, and Tucson. It also has a war chest totaling over $ 298 million, with contributions from Sina, Nvidia, UPS, and Mando.

On the other hand, analysts like Boston Consulting Group’s Brian Collie now believe broad commercialization of autonomous cars won’t happen before 2025 or 2026, at least three years later than originally anticipated. Partly as a consequence of halted real-world vehicle testing, the coronavirus has delayed Lyft rival Waymo’s work by at least two months. Meanwhile, Ford pushed the launch of its driverless vehicle service from 2021 to 2022.

TuSimple’s Class 8 semi-trucks can carry loads exceeding 33,000 pounds and are level 4 under the guidelines penned by the Society of Automotive Engineers (SAE), meaning they’re capable of full autonomy in controlled (and often geofenced) highways and local streets. Unlike self-driving perception platforms from the likes of Uber and Waymo, TuSimple’s is decidedly camera-forward. Using an eight-camera array and other sensors, it can detect cars, pedestrians, and other obstacles up to 1,000 meters away.

TuSimple says its approach enables it to achieve three-centimeter precision for truck positioning, even in inclement weather and at night, and it allows for plenty of leeway in real-time decision-making. It also claims better efficiency than its competitors. TuSimple says its trucks are able to monitor traffic flow far ahead to maintain a given speed more consistently than human drivers and competing autonomous vehicle systems. The company claims this reduces fuel consumption by as much as 15% and average purchased transportation costs by 30%.

TuSimple has plenty in the way of competition, like Thor Trucks and Pronto.ai. There’s also Ike, a self-driving truck startup founded by former Apple, Google, and Uber Advanced Technologies Group engineers that has raised $ 52 million. And then there’s venture-backed Swedish driverless car company Einride. Meanwhile, Paz Eshel and former Uber and Otto engineer Don Burnette recently secured $ 40 million for their startup, Kodiak Robotics. That’s not to mention Embark, which integrates its self-driving systems into Peterbilt semis and launched a pilot with Amazon to haul cargo, or driverless truck solutions from incumbents like Daimler and Volvo.

But demand for driverless trucks is strong. The industry stands to save the logistics and shipping industry $ 70 billion annually while boosting productivity by 30%. According to a recent study from the Consumer Technology Association, a quarter (26%) of consumers now view autonomous delivery technologies more favorably than before the health crisis. Besides cost savings, the growth is driven in part by a shortage of human drivers. In 2018, the American Trucking Associates estimated that 50,000 more truckers were needed to close the gap in the U.S., even despite the sidelining of proposed U.S. Transportation Department screenings for sleep apnea.

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Big Data – VentureBeat

Calling My ERP Friends: Seamless Network Interoperability As The Next Evolution Of B2B Networks

March 17, 2020 SAP

Imagine you meet a new friend who you want to communicate with regularly. That sounds easy, right? But, instead of just selecting her name on your phone and contacting her, your telco provider says you first have to create a “flight plan” – a list of all your new friends sorted by 1) their value (meaning what’s in for you and your friend), and 2) the technical effort it takes to connect. Unfortunately, your new friend is No. 21 on the list. That makes her part of the third wave to be “onboarded.” But, even before the first wave, there has to be a pilot to test the best way(s) to get in touch with your friends. And, once wave three starts, a communication consultant will get in touch with her on your behalf to tell her she will have to contract with your telco provider before the two of you can communicate.

In private life, this scenario sounds crazy. In the world of B2B communication, this is how it often works.

In a B2B scenario, regular communication between trading partners is a key success factor. Sharing forecasts, commitments, production plans, stock-on-hand details, and end-to-end procure-to-pay communication avoids surprises and disruptions and ensures a high level of transparency, agility, and process efficiency.

For many years, one-to-one Electronic Data Exchange (EDI) for integrated electronic B2B communication as well as on-premises supplier portals was the state-of-the-art technology. However, technical setup, maintenance, and support costs were fairly high and, depending on the industry, prevented the technology from adding significant value for users.

