Is IBM’s Acquisition of Red Hat the Biggest Acquihire of All Time?

Estimated Reading Time: 11 minutes

Internally, Amalgam Insights has been discussing why IBM chose to acquire Red Hat for $34 billion dollars fairly intensely. Our key questions included:

  • Why would IBM purchase Red Hat when they’re already partners?
  • Why purchase Red Hat when the code is Open Source?
  • Why did IBM offer a whopping $34 billion, $20 billion more than IBM currently has on hand?

As a starting point, we posit that IBM’s biggest challenge is not an inability to understand its business challenges, but a fundamental consulting mindset that starts with the top on down. By this, we mean that IBM is great at identifying and finding solutions on a project-specific basis. For instance, SoftLayer, Weather Company, Bluewolf, and Promontory Financial are all relatively recent acquisitions that made sense and were mostly applauded at the time. But even as IBM makes smart investments, IBM has either forgotten or not learned the modern rules for how to launch, develop, and maintain software businesses. At a time when software is eating everything, this is a fundamental problem that IBM needs to solve.

The real question for IBM is whether IBM can manage itself as a modern software company.

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From Calero World Online: From TEM to ITEM: Leveraging TEM for Non-Traditional Expenses

On October 18th, I presented a webinar at Calero World Online on the future of IT cost and subscription management. In this presentation, I challenge existing telecom and IT expense management managers to accept their destiny as pilots and architects of enterprise digital subscriptions.

Telecom expense has traditionally been the most challenging of IT costs to manage. With the emergence of software-as-a-service, cloud computing, the Internet of Things, and software-defined networks, the rest of the IT world is quickly catching up.

In this webinar, you will learn:

  • How the latest trends and technology are driving change to enterprise management strategies
  • How the challenges of traditional TEM and cloud expense management are similar in nature (and why TEM is a good place to start)
  • How organizations are benefiting from ITEM best practices using sample use cases

To learn more about the upcoming challenges of IT expense management, aligning technology supply to digital demand, and being the shepherd for your organization’s technology sourcing, utilization, and optimization, click here to watch this webinar on-demand.

ICYMI: On Demand Webinar – Four Techniques to Run AI on Your Business Data

On October 17th, I presented a webinar with Incorta’s Chief Evangelist, Matthew Halliday, on the importance of BI architectures in preparing for AI. This webinar is based on a core Amalgam Insights belief that all enterprise analytics and data science activity should be based on a shared core of trusted and consistent data so that Business Intelligence, analytics, machine learning, data science, and deep learning efforts are all based on similar assumptions and can build off each other.

While AI is beginning to impact every aspect of our consumer lives, business data-driven AI seems to be lower on the priority list of most enterprises. The struggle to understand the practical value of AI starts with the lack of ability to make business data easily accessible to the data science teams. Today’s BI tools have not kept up with this need and often are the bottlenecks that stifle innovation.

In this webinar, you will learn from Hyoun Park and Matthew Halliday about:
  • key data and analytic trends leading to the need to accelerate analytic access to data.
  • guidance for challenges in implementing AI initiatives alongside BI.
  • practical and future-facing business use cases that can be supported by accelerating analytic access to large volumes of operational data.
  • techniques that accelerate AI initiatives on your business data.

Watch this webinar on-demand by clicking here.

Why It Matters that IBM Announced Trust and Transparency Capabilities for AI


Note: This blog is a followup to Amalgam Insights’ visit to the “Change the Game” event held by IBM in New York City.

On September 19th, IBM announced its launch of a portfolio of AI trust and transparency capabilities. This announcement got Amalgam Insight’s attention because of IBM’s relevance and focus in the enterprise AI market throughout this decade.  To understand why IBM’s specific launch matters, take a step back in considering IBM’s considerable role in building out the current state of the enterprise AI market.

