ServiceNow Acquires DxContinuum for Machine Learning, Automation, and IoT

On January 18, ServiceNow announced it has agreed to acquire DxContinuum in an all-cash transaction. ServiceNow’s current market cap is over $13 billion. DxContinuum raised $1.63 million in a single funding round in August 2015. By combining DxContinuum’s machine learning capabilities with ServiceNow’s IT asset management and service support, as well as ServiceNow Ventures’ previous investments in mobility and expense management players like MobiChord, ServiceNow will be better positioned to pursue customer opportunities in the Internet of Things (IoT) and cloud-based environments of the future with a solution that supports proactive service through machine learning and predictive analytics.

ServiceNow is an enterprise solutions management company that provides cloud-based service, operations, and business management solutions across organizational domains including IT, field service, human resources, facilities, and finance. ServiceNow’s solution is aimed at better managing “everything as a service” – the new, highly complex business models that have arisen from the subscription economy. The platform is offered as a single portal for service requests to reduce the back and forth email and spreadsheet communication typical in organizational IT, HR, and service departments. The ServiceNow portal provides an integrated location for users to make all IT requests including asset ordering, helpdesk, and support services, and is scalable due to ServiceNow’s cloud deployment model.

DxContinuum provides cloud-based predictive analytics software that embeds within enterprise CRM and marketing automation environments, utilizing machine learning and natural language processing to analyze sales and marketing data, detect patterns in the data, and generate predictive forecasting models.

The acquisition of DxContinuum will allow ServiceNow to integrate DxContinuum’s machine learning algorithms into its platform, enabling automated and predictive models for processing enterprise service request data, IT asset data, and sales and marketing data. The partnership is especially important as organizations that utilize ServiceNow for automated service management begin to fulfill more complex IT and service requests, including those for IoT connected devices and networks.

Connected devices associated with the Internet of Things generate significant volumes of data and requests independently. With ServiceNow’s acquisition of DxContinuum, machine and manual work requests can now be automatically categorized and routed within ServiceNow’s portal, enabling users to automate the process of prioritizing and resolving requests.

ServiceNow’s platform is based on a customizable, cloud-deployment model, and with the acquisition of DxContinuum, the platform will be better equipped to scale, compute, and store departmental data and service requests generated in IoT environments. The addition of machine learning and predictive capabilities will allow ServiceNow customers to predict and plan for service requests, enabling them to better contextualize and support data generated by IT assets and departmental groups. The combined platform will support proactive service through machine learning and predictive technologies to anticipate requests and identify data relationships more quickly, creating a single, self-learning data environment across marketing, sales, and service data.

The announcement also has implications for the Technology Expense Management (TEM) industry, in particular for players like MobiChord that are built on, and differentiate through, an integration with the ServiceNow platform.

In November 2016, ServiceNow Ventures invested seed funding in MobiChord, a Telecom Service Management company whose subscription-based software offering manages organizations’ telecom and cloud subscription services, assets, and expenses. MobiChord’s solution is highly integrated with ServiceNow for asset, expense, and service management, including real-time management of IoT assets. As TEM vendors are increasingly asked to support IT assets beyond mobile devices and wired networks, including IoT and cloud, ServiceNow’s expanded capabilities in IoT through its acquisition of DxContinuum may allow MobiChord to offer additional machine learning and predictive functionality to its customers, creating a solution that spans from device to cloud.

By broadening its portfolio to include asset management, machine learning, and mobility support, ServiceNow contextualizes marketing, sales, and service data for IoT solutions through a self-learning data environment that utilizes predictive and machine learning technologies.

Telesoft Announces Executive Changes, Continues Trend of Movement in TEM

TelesoftLeadership

On January 17, Telesoft announced it has hired Tamara Saunders and Don Luby as Chief Financial Officer and Senior Vice President of Sales, respectively. Telesoft also announced the appointment of Charlotte Yates to Telesoft’s board of directors. The appointments represent Telesoft’s first major executive talent change since September 2016, when Telesoft was acquired by private equity firm, Sumeru Equity Partners, after which Sumeru retained much of Telesoft’s existing management team.  At the time, Blue Hill commented that an opportunity existed for greater consolidation and investment in the Technology Expense Management (TEM) market in the near term.

Charlotte Yates has over 30 years of experience serving in leadership and advisory roles for technology and telecommunications companies. Most notably, Yates co-founded and served as CEO at Telwares, a provider of network and IT advisory and cost management services which had previously rolled up TSL, Digital Reliance, MSS*Group, and QuantumShift in a TEM market rollup through the 2000s. In March 2011, Tangoe acquired Telwares’ Telecom Expense Management business, including its invoice management, call accounting, and mobile device management operations.

Don Luby is a veteran in the Technology Expense Management space with over 30 years of experience, having served most recently as VP of Sales at Tangoe after being acquired through Tangoe’s acquisition of IBM’s Rivermine TEM business in May 2015. Prior to Tangoe, Luby’s previous experience included stints at IBM, Emptoris, and HP.

Rivermine’s high degree of customization enabled Luby to pursue some unique solutions-driven sales opportunities in his role at Rivermine. Blue Hill notes that Luby’s experience may provide a new perspective in Telesoft’s go-to-market strategy in helping Telesoft to highlight opportunities for enterprise-specific customizations.