Traditional one to one networks 1024x314 Calling My ERP Friends: Seamless Network Interoperability As The Next Evolution Of B2B Networks

Figure 1: Traditional, one-to-one connections between companies have reached a level of complexity that is difficult and expensive to handle. As a result, suppliers hesitate to introduce new connections.

In the past 10 years, multiple B2B collaboration networks have evolved. B2B collaboration networks are cloud platforms that offer multiple ways to connect and also support manual or electronic communication with the cloud platform. The key advantage of those networks is the ability to connect just once to communicate with multiple trading partners. Most of those networks have a focus area (either a specific business area, such as procurement or logistics, or a specific industry), and trading partners are fairly distributed across those networks.

Figure 2: Cloud collaboration platforms allow a company to connect once and communicate with all trading partners on the network.

In order to drive value for the companies collaborating via such a network, the number of connected trading partners is the key success criteria. Unfortunately, convincing trading partners to join a new network takes months, if not years, because they have to connect to multiple communication channels, which drives process complexity and costs.

Figure 3: Suppliers still must connect to multiple collaboration platforms (e.g., in case supplier C and D would like to collaborate with company A and B).

Consequently, suppliers and customers are heavily pushing network operators to connect their networks, enabling interoperability between the networks so the trading partners can stay on the network of their choice and still transact with all their customers. As a result, network providers can establish things like value-added network (VAN) tunnels and field maps between the networks so every message can be transmitted and translated easily from one network to another.

This approach shows incredible results in terms of supplier adoption and onboarding time. Furthermore, the rate of electronically integrated processes (driving process efficiency and compliance) is much higher compared to net new onboardings, which often start with web graphical user interface-driven, manual processes.

There are several reasons for success:

The network of networks (NEON) approach truly fulfills the connect-once promise. Besides some additional potential legal and commercial agreements, the supplier can continue to use its network of choice.

Companies have almost immediate access to all trading partners connected on the networks and can run robust B2B collaboration processes within a matter of days.

There’s no need to convince and educate suppliers in regards to how to connect to and maintain a new network.

Issues can be resolved quickly, as the network providers speak to each other directly.

There’s no need to build up additional backend integration for orders, forecasts, track and trace, etc., as a supplier’s backend systems (ERP, planning, engineering, etc.) typically would already be well integrated into its network of choice.

The flipside is related to the fact that there’s no standard method of interoperability. These network-to-network connections will always look different in terms of:

Technical connectivity protocols and formats

Business rules: Many networks will send out a reminder in case of an overdue order response or an alert in case a goods receipt does not match the original order. Those rules need to be aligned between the networks, so it’s clear who informs who in case of a disruption.

Electronic invoice compliance: In the event that both networks can create legal electronic invoices, one network would have to step back.

Support models: Support workflows could be different for a network A and B combination compared to a network C and B combination.

SLAs (e.g., response times, uptimes, etc.) and security aspects (e.g., support of International Traffic in Arms Regulations, or ITAR, compliance)

Commercial and legal aspects: For example, some networks charge suppliers, some charge customers, some are transaction-based, some are spend-based.

Last, but not least, while the technical aspects of the NEON approach can be solved quite easily, misalignments in terms of processes are harder to solve. Think about a supplier-managed inventory (SMI) process: It is fairly easy to technically share forecasts and stock levels, but it is more difficult to come to an agreement about process workflows, responsibilities, and liabilities.

Still, what we see in the market is that the benefits of connecting once overlay the potential negative aspects. There are more and more success stories of where a procurement and supply chain collaboration network interoperates with industry networks.

Making it as easy as possible for trading partners to communicate with their customers is the key success criteria to drive value in terms of process efficiency and working capital at minimal IT costs. Interoperability between networks is the next evolutionary step to enable companies to interoperate seamlessly, in just the way you would get in touch with a friend.

The Ariba Network is supporting the approach of network interoperability and established network connections to multiple industry and solution-specific networks so that customers not only have access to more than 4 million suppliers directly connected to the Ariba Network, but also to suppliers connected to other networks.