IBM AI in Context

Since IBM’s public launch of IBM Watson on Jeopardy! in 2011, IBM has been a market leader in enterprise artificial intelligence and spent billions of dollars in establishing both IBM Watson and AI. This has been a challenging path to travel as IBM has had to balance this market-leading innovation with the financial demands of supporting a company that brought in $107 billion in revenue in 2011 and has since seen this number shrink by almost 30%.

In addition, IBM had to balance its role as an enterprise technology company focused on the world’s largest workloads and IT challenges with launching an emerging product better suited for highly innovative startups and experimental enterprises. And IBM also faced the “cloudification” of enterprise IT in general, where the traditional top-down purchase of multi-million dollar IT portfolios is being replaced by piecemeal and business-driven purchases and consumption of best-in-breed technologies.

Seven years later, the jury is still out on how AI will ultimately end up transforming enterprises. What we do know is that a variety of branches of AI are emerging, including

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IBM Presents “Change the Game: Winning with AI” in New York City

(Note: This blog is part of a multi-part series on this event and the related analyst event focused on IBM’s current status from an AI perspective.) On September 13th, 2018, IBM held an event titled “Change the Game: winning with AI.” The event was hosted by ESPN’s Hannah Storm and held in Hell’s Kitchen’s Terminal…

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EPM at a Crossroads: Big Data Solutions

Key Stakeholders: Chief Information Officers, Chief Financial Officers, Chief Operating Officers, Chief Digital Officers, Chief Technology Officer, Accounting Directors and Managers, Sales Operations Directors and Managers, Controllers, Finance Directors and Managers, Corporate Planning Directors and Managers

Analyst-Recommended Solutions: Adaptive Insights, a Workday Company, Anaplan, Board, Domo, IBM Planning Analytics, OneStream, Oracle Planning and Budgeting, SAP Analytics Cloud

In 2018, the Enterprise Performance Management market is at a crossroads. This market has emerged from a foundation of financial planning, budgeting, and forecasting solutions designed to support basic planning and has evolved as the demands for business planning, risk and forecasting management, and consolidation have increased over time. In addition, the EPM market has expanded as companies from the financial consolidation and close markets, business performance management markets, and workflow and process automation markets now play important roles in effectively managing Enterprise Performance.

In light of these challenges, Amalgam Insights is tracking six key areas where Enterprise Performance Management is fundamentally changing: Big Data, Robotic Process Automation, API connectivity, Analytics and Data Science, Vertical Solutions, and Design Thinking for User Experience

Supporting Big Data for Enterprise Performance Management

Amalgam Insights has identified two key drivers repeatedly mentioned by finance departments seeking to support Big Data in Enterprise Performance Management. First, EPM solutions must support larger stores of data over time to fully analyze financial data and a plethora of additional business data needed to support strategic business analysis. The challenge of growing data has become increasingly important as enterprises now face the challenge of managing billion row tables and outgrow the traditional cubes and datamarts used to manage basic financial data. The sheer scale of financial and commerce-related transactional data requires a Big Data approach at the enterprise level to support timely analysis of planning, consolidation, close, risk, and compliance.

In addition, these large data sources need to integrate with other data sources and references to support integrated business planning to align finance planning with sales, supply chain, IT, and other departments. As the CFO is increasingly asked to be not only a financial leader, but a strategic leader, she must have access to all relevant business drivers and have a single view of how relevant sales, support, supply chain, marketing, operational, and third-party data are aligned to financial performance. Each of these departments has its own large store of data that the strategic CFO must also be able to access, allocate, and analyze to guide the business.

New EPM solutions must evolve beyond traditional OLAP cubes to support hybrid data structures that effectively scale to support the immense scale and variety of data being supported. Amalgam notes that EPM solutions focusing on large data solutions take a variety of relational, in-memory, columnar, cloud computing, and algorithmic approaches to define categories on the fly, store, structure, and analyze financial data.