Tamara Saunders joins the firm after more than 20 years of experience in telecommunications public accounting and financial roles, having most recently served as CFO of Telesphere and VP of Finance at Vonage, which acquired Telesphere in 2014.

Blue Hill notes that it is interesting that Telesoft is acquiring talent from Tangoe, and hints that the consolidation and shifting market leadership positions in the TEM market are continuing trends, especially as Tangoe is poised to potentially undergo additional transformation. Key executive talent continues to change hands and large global vendors face both outside investment and the potential for additional consolidation in the near future. With this move, Telesoft joins the race for TEM market leadership along with fellow private equity-funded firms Calero and Asentinel, as well as fast-growing independent firms such as Cass Information Systems and Cimpl, and mobility managed service firms with strong TEM capabilities such as MOBI and Mobichord.

Just last week, Blue Hill covered Tangoe’s announcement made on January 3, 2017 that the company has received two non-binding acquisition proposals: one from Marlin Equity Partners, and the other a joint proposal from Clearlake Capital Group and Vector Capital Management. Both Clearlake and Marlin own large global TEM players: Calero and Asentinel, respectively.

Blue Hill has previously profiled Telesoft, alongside Calero, Asentinel, and Tangoe, as key Technology Expense Management (TEM) vendors equipped to manage TEM on a global scale. In particular, Blue Hill has highlighted Telesoft’s flexible, single-platform solution, as well as the company’s ownership and business continuity – remaining owner/operator run with over 30 years in business – as key differentiators for the company.

The TEM market is clearly attracting attention, not only from outside investors but also from seasoned veterans in the space seeking new opportunities with large global players. Since our coverage of the global TEM landscape in September 2016, the market has already undergone several significant changes and investments in just these few months. This makes our jobs at Blue Hill exciting (and easy!) as new opportunities to provide coverage and guidance continue to emerge.

Retail Needs a Refresh: PTC and First Insight Partner to Deliver Technology Solutions for Retailers

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On January 12, First Insight, Inc., a retail solutions provider focused on incorporating the customer viewpoint into product design and merchandising, announced the launch of its Optimized Line Planning (OLP) solution in collaboration with PTC’s ThingWorx IoT (Internet of Things) platform and FlexPLM product lifecycle management suite for consumer products. Blue Hill provides guidance on what the partnership means for retail environments, PTC’s foothold in the retail segment, and retail technology trends, within the context of a shift from traditional brick and mortar retail toward a more connected, data- and technology-driven retail landscape focused on maximizing long-term customer value.

Before retail had access to evolving data about its customers and supply chain, and new methods by which to interact with these customers – including social media channels and targeted campaigns – merchandising, forecasting, and retail planning were based on historical information, or guesswork. This old-school view of the customer-brand interaction, with a focus on maximizing transactional rather than long-term value, has quickly shifted with technology trends and new business models, and has put traditional retailers at a disadvantage. In business, the new motto is no longer cash is king, but data is king.

To address this shift toward customer-focused and data-driven decision-making in retail, the partnership between First Insight and PTC is aimed at providing retailers with actionable insights earlier in the product design cycle by incorporating PTC’s ThingWorx machine learning, predictive analytics, and IoT-driven customer support capabilities, along with its FlexPLM software, with First Insight’s InsightSuite solution. InsightSuite, with new product selection, pricing, and marketing modules, is aimed at enabling brands to more accurately design, select, price, and market new products. InsightTARGETING is focused on creating buyer personas and targeted offerings based on historical sales data and purchase history, as well as real-time consumer input. FlexPLM incorporates data from physical products, web-based resources, and enterprise software systems, along with ThingWorx’s connectivity layer, to enable collaboration and data-based decision-making for retailers.

Alongside First Insight’s solution, ThingWorx’s machine learning and predictive capabilities will enable more forward-focused analysis by using historical data to predict and plan for future demand. Through these insights, retailers can better understand which product attributes customers value most and how these attributes impact revenue, capture and analyze key data about their customer base, inform assortment strategy based on this customer understanding, and create optimal products and line plans based on data-driven recommendations from the tool.

Blue Hill has observed PTC’s expansion into the retail and consumer products segment, which has historically not been PTC’s primary business driver compared to verticals such as industrial products, electronics and high tech, and federal, aerospace and defense. Retail and consumer accounted for 8% of PTC’s revenue by industry for fiscal year 2016, compared to 32% made up by industrial products. These revenue percentages have remained fairly constant for PTC since fiscal year 2011.

The partnership will provide both companies with a stronger foothold in retail by integrating data, software systems, and retail planning with backend functions such as supply chain management and manufacturing, increasing the flow of data between these areas and the insights that can be drawn from that data.

PTC is further expanding the capabilities of its FlexPLM software solution. On January 15, at the National Retail Federation Convention & Expo (aka Retail’s BIG Show), PTC announced a web-based concept management app for FlexPLM that will allow users to capture and share inspirations, ideas, requirements, and feedback, including real-time trending imagery from social media platforms such as Instagram. Users can share these product concepts across the enterprise through digital boards built from images, videos, text, documents, and color palettes. The concept management app is aimed at providing direction for product, material, range, and seasonal planning, shortening the time from ideation to product development. Says Quach Hai, Senior Director, Retail Product Management, PTC, “We are seeing a shift to digital tools and methods across the entire development cycle.”