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Digitalist Magazine

Scalable, Authentic, And Manifold: How To Maximize The Business Impact Of Your Corporate Alumni Network (Part 3)

February 25, 2020 SAP

Part 3 of the three-part series, “Scalable, Authentic, and Manifold.” In this blog, we will discuss best practices for leveraging network variety by managing network diversity.

We closed part two of this blog series on corporate alumni networks with some thoughts about the important role of self-organization to keep a network active even if a generally positive and high degree of network variety might debilitate the activity level within it due to too much complexity – as complexity is a compelling consequence of strong variety.

Although at first glance, it looks like you can’t have variety without accepting complexity, here are a few thoughts about practical network management experiences to reconcile both in favor of your network’s effectiveness.

Within the SAP alumni network, there is a healthy degree of variety, as a few findings about its network demographics illustrate:

Age: The ages of SAP alumni are quite equally distributed around an average of 46 years: 33% are younger than 40 years, 59% are younger than 51 years, and 19% are older than 60.

Career stage: 50% consider themselves to be in a mid-career stage; 12% say they are early in their career; 21% are late; 12% are retired, and 5% are in a career break.

Tenure and hierarchy: With an average tenure of 8.3 years, 43% left SAP as employees with non-supervisory functions; 27% as team leaders or supervisors; and 30% as managers in leading or executive functions.

Geography: The SAP alumni network is established in around 80 countries across the globe with 56% of the alumni indicating Europe as their home region, 23% the Americas, 15% Asia-Pacific, and 6% Africa and Middle East.

Alumni since…: 57% of network members left SAP just 1 to 4 years ago, another 11% left 5 or 6 years ago.

Next career step: Roughly 51% mentioned an SAP partner as their current employer, 25% an SAP customer, and just 7% an SAP competitor.

Professional focus: By analyzing qualitative survey statements, we derived a broad range of interests – from concrete tactical and project-based topics to more strategic perspectives on innovational IT and industry trends.

In my opinion, it is undeniable that the less homogeneous a network is, the higher its potential to be leveraged in manifold business-related contexts. Thus, the variety of the SAP alumni network is a promising fundamental to support the various business objectives SAP Alumni Relations is committed to.

As stated in a prior post, successful (alumni) network management means to a large extent successful incitement to self-organization. So, what does the mean in this context? The job to be accomplished here is to help transform a network’s amorphous variety towards a kind of shaped diversity, avoiding overwhelming individuals with a network’s complexity, helping them orient themselves to a set of better digestible subsets or “partial networks,” and then enabling them to effectively take action. It is important to put a clear focus on providing the community with local information, developing a community of local alumni ambassadors, and supporting local communities in conducting regionally specific alumni events.

Another more general approach to effectively managing network variety is to catalyze the emergence of network sub-communities, be it around certain geographies, ages (e.g., student alumni groups are a common example), or topics of interest, industries, lines of business, and so forth. The SAP Alumni Portal now offers such functionality, and a couple of communities are evolving. But again: network management is mainly about incitement to self-organization, so an alumni network manager’s job is not to pre-define groups she or he thinks would make the most sense, but to offer the opportunity and then let the network decide which paths to take.

Fig3 1024x229 Scalable, Authentic, And Manifold: How To Maximize The Business Impact Of Your Corporate Alumni Network (Part 3)

Holistic alumni network management as a professional standard

“They take action, they are authentic, and they are (demographically) everywhere!” might be an appropriate statement to summarize the empirical findings about the SAP alumni network discussed in this blog series. Also, the data tells us a lot about its concrete business potential and how to leverage it by managing size, trust, and diversity.

In addition, the numbers provide us with three key messages on different abstraction levels about successful and holistic alumni relations management:

The numbers are strong indicators or “proof points” about the great business potential behind alumni relations networks.

Network management practices that are aware of and conscious about trust-based networks’ very specific conditions and characteristics are able to increase network effectivity even more. In particular, it is important to carefully balance incentives to self-organization vs. traditional organization in terms of mechanistic steering as we know it from our day-to-day work within formal organizations.