To support these large stores of data and effectively support them from a financial, strategic, and analytic perspective, Amalgam Insights recommends the following companies that have been innovative in supporting immense and varied planning and budgeting data environments based on briefings and discussions held in 2018:

  • Adaptive Insights, a Workday Company
  • Anaplan
  • Board
  • Domo
  • IBM Planning Analytics
  • OneStream
  • Oracle Planning and Budgeting
  • SAP Analytics Cloud

Adaptive Insights

Adaptive Insights’ Elastic Hypercube, an in-memory, dynamic caching and scaling solution announced in July 2018. Amalgam Insights saw a preview of this technology at Adaptive Live and was intrigued by the efficiency that Adaptive Insights provided to models in selectively recalculating only the dependent changes as a model was edited, using a dynamic caching approach for only using memory and computational cycles when data was being accessed, and using both tabular and cube formats to support data structures. This data format will also be useful to Adaptive Insights as a Workday company in building out the various departmental planning solutions that will be accretive to Workday’s positioning as an HR and ERP solution after Workday’s June acquisition (covered in June in our Market Milestone).

Anaplan

Anaplan’s Hyperblock is an in-memory engine combining columnar, relational, and OLAP approaches. This technology is the basis of Anaplan’s platform and allows Anaplan to rapidly support large planning use cases. By developing composite dimensions, Anaplan users can pre-build a broad array of combinations that can be used to repeatably deploy analytic outputs. As noted in our March blog, Anaplan has been growing rapidly based on its ability to rapidly support new use cases. In addition, Anaplan has recently filed its S-1 to go public.

Board

Board goes to market both as an EPM and a general business intelligence solution. Its core technology is the Hybrid Bitwise Memory Pattern (HBMP), a proprietary in-memory data management solution, designed to algorithmically map each bit of data, then to store this map in-memory. In practice, this approach allows Board to allow many users to both access and edit information without dealing with lagging or processing delays. This approach also allows Board to support which aspects of data to support in an in-memory or dynamic manner to prioritize computing assets.

Domo

Domo describes its Adrenaline engine as an “n-dimensional, highly concurrent, exo-scale, massively parallel, and sub-second data warehouse engine” to store business data. This is accompanied by VAULT, Domo’s data lake to support data ingestion and serve as a single store of record for business analysis. Amalgam Insights covered the Adrenaline engine as one of Domo’s “Seven Samurai” in our March report Domo Hajimemashite: At Domopalooza 2018, Domo Solves Its Case of Mistaken Identity. Behind the buzzwords, these technologies allow Domo to provide executive reporting capabilities across a wide range of departmental use cases in near-real time. Although Domo is not a budgeting solution, it is focused on portraying enterprise performance for executive consumption and should be considered for organizations seeking to gain business-wide visibility to key performance metrics.

IBM Planning Analytics

IBM Planning Analytics runs on Cognos TM1 OLAP in-memory cubes. To increase performance, these cubes use sparse memory management where missing values are ignored and empty values are not stored. In conjunction with IBM’s approach of caching analytic outcomes in-memory, this approach allows IBM to improve performance compared to standard OLAP approaches and this approach has been validated at scale by a variety of IBM Planning Analytics clients. Amalgam Insights presented on the value of IBM’s approach at IBM Vision 2017 both from a data perspective and from a user interface perspective that will be covered in a future blog.

OneStream

OneStream provides in-memory processing & stateless servers to support scale, but their approach to analytic scale is based on virtual cubes and extensible dimensions, which allow organizations to continue building dimensions over time that are tied back to a corporate level and to create logical views of data based on a larger data store to support specific financial tasks such as budgeting, tax reporting, or financial reporting. OneStream’s approach is focused on financial use rather than general business planning.

Oracle Planning and Budgeting Cloud

Oracle Planning and Budgeting Cloud Service is based on Oracle Hyperion, the market leader in Enterprise Performance Management from a revenue perspective. The Oracle Cloud is built on Oracle Exalogic Elastic Cloud, Oracle Exadata Database Machine, and the Oracle Database, which provide a strong in-memory foundation for the Planning and Budgeting application by providing an algorithmic approach to manage storage, compute, and networking. This approach effectively allows Oracle to support planning models at massive scale.