Retailers face increasing competition from online sales and amongst other brands attempting to stay abreast of rapidly changing trends and consumer preferences. Just look to recent announcements from stores like Macy’s and The Limited. After poor sales and lower holiday performance than expected from both retailers, The Limited announced that it is closing all 250 of its stores, and Macy’s announced that it is cutting 10,000 jobs. Technology solutions that utilize data to align product, merchandising, and supply chain efforts around customer demand can provide an advantage for retailers by shortening the time from product design to store shelves through informed decision-making.

Blue Hill recommends that retailers consider the combined capabilities that First Insight and PTC will provide through their partnership when seeking new means of understanding and selling to their customers. For PTC, First Insight’s foothold in retail may provide the company with upsell opportunities for its cloud solutions, as retailers seeking to incorporate data into their operations may require increased capacity to store and compute that data. As retailers start to invest in solutions to optimize their performance through the use of data, they are beginning a shift toward the retail environments of the near future – environments that will undoubtedly use technologies like IoT and augmented/virtual reality to better connect with and sell to customers.

Self-Service Big Data in the Cloud: Questioning Authority with Qubole CEO Ashish Thusoo

Ashish ThusooThis is the fourth in Blue Hill Research’s blog series “Questioning Authority with Toph Whitmore.

Ashish Thusoo is the co-founder and CEO of Big-Data-as-a-Service provider, Qubole. He and I recently talked DataOps, data disintermediation at Facebook, elastic-data pricing models, abstraction layers, and the future of Big Data infrastructure. (Hint: It’s in the cloud.)

TOPH WHITMORE: You were an engineering manager at Facebook, where you implemented a DataOps approach to infrastructure management. You left Facebook in 2011 to start up Qubole. What motivated you to move on?

ASHISH THUSOO: That topic [DataOps] is very pertinent, and is something that a lot of companies struggle with. A lot of the genesis around Qubole was based on that.

Creating these data lakes, operating these Big Data platforms and making them available, making them self-service—those are extremely difficult tasks for most companies. At Qubole, we said, you know what, the best way to do this is to use the cloud! Use the cloud to create Big Data infrastructure that is self-service and automated. Automation takes care of the operational needs around the self-service infrastructure, and the interfaces are self-service enough that a marketing analyst or business analyst or data analyst can go into that infrastructure and do some queries and such.

Qubole is heavily influenced by the experience that we had at Facebook. My cofounder and I joined Facebook in 2007. We had a data-warehousing system, and we had the data team. Analysts would talk to the data team, and the team would then go off to get vanilla data that was stored in silos, and create some summary datasets, then put those into a data warehouse, and then analysts would come in and query that data. The process was very, very slow. Essentially, the direct result of that slow process was that we pulled data, but we didn’t actually use it that much. And the analysts would just go forward with their intuition. Data delayed is basically data denied.

When we went in there, we said this is a broken model, especially for a company that is growing so quickly. We need to rethink this model, and essentially create a self-service platform, which everybody in the company can use, and make the data team support that platform instead of being between the users and the platform.

That model is essentially what we built inside Facebook. The hope and thesis was that if you’re a data analyst, data scientist, developer, or end user, you should be able to get to the data without having to call anyone for help. The infrastructure should make that access easy, and also support that access. So, if you’re writing a query, the operational model should scale enough that it will be able to give you the results in time.

TW: You built this for Facebook. How did you recreate the technology at Qubole?

AT: We were using open-source tools at Facebook. At Qubole, the vision is similar to what we achieved inside Facebook, but with Qubole, we want to achieve it for everyone out there, for every other company. Our mantra here is that if you aspire to be a data-driven company, you should use Qubole. It will help you do that. Much in the same way that that internal platform helped Facebook.

The technology stack is completely different. Facebook was all on-prem. The enabler for Qubole was the cloud. We saw people trying to create data lakes on-prem. With Hadoop, the cost of storage had gone down dramatically. But infrastructure on-prem is still very, very limited. It’s static. You put up your clusters, you put up your systems, and then—even if you put it up so that other people can use the infrastructure—there’s always this risk for the administrator that “I can’t really open this up to everyone because it’s going to be a big problem.”

With the cloud, we turned that on its head. With the cloud, you can create a new system on the fly. It’s completely elastic. With the Qubole platform, you could create these self-service interfaces for data engineers, data scientists, and data analysts.

Our mantra is that—on the cloud platform—for any of the transformations that are coming in to that interface, we create the infrastructure on the fly. We orchestrate the computing infrastructure, and for storage, the data lakes actually that are being created on the cloud are being created on the object stores, not in HDFS. They are being created in object stores in Amazon, Oracle, Azure(Microsoft), or Google clouds.

In the cloud, the object store actually decouples compute and storage. You can keep creating the data lake, you can keep putting the data in the object store, and then with a platform like Qubole, you can have an infrastructure that adapts to your compute needs.

TW: How do you differentiate Qubole from the big Hadoop players?

AT: First, we position ourselves as the cloud platform for Big Data. The big difference for the other vendors: The distro distribution mechanism works well if you are doing on-prem. But when you go to the cloud, you can actually see all of this as a Big Data service. You can do a SaaS platform, which will remove all the complexity of having to stand up infrastructure.