To holistically think about and manage networks, we need to understand network management as dealing with three separate objects:
1. The network, as such
2. The boundaries of the network being a self-sustaining object
3. The network not just as homogeneous entity but also as a set of sub-units

To allow an (alumni) network to fully unleash its potential of being far more than just the sum of its parts, all three levels need to be taken care of. If just one of them is ignored, the potential of the entire network lags behind its possibilities.

Fig4 Scalable, Authentic, And Manifold: How To Maximize The Business Impact Of Your Corporate Alumni Network (Part 3)

Learn more about “Leveraging Corporate Alumni For Strategic Transformation.”

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Digitalist Magazine

The Network And Your Supply Chain (Part 2)

November 13, 2019 SAP

Part 2 of the “The Network And Your Supply Chain” series

Networks have had a very positive effect in today’s world – just think about how Airbnb, Uber, Facebook, and Alibaba have impacted your life. These networks have created a digital platform for all their participants, and the fundamental objective of the network is value creation for participants. The so-called “network effect” comes into play when increased numbers of participants improve the value of the service or the product offering.

From the lens of supply chain leaders, it is very important to recognize that a network can determine the efficiency and effectiveness of your supply chain. Networks are critical for value creation; they become the system of record in a multi-enterprise collaboration world.

What to look for in a network that serves your enterprise

Financial opportunities, such as cost reduction, working capital optimization, on-time deliveries, and quality improvements

Process automation that results in saving time and administrative costs

Preventive risk tracking against late shipments and logistical errors

An integration framework to operationalize your business processes and drive business value

Visibility and insights across the network for a better understanding of the state of processes

All of the above will enable full supply chain alignment within and outside the four walls of your enterprise and can offer the business very positive outcomes.

To achieve these objectives for your enterprise, the challenge is to ensure your trading partners are onboarded and managed. This is where the network plays a crucial role. Think of some of your current business challenges: maintaining pricing contracts, confirming goods with your warehouse clerk, working with your planner to ensure your supplier has the capacity to meet the forecast, or collaborating with your quality assurance team about a quality incident they created on an incoming batch from a supplier.

This is a normal day in a life of “what can go wrong in your supply chain.” Navigating the challenges and developing a winning strategy not only requires the right structure within your organization but also working with your trading partners – your suppliers, logistics providers, and partners – to ensure you have the right communication mechanisms and tools to support the free flow of commerce in your organization.

Some industries have been very successful in embracing the network. Electronics manufacturers, for example, have a great deal of experience and knowledge from building and managing their digital supply chains by creating a network with outsourced manufacturers. Consumer products organizations and retailers may be far behind, but they have started to work on transforming their supply chains and leveraging the network.

In reality, what you really need is a high level of transparency that provides mutual benefits for your enterprise without burdening your trading partners. Business-to-consumer (B2C) markets are enabling companies to deliver this level of insight, providing information about shipment updates with real-time visibility. Here are some key aspects that need to be considered to make the network work to your advantage:

Data from internal and external sources needs to be brought into a simple platform – data consolidation and enrichment.

The consolidated data needs to be augmented and cross-referenced with information that is relevant for your organization – analytics and network optimization.

Information from external sources like weather, traffic, and social networks that could impact your business operations needs to be included – social listening and monitoring tools.

The enriched information needs to be linked into your data models and advanced analytics systems then optimized to feed into the control center for further review – proactive response management.

Easy data visualization and governance need to be provided and privacy and security compliance standards need to be adhered to in the cloud – data security and compliance.

All of the above means your network has two main critical components: the trading partners who play a key role in enabling your supply chain, and a digital platform that can help your enterprise create agile and flexible business processes, providing improved supply chain collaboration and frictionless integration to enable the next-generation intelligent supply chain.

Get to know the SAP C/4HANA and Qualtrics portfolio by joining our webinar on November 26th.