SAP Analytics Cloud

SAP Analytics Cloud, SAP’s umbrella product for planning and business intelligence, uses SAP S/4HANA, an in-memory columnar relational database, to provide real-time access to data and to accelerate both modelling and analytic outputs based on all relevant transactional data. This approach is part of SAP’s broader HANA strategy to encapsulate both analytic and transactional processing in a single database, effectively making all data reportable, modellable, and actionable. SAP has also recently partnered with Intel Optane DC persistent memory to support larger data volumes for enterprises requiring larger persistent data stores for analytic use.

This blog is part of a multi-part series on the evolution of Enterprise Performance Management and key themes that the CFO office must consider in managing holistic enterprise performance: Big Data, Robotic Process Automation, API connectivity, Analytics and Data Science, Vertical Solutions, and Design Thinking for User Experience. If you would like to set up an inquiry to discuss EPM or provide a vendor briefing on this topic, please contact us at info@amalgaminsights.com to set up time to speak.

Last Blog: EPM at a Crossroads
Next Blog: Robotic Process Automation and Machine Learning in EPM

FloQast Supports ASC 606 Compliance by Providing a Multi Book Close for Accountants

On September 11, 2018, FloQast announced multi-book accounting capabilities designed to help organizations to support ASC 606 compliant financial closes by supporting dual reporting on revenue recognition and related expenses. As Amalgam Insights has covered in prior research, ASC 606/IFRS 15 standards for recognizing revenue on subscription services are currently required for all public companies…

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VMware Purchases CloudHealth Technologies to support Multicloud Enterprises and Continue Investing in Boston


Vendors and Solutions Mentioned: VMware, CloudHealth Technologies, Cloudyn, Microsoft Azure Cloud Cost Management, Cloud Cruiser, HPE OneSphere. Nutanix Beam, Minjar, Botmetric

Key Stakeholders: Chief Financial Officers, Chief Information Officers, Chief Accounting Officers, Chief Procurement Officers, Cloud Computing Directors and Managers, IT Procurement Directors and Managers, IT Expense Directors and Managers

Key Takeaway: As Best-of-Breed vendors continue to emerge, new technologies are invented, existing services continue to evolve, vendors pursue new and innovative pricing and delivery models, cloud computing remains easy to procure, and IaaS doubles every three years as a spend category, cloud computing management will only increase in complexity and the need for Cloud Service Management will only increase. VMware has made a wise choice in buying into a rapidly growing market and now has greater opportunity to support and augment complex peak, decentralized, and hybrid IT environments.

About the Announcement

On August 27, 2018, VMware announced a definitive agreement to acquire CloudHealth Technologies, a Boston-based startup company focused on providing a cloud operations and expense management platform that supports enterprise accounts across Amazon Web Services, Microsoft Azure, and Google Cloud Platform.

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Oracle Autonomous Transaction Processing Lowers Barriers to Entry for Data-Driven Business

I recently wrote a Market Milestone report on Oracle’s launch of Autonomous Transaction Processing, the latest in a string of Autonomous Database announcements made by Oracle following announcements in Autonomous Data Warehousing and the initial announcement of the Autonomous Database late last year. This string of announcements by Oracle takes advantage of Oracle’s investments in…

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Azure Advancements Announced at Microsoft Inspire 2018

Last week, Microsoft Inspire took place, which meant that Microsoft made a lot of new product announcements regarding the Azure cloud. In general, Microsoft is both looking up and trying to catch up to Amazon from a market share perspective while trying to keep its current #2 place in the Infrastructure as a Service world ahead of rapidly growing Google Cloud Platform as well as IBM and Oracle.  Microsoft Azure is generally regarded as a market-leading cloud platform, along with Amazon, that provides storage, computing, and security and is moving towards analytics, networking, replication, hybrid synchronization, and blockchain support.

Key functionalities that Microsoft has announced include:

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