Qubole users come in, create a login, and they’re ready! The same infrastructure is ready. And through that SaaS service, we are processing some 575 petabytes of data every month.

Second, the open-source software distros were built in the era of datacenters, and go in the direction of a converged architecture: “Store data in HDFS, and the same machine will be used for computation.”

Cloud architecture has changed that. The diverged architecture, where the storage is in an object store and compute, is ephemeral, gives customers a flexible pricing model and an elastic data model. And we position Qubole as a cloud-agnostic, cloud data platform that offers Big Data as a service to our clients.

TW: You mentioned the pricing model. I hear concerns from enterprise data leaders about pricing penalties for data growth. Qubole’s message of agile scaling sounds great, but what do I do if I’m about to turn on a new IoT data-delivery system? Will my expenses go up as my data volumes explode?

AT: That is a common issue. And not just for IoT projects. It’s not just the data pricing—the compute can go completely haywire too. You can get a thousand machines in the cloud in a jiffy.

There are two answers. The first is auditability—the ability to give complete visibility to the administrator as to where the costs are going: Which teams are using it more? Are they using it for the right reasons? Are certain data sets being used? Are certain datasets not being used? Can those then be moved to a different archival store? Or maybe they should be not stored?

Second is the cloud pricing model we follow. Cloud adoption initially started off in mid-market, maybe typically with the startup, millennial company.

TW: And software devs.

AT: Right. The pricing model was essentially compute hours. For entry, that model is great. And Qubole offers that. But as your computation scales, as your data scales, you get a discounted price for that.

Often, people use our elastic model in the POC stage, or in the early adoption cycle. When it’s clear the extent [to which] they need infrastructure, then they go into subscription pricing, where they buy a certain amount of compute for a certain price. And that scales. Their pricing is not going to go haywire.

TW: You talked about data scientists, data engineers, data analysts using Qubole. What’s their “pain” right now? And how does Qubole alleviate that?

AT: For these personas, self-service is the big thing: “I don’t want to wait for my data, I want it now.”

In most enterprises, a data team empowers all three roles. This is the team that is the internal sponsor for the infrastructure and systems needed to power analysis. Qubole targets the data teams: Instead of being on the receiving end of the ire of the folks saying “Hey, where’s my data?” the data teams can actually say, “You know what, with the help of Qubole, we’ve created this service, this infrastructure, this Big Data platform for you.” It becomes a mechanism for driving a full-blown data transformation, much in the same way that we drove it at Facebook from 2007-2011.

All of the learnings are there, and—as a self-service option—Qubole provides these users with the right tools for what they want to do. For example, Apache Spark is very popular with data scientists, so we have a Spark offering. We support Presto, which is more in tune for a data analyst. The same data platform can also be used by developers, who might be using Hadoop or Spark for writing applications. Or an engineer who might be using Hive for data-cleansing.

For the data team, Qubole becomes very powerful as a single platform. The data team can serve each of these different personas, and the data team is able to have complete control, and full visibility into what is happening. And can drive that infrastructure on any cloud that they want.

TW: The enterprise market question: Have you seen accelerated adoption in particular verticals?

AT: Our strategy has been “follow the cloud.” Some industries, like media, retail, ecommerce, or even enterprise marketing departments, are adopting the cloud before others. But we also see growing interest from healthcare, even financial services.

From the industry perspective, we feel that industry should know how to drive this transformation. What do you need from the perspective of people, processes, and technology to achieve that?

There is a growing realization across different verticals that they have to adopt a culture of DataOps, where data is widely available. Qubole is a catalyst in driving that adoption of data across the enterprise.

TW: We share an interest in that topic! Where do you see cloud-based data services evolving in the next few years, and where does Qubole go from here?

AT: The future is bright! When we started the company in 2011, there was a question mark on whether cloud would actually be the disruptive technology it had the potential to be. That question is answered now.

Companies are moving to the cloud, partly because applications are being built there, and new data is being produced there. But also, those businesses are realizing that they need to become much more agile with respect to their IT service.

In the cloud market, AWS is by far the leader, but we are also seeing the emergence of Azure, the emergence of Oracle, of Google, and more. As that happens, it creates a great dynamic for the market, because it gives companies options. Once you start treating clouds as base-level compute and services, you need services which can be agnostic. Qubole has a very strong role to play in that.

 

Developing Trends for DevOps in 2017: Security, Containers, and More

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Companies that are turning to DevOps can be seen this time of year alongside those of us who have New Year’s resolutions to be healthier, but still can’t avoid grabbing free cookies in the coffee room. Why? Because DevOps involves both small but meaningful changes in culture, as well as more significant shifts in processes. To be done well, DevOps requires a more strategic focus on communication and collaboration, not just tools. Continuous delivery is only possible if these tools support relevant changes in culture and in processes.

What will be the key trends in 2017 for DevOps? On the basis of a number of conversations with industry leaders and key users, Blue Hill foresees trends in security, container usage, and a shift in business models toward release development, risk avoidance, and cloud orchestration.