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Solutions Journalism Network Transforms Newsrooms by Educating the Next Generation of Journalists

November 5, 2019 NetSuite

Posted by Barney Beal, Content Director

Headlines focusing on crime, inequality, war and pollution proliferate in news outlets today. Positive responses to those problems that are happening all over the world often get lost in the shuffle.

However, there’s a movement underway to change how news is presented. Solutions Journalism Network, an independent nonprofit organization, is leading that charge.

Founded in 2013 by world-renowned journalists from the New York Times, Solutions Journalism Network advocates for evidence-based reporting linking problems to solutions in newsrooms and journalism schools all over the U.S. The organization provides training to editors, journalists and university professors in an effort to change the way news is delivered to the public.

“We’re affecting the mass of new journalists who are turning out through colleges and universities,” said Maurisse Johnson, Chief Financial Officer of Solutions Journalism Network. “They graduate and go to newsrooms, magazines and media outlets, and produce solutions journalism, thus changing the old ways of newsrooms.”

One very visible example of solutions journalism at work is coverage around voter fraud. An article focused on solutions journalism would mention that voter fraud exists while also showcasing ways global communities work to combat the practice.

Solutions Journalism Network is funded primarily by grants from foundations and donations from corporations and individuals. In the last two years they’ve experienced massive growth: a 40% increase in grant funding in just 24 months.

“Our mission has remained the same throughout, but our administrative burden exploded,” Johnson said. “We received an increase in the number of grants, the average grant size doubled, and we had to increase headcount accordingly.”

Prior to the surge in grants, Solutions Journalism Network used a combination of desktop accounting software and an outside accounting firm to manage their books. But as the organization grew at breakneck speed, so too did the complexity of its finances.

“We were at an inflection point where our organization had matured beyond external management of our books,” Johnson said. “As grants grew in both size and volume, we had a bigger responsibility to provide reporting and answer questions for funders on an ad hoc basis.”

At that time, Johnson undertook a business process review that lasted about six months. He made sure he thoroughly understood the business model, the people and the grant functions, so he could build a new process around all three.

Specific requirements for nonprofit accounting functions aided Johnson in narrowing down platforms for review. His choice of NetSuite was based on a combination of pre-built reports customized for nonprofits, the ease of closing out sub-ledgers, straightforward allocation tracking, and a pre-established trust in NetSuite based on years of experience.

“I have a history with Oracle that’s built on trust,” Johnson said. “I know that Oracle is going to put their efforts towards the development of NetSuite and offer me a robust support team. If something goes awry, Oracle will invest resources in it.”

Solutions Journalism Network went through a four-month implementation that included on-site builds – a huge benefit for Johnson and his team. NetSuite went live in January of 2019, including a direct connection to Solutions Journalism Network’s expense management platform.

Roughly one-third of their 40+ employees use it in some capacity, with plans to increase that percentage in the coming years.

“Dashboard reporting for nonprofits is already configured in NetSuite,” Johnson said. “We didn’t have to spend time building it. We don’t have to close out individual ledgers every month. And the allocation tracking in NetSuite is quite sophisticated. Grants dictate salary coverage and the allocations change every year. Being able to articulate this in a financial system (rather than manually) is huge.”

With the launch of NetSuite, Solutions Journalism Network has experienced time savings, increased confidence, and simplification across the organization. Today, Johnson can close the books in less than an hour. Auditors, board members and other financial professionals immediately have a level of trust when they learn that Solutions Journalism Network is using NetSuite. And given the ease-of-use, Johnson is able to leverage the data in NetSuite for interactive, organization-wide conversations.

“With NetSuite, we can share data across our organization with an ease we’ve never experienced before,” Johnson said. “Previously, we had static copies of accounting data that we’d send to stakeholders. Now, we can have a web meeting with a program manager and go through their P&L, asking meaningful questions we didn’t have access to before.”

The flexibility of financial reporting provides a big bonus as well. Before NetSuite, Johnson would have to manually run one report query across 50 different grants, which makes a big difference when you have limited or no IT staff. Now he can just apply a grant-specific filter in NetSuite to create each report. And, individual users can access reporting on their phones via an app – making it more easily digestible and accessible for all.