  • DevOps will help to serve as an orchestrator between cloud environments. The growth of Amazon Web Services (AWS), Azure, and other cloud platforms acts as an enabler for DevOps activities. It is a win-win situation in that DevOps solutions, which help orchestrate across cloud providers, will only accelerate cloud adoption by eliminating the lock-in risk of using one cloud provider.
  • In 2017, building-in security practices at the core of application development, rather than as an addition after the fact, will be key to a safer environment. The DevSecOps model builds on the principle that everyone is responsible for security, by making ‘security as code’ to distribute security decisions at scale without sacrificing the quality of the solution required.
  • The popularity of containerization solutions (e.g. Docker) is increasing due to the need to provide a consistent environment from development to production. Given the trend toward hybrid cloud and multi-cloud environments, containers provide useful mechanisms for data portability. We will also see an increased shift away from defining containers directly, and more of a shift towards having containers generated automatically where necessary.
  • Automated release orchestration will be critical in the application delivery process, as this approach provides the consistency in the delivery process that business demands, along with the flexibility that IT teams need to deliver solutions faster.

Which data-oriented solutions help bring these types of collaborations to bear? Some of the providers Blue Hill is looking at right now include:

  • Rocana, which wants to bring big data, analytics, and visualizations to DevOps to increase transparency, giving admins better visibility into their data centers and applications, and helping them solve problems through more immediate actions.
  • Resilio, whose Connect solution is providing a resilient, scalable, and centrally-managed solution to efficiently move data.
  • Coralogix, which has created a machine-learning SaaS platform that analyzes traced data from production systems, detects the root cause of software issues, and actively delivers real-time solutions.
  • Supergiant, which has a container orchestration system that makes it easier to scale distributed applications, and is built on Kubernetes.
  • vArmour, with its distributed security system that provides application-aware micro-segmentation.
  • Resolve Systems, which is changing processes by accelerating incident resolution in IT Ops, Network Ops, and customer care centers.

Blue Hill will explore these and other topical solution providers in our DevOps journey this year. DevOps is not just about development but about a process shift towards continuous delivery while maintaining quality. This is because DevOps as a concept is driven by an understanding of the value of collaboration between development and operations staff throughout all stages of the development lifecycle. This is particularly true when creating and operating a service, as it reflects just how important operations has become in our increasingly service-oriented world.

Blue Hill Research Subscription Billing Highlights, December 2016

Blue Hill Research Subscription Billing HighlightsNote: To support questions from enterprise buyers and private investors that are looking at Subscription Billing and the larger world of Demand-Driven Monetization, Blue Hill is starting a review of key announcements and analysis focused on subscription billing including, but not limited to: Amdocs, APTTUS, Aria, Avangate, Cerillion, ChargeBee, Chargify, CheddarGetter, Cleverbridge, Comverse, Ericsson, FinancialForce, FuseBill, GoTransverse, Intacct, Kenandy, Logisense, Microsoft, NetSuite, Oracle, Recurly, Salesforce, SAP, Softrax, Spreedly, and Zuora.

Blue Hill’s view of subscription billing and Strategy Monetization are that
- Strategy Monetization is the practice of translating business strategy into revenue.
- Subscription Billing is an important bridge towards a client-driven, on-demand utilization economy.
- “Assets” are now liabilities when they are underutilized or unrelated to monetization.
- Permanent ownership is increasingly being replaced by on-demand usage across all aspects of society.
- The most important true assets are customer relationships.

Apttus

Apttus Expands its Offering to Meet Increased Demand for Quote-to-Cash Solutions

On December 15, Apttus announced the general availability of its new Quote-to-Cash and Quote-to-Contract editions that bundle together essential tools to manage revenue cycles. Quote-to-Cash will be offered in two editions: Enterprise, which includes full solution configuration, pricing, quoting, contract creation, obligations management, and revenue management; as well as Ultimate, which will also feature complex approval processes, mass renewals management, and transaction compliance solutions. Quote-to-Contract will be offered in two editions as well, Ultimate and Enterprise, with similar features as Quote-to-Cash. All Quote-to-Cash solutions will pair with Apttus’ machine learning capabilities and the company’s intelligent agent, Max.

Blue Hill notes that Apttus also offers a Billing and Subscription Management module that is fully integrated with its Quote-to-Cash capabilities. By synchronizing bills and invoice presentations with all aspects of quote to cash, Apttus will be able to support subscription renewal and granular compliance requirements more easily and accurately.

Avangate

Avangate Launches New Growth Accelerator Suite

On December 8, Avangate announced the release of Growth Accelerator Suite, a collection of embedded features and templates aimed at helping software and SaaS organizations to maximize customer lifetime value and recurring revenue. Key features in the new release include tools for customer acquisition and conversion, customer engagement, campaign promotion, and self-service payment management.

Blue Hill notes that subscription-based customer relationships require increased touchpoints focused on maximizing value for customers and ensuring long-term recurring revenue. Avangate’s new features aim to grow customer lifetime value by incorporating acquisition, engagement, and conversion features in a single suite. Blue Hill notes that these features provide an engaged and self-service customer experience that may translate into higher lifetime value for subscription-based businesses.  

 

Avangate Appoints Gregor Morela As Chief Financial Officer

On December 15, Avangate announced that it has appointed Gregor Morela as Chief Financial Officer. Prior to joining Avangate, Morela most recently served as the CFO of Linq3 Technologies LLC, a private company that offers state-regulated lottery products on point-of-sale terminals. Morela also held various leadership roles at Landis+Gyr, an energy management and metering technology company.

Blue Hill notes that Morela’s background in financial management for complex and highly regulated product lines will be well suited to the subscription billing space in which companies have non-standardized revenue recognition and reporting needs. In addition, for financial products, the CFO often serves as an important proxy for the company’s ability to support increasingly complex customer requests and regulated billing environments.

NetSuite

Anytime Collect Announces Integration with NetSuite Cloud ERP

On December 6, Anytime Collect, a provider of cloud-based accounts receivable applications, announced new integration with NetSuite cloud ERP. The integration is aimed at making accounts receivable management and credit and collections processes easier for global customers by linking with a customer’s ERP or business accounting software to centralize account information. NetSuite and Anytime Collect together will provide automated email, invoice presentment, customer self-service bill payment, and scheduled internal email alerts.

Blue Hill notes that combining NetSuite’s cloud-based ERP system with Anytime Collect’s accounts receivable and credit collection tools provides a single solution for managing the entire credit and collections process within a company’s existing ERP. By combining cloud-based AR with NetSuite’s SuiteBilling capabilities, NetSuite customers now potentially greater control in managing the revenue lifecycle.

These are the key subscription billing and strategic monetization announcements Blue Hill saw in December 2016. If you have any new tips to provide or would like to schedule a briefing, please contact us at research@bluehillresearch.com

Blue Hill Research Enterprise Performance Management Highlights, December 2016

Balancing the accountNote: To support questions from enterprise buyers and private investors interested in the Enterprise Performance Management market across Planning, Budgeting, Forecasting, Consolidation, Close, and Audit, Blue Hill provides a monthly review of the key announcements made in this space for companies including, but not limited to: Adaptive Insights, Anaplan, Axiom EPM, Blackline, Board, Budget Maestro, Capital Confirmation, FloQast, Host Analytics, IBM, Longview, Onestream, Oracle, Prophix, SAP, Tagetik, Tidemark, Trintech, and Workday.

As enterprise performance and financial control companies finished up the year, Blue Hill noted a trend in ongoing integration and application development from press releases announced in December. Noted announcements included the following from Adaptive Insights, Anaplan, BOARD, and Tagetik.

Adaptive Insights

Adaptive Insights Completes Over 1,500 Integrations Across More than 100 Different Systems

On December 15th, Adaptive Insights announced that it had supported over 1,500 integrations across enterprise applications ranging from ERP to CRM to HR. In this release, Adaptive noted integrations with Intacct, Microsoft Dynamics, NetSuite, Oracle, SAP, Salesforce, and Workday as examples of common integrations across Adaptive’s portfolio of over 3,000 customers.

Blue Hill believes these integration requests reflect the increasing need for the CFO to track non-financial data associated with corporate performance or strategy execution. As financial professionals continue to evolve the maturity of their planning, budgeting, and forecasting capabilities, the next stage of maturity is to effectively integrate planning with non-financial systems to gain business-based context for existing financial data.

Anaplan

Anaplan Launches Application Lifecycle Management for Cloud EPM

On December 13, Anaplan announced Application Lifecycle Management in its 2016.4 release. This capabilities allows Anaplan customers to manage the operational aspects of application development and deployment while improving security, audit, and controls associated with enterprise data. In addition, the 2016.4 release also includes integration and visualization improvements associated with partnerships with Informatica and Tableau.

This capability showcases Anaplan’s flexibility in supporting a wide variety of enterprise capabilities as a planning platform. Blue Hill believes that Anaplan’s ALM capabilities, coupled with partnerships with enterprise market leaders, demonstrates Anaplan’s continued focus on providing an extremely flexible back-end platform for development while maintaining a user-friendly and contextualized front-end for end users.

Board

BOARD International Names Michael Talbott Global Product Director and Evangelist

BOARD partners with Spiral Data

BOARD partners with Sopra Steria

BOARD was especially active in December both in hiring Michael Talbott as BOARD’s Global Evangelist and in setting up partnerships with Spiral Data in Australia and with Sopra Steria to support digital transformation efforts.

All three of these announcements are important as BOARD continues to expand its scope. Since September 2015, when BOARD 10 was released, BOARD has been able to provide a combination of financial planning, BI, and analytics on the Microsoft Azure cloud. This has allowed BOARD to more aggressively pursue both markets that are cloud-focused in their pursuit of enterprise applications and markets focused on digital transformation. Blue Hill believes that this combination of evangelism and strategic partners will be valuable to BOARD in 2017 as the company continues to refresh its brand and directly compete with other Cloud EPM vendors.

Tagetik

Tagetik launches Tagetik Nordic AB to serve Sweden, Denmark, Norway, Finland, and Iceland

On December 1st, Tagetik announced a new subsidiary, Tagetik Nordic AB, based out of Stockholm, Sweden. This company was created after Tagetik acquired its distributor in the Nordic market and allows Tagetik to directly support Nordic customers across sales and professional services needed in these markets.

Blue Hill notes that the “European” market is actually 44 different countries. To successfully support European customers, enterprise software vendors must pick and choose the countries that they are willing to support. Tagetik’s investment in the Nordic market is a logical extension both of Tagetik’s business success and partnership with Qlik.