For the future, Johnson plans to work towards integrating Solutions Journalism Network’s customer relationship management (CRM) platform and payroll providers. His goals are to connect initial grant conversations in the sales cycle all the way to incoming grant funds, and tie payroll directly to financial data as well.

“We want to be able to answer questions like, how many foundations are we engaged with for over six months, what percentage produce dollars after six months, and what’s the churn rate,” Johnson said. “NetSuite is so robust in terms of creating KPIs, and we expect these to be viable metrics once we make the connection in the next year.”

Learn how other nonprofits like Solutions Journalism Network streamlined business processes using NetSuite.

Posted on Mon, November 4, 2019
by NetSuite filed under

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Shopify acquires 6 River Systems for $450 million to expand its AI-powered fulfillment network

September 10, 2019 Big Data

Shopify today announced it is acquiring 6 River Systems, a startup focused on fulfillment automation for e-commerce and retail operations. The deal is valued at approximately $ 450 million — 60% in cash and 40% in shares.

In June at its Unite partner and developer conference, Shopify announced the Shopify Fulfillment Network, which uses machine learning to ensure timely deliveries and lower shipping costs. Shopify’s fulfillment centers span California, Georgia, New Jersey, Nevada, Ohio, Pennsylvania, and Texas. The network, which is only available in early access, supports merchants that ship between 10 to 10,000 packages per day. The company hopes to eventually support between 3 to 30,000 packages per day. The 6 River Systems acquisition looks like an attempt to speed up that growth.

“Shopify is taking on fulfillment the same way we’ve approached other commerce challenges, by bringing together the best technology to help everyone compete,” Shopify CEO Tobi Lütke said in a statement. “With 6 River Systems, we will bring technology and operational efficiencies to companies of all sizes around the world.”

Robots in the warehouse

6 River Systems is best known for its Chuck autonomous vehicles that can move around packages in warehouses. Indeed, Shopify believes that adding the robots to its fulfillment network “will increase the speed and reliability of warehouse operations, by empowering on-site associates with daily tasks, including inventory replenishment, picking, sorting, and packing.”

While Shopify plans to accelerate the growth of its AI-powered fulfillment network, it promises to keep selling 6 River Systems’ solution for warehouses. The startup’s solution operates in more than 20 facilities in the U.S., Canada, and Europe. It fulfills millions of units each week for companies including Lockheed Martin, CSAT Solutions, ACT Fulfillment, DHL, XPO Logistics, and Office Depot.

Shopify doesn’t expect the transaction to have any material effect on its revenue in 2019. It will increase the company’s expenses for 2019 by $ 25 million, however, including $ 10 million in operating expenses, $ 8 million in amortization of intangible assets, and $ 7 million in stock-based compensation. The company does expect 6 River Systems to generate annual billings of approximately $ 30 million in 2020.

Founded in 2015 by Jerome Dubois, Rylan Hamilton, and Chris Cacioppo, 6 River Systems is based in Waltham, Massachusetts. 6 River Systems had raised $ 46 million to date from Eclipse Ventures, Menlo Ventures, Norwest Venture Partners, and iRobot. Dubois and Hamilton were previously executives at Kiva Systems (Amazon acquired Kiva Systems for $ 775 million in March 2012). Shopify specifically called that out in its release, noting that the acquisition will give it “experienced leaders from Kiva Systems (now Amazon Robotics).”

The deal has already been approved by 6 River Systems’ stockholders. Included in the $ 450 million amount is approximately $ 69 million for the startup’s founders and employees “that will vest subject to certain conditions and will be treated as stock-based compensation.” The acquisition is expected to close in Q4 2019.

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Big Data – VentureBeat

Tag Archives: Network

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Solutions Journalism Network Transforms Newsrooms by Educating the Next Generation of Journalists

Shopify acquires 6 River Systems for $450 million to expand its AI-powered fulfillment network

Robots in the warehouse

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