Blue Hill Research Communications Lifecycle Management Highlights: December 2016

Blue Hill Research Communications Lifecycle Management HighlightsNote: To support questions from enterprise buyers and private investors that are looking at Telecom Expense Management and the greater Communications Lifecycle Management world, Blue Hill is starting a monthly review of the key announcements made in this space for companies in this space including, but not limited to: 4telecomhelp, ACCOUNTabill, Advantix, AMI Strategies, Anatole, Asentinel, Avotus, Calero, Cass Information Systems (NASDAQ: CASS), Cimpl (formerly Etelesolv), Comview, EZwim, GSGTelco, IBM Global Services (NYSE: IBM), ICOMM, MDSL, mindWireless, MOBI, Mobichord, Mobile Solutions Services, MobilSense, MTS (NASDAQ: MTSL), Nebula, NetPlus, Network Control, Tangoe (NASDAQ: TNGO), Telesoft, Valicom, vCom, Visage, and Vodafone Global Enterprise (NASDAQ: VOD)

Communications Lifecycle Management news items that have gotten Blue Hill’s attention in December 2016 include announcements from Asentinel, Cass Information Systems, mindWireless, NetPlus, Tangoe, and Vodafone.

Asentinel

Asentinel Hires Philippe Lignac As Global Head of Sales

On December 21, Asentinel announced that Philippe Lignac has joined the company as global Chief Sales Officer. Prior to joining Asentinel, Lignac served as Global Sales Director at MDSL.

Blue Hill notes that Asentinel has grown strategically in the past few years through appointments of a new Chief Marketing Officer, Mark Ledbetter, as well as through acquisitions of eMOBUS and Anatole. As the global TEM market becomes more competitive, Asentinel is aggressively positioning itself as a market leader by investing in strategic opportunities from a talent and acquisition perspective.

Cass Information Systems

Cass Information Systems Inc (CASS) Breaks into New 52-Week High on December 27 Session

On December 27, shares of Cass Information Systems Inc. broke into a new 52-week high, hitting a peak of $74.83. Shares closed at $74.44, up 1.21% from opening at $74.10. The company now has a market cap of $831.96 million.

In Blue Hill’s November 2016 Communications Lifecycle Management Highlights, we wrote about Cass’ stock hitting a new 52-week high on November 21, closing at $72.21 per share. Cass continues to experience stock growth month over month, demonstrating that investors are confident in Cass’ future earnings. Blue Hill profiled Cass as a key Telecom Expense Management vendor equipped to manage TEM on a global scale in our Global Telecom Expense Management Landscape.

mindWireless

mindWireless Continues to Lead Corporate Wireless Management After Recent Expansion

On December 6, mindWireless announced that it has relocated its headquarters from Houston, Texas to Austin, Texas, undertaking a 40% expansion of the company’s office space. The company cited its motivation in relocating to Austin as a desire to take part in the growing tech community present in the city.

Blue Hill notes that as mobile expense management providers continue to compete heavily on the strength of their software solutions, recruiting from a tech-focused community like Austin is strategic. Relocating to Austin may attract a different talent pool for mindWireless as the company continues to prioritize mobile and to build out its wireless consulting business. The expansion of the company’s office space will allow mindWireless to invest in and grow its service and support teams going forward.

NetPlus

NetPlus Appoints New Senior Mobility Manager for Enterprise Mobility Management

On December 19, NetPlus announced that Michael Cardinal has joined the company as Senior Mobility Sales Manager for NetPlus’ mobile device management and expense management suites. Cardinal brings to the company his 15-year background in wireless and mobile technology, serving in management positions for top wireless carriers in the US.

Blue Hill notes that Cardinal’s experience and carrier perspective will be well suited to continuing to build out NetPlus’ mobile expense management solutions. His existing carrier contacts and past relationships may prove a competitive advantage for NetPlus in broadening its support for major US carriers and negotiating favorable contracts for enterprise clients.

Tangoe

Tangoe Expands Logistics Facility to Serve the Expanding Managed Mobility Services Market

On December 14, Tangoe announced the opening of its newly expanded Logistics Center in Austin, Texas to support forward and reverse logistics for enterprise customers. The new facility will increase Tangoe’s scale to undertake onsite repairs, replenishments, and customizations for enterprises, and will grow Tangoe’s logistics transactions from 10,000 to 50,000 per month. The facility will process a range of mobile devices including smartphones, tablets, laptops, IoT devices, and other IT assets.

Blue Hill covered this announcement in greater detail in a recent blog post, in which we remarked that Tangoe’s expanded logistics capabilities will enable the company to further support enterprises seeking Managed Mobility Services (MMS) and Mobility-as-a-Service (MaaS) offerings from Tangoe. Support for IoT devices demonstrates Tangoe’s continuing investments in scaling to meet the IT needs of global enterprises.

Vodafone

Vodafone Appoints Brian Humphries as Group Enterprise Director

On December 6, Vodafone announced it has appointed Brian Humphries as Group Enterprise Director. Beginning in February 2017, Humphries will oversee Vodafone Global Enterprises, the Group’s dedicated multinational unit with over 1,700 enterprise customers, as well as Vodafone’s Internet of Things (IoT), Cloud Hosting, and Carrier Services businesses. Enterprise accounted for 28% of Vodafone Group revenue as of September 30, 2016. Humphries is currently serving as the President and Chief Operating Officer, Infrastructure Group at Dell EMC, and has previously worked in senior executive roles at Hewlett-Packard.

Blue Hill notes that Dell EMC and Hewlett-Packard Enterprise (HPE) – companies at which Humphries has previously served in executive leadership roles – have recently invested in building out cloud infrastructure and IoT businesses. Blue Hill finds it interesting that Vodafone has picked up expertise from Dell EMC, which Blue Hill has previously described as betting big on cloud computing.

The Hadooponomics Podcast, Episode 18 – Big Government, Big Tech … Big Trouble? How Tech and Global Policy Can Co-Exist

Hadooponomics18This week on Hadooponomics, we have on the show Evan Swarztrauber, Communications Director at TechFreedom, a Washington D.C. think tank for tech advocacy, and host of the Tech Policy Podcast. With Evan’s background in tech policy, we dive into the intersection of data, policy, and the public good in this episode, to explore how technology, government, and individual liberty can co-exist in the age of Big Data.

We begin by juxtaposing the government side of Big Data with the commercial side, and exploring why each may have different outcomes for and rationale behind Big Data collection. In the U.S., we largely see these two Big Data buckets as distinct, though in reality there are privacy and security implications for Big Data collection regardless of whether it is driven by a commercial relationship (like with Google), or a surveillance relationship (like with the government).

As we saw with the Dyn DDoS attack, in which consumer devices connected to the Internet were targeted, unregulated technologies can pose security concerns even when users “consent” to share data with the device or business. With government leaks, such as from Edward Snowden and WikiLeaks, there is now an incentive to secure data and products not just from commercial entities but also from the government.

The potential of Big Data and Big Tech is exciting and the possibilities seemingly endless. But with emerging technologies like autonomous vehicles, there is a balancing act between supporting potentially life-changing innovations, and providing the policy regulation to ensure the technology is explored and developed with security, privacy, and consumer protection in mind. We discuss how we can balance these concerns while accommodating varied stakeholder interests including from Big Data practitioners, commercial entities, governments, and citizens, on a global scale.

For those of you keeping track at home, this is the final episode of Season 3 of the Hadooponomics Podcast. It has been a pleasure sharing these stories with you this season and exploring the wide reach of Big Data across industries and across the globe. Be sure to check back here for updates on Season 4 and I thank you for being a part of this great season!

Enjoy!

Listen to the Show:

Use the embedded media player to stream the full episode or you can subscribe to our iTunes and Stitcher channels. The full transcript of the interview is also available.

PodcastHadooponomics Podcast Home | Subscribe via iTunes | Stitcher Radio | Transcript

Additional Resources

TechFreedom Website

The Tech Policy Podcast

Find Evan on Twitter

About Arcadia Data:

Arcadia Data Logo

Arcadia Data unifies visual analysis, business intelligence and data discovery; it runs natively on your Hadoop clusters without data extracts. Its easy-to-use browser-based visualizations deliver secure access for hundreds of concurrent users across hundreds of billions of rows in near-real time.

The Hadooponomics Podcast, Episode 17 – Data and Decision Makers: The Human “Resources” for Big Data in HR

Hadooponomics17For our next episode of Hadooponomics, we look at the intersection of Human Resources (HR) and Big Data to determine how companies can take human-based data, which is inherently non-numeric, and attempt to quantify it. We have on the show Evan Sinar, Chief Scientist and Vice President of Development Dimensions International (DDI), a company focused on using data to identify and develop leadership in the enterprise. Evan applies his background in industrial organizational psychology to understanding the human side of Big Data and leadership.

We cover a lot of ground in this episode, from best practices in data visualization to the transformative power of Big Data, what it means to be a leader, and how HR and Big Data overlap. We’ve seen throughout the show the overwhelming impact Big Data and data-driven decision making has on organizations, and this is true across departments and functional groups. But as Evan points out, HR has typically been slow to adopt data-based decision making, and part of this has to do with the complex nature of human data.

According to Evan, organizations need to be savvier about people analytics, including what data they are collecting, how they are collecting it, and how they are using that data. The human-oriented nature of HR produces data that is typically non-numeric, and thus difficult to analyze using traditional Big Data methodologies. Evan describes how we can begin to quantify this “human element” that has been missing from Big Data of the past. But there’s another problem with relying on Big Data as a blanket solution: there should always be the role of a human expert to make the final judgment call.

How do we reconcile these seemingly contradictory ideals? And how can Big Data begin to understand the human element, enough to potentially assess tough-to-define qualities, like leadership ability, that previously required human judgment? Evan has some answers and we explore these concepts, and the data-oriented organizational structures and leadership of the future, in this episode.

Enjoy!

Listen to the Show:

Use the embedded media player to stream the full episode or you can subscribe to our iTunes and Stitcher channels. The full transcript of the interview is also available.

PodcastHadooponomics Podcast Home | Subscribe via iTunes | Stitcher Radio | Transcript

Additional Resources

Find Evan on Twitter @EvanSinar

Find Evan on LinkedIn

Follow Evan’s Blog at DDI

About Arcadia Data:

Arcadia Data Logo

Arcadia Data unifies visual analysis, business intelligence and data discovery; it runs natively on your Hadoop clusters without data extracts. Its easy-to-use browser-based visualizations deliver secure access for hundreds of concurrent users across hundreds of billions of rows in near-real time.