Infor Advances Data Agenda With ‘Coleman’ AI, Birst BI Integration

Doug Henschen

Former Vice President and Principal Analyst
Constellation Research

Doug Henschen is former Vice President and Principal Analyst where he focused on data-driven decision making. Henschen’s Data-to-Decisions research examines how organizations employ data analysis to reimagine their business models and gain a deeper understanding of their customers. Henschen's research acknowledges the fact that innovative applications of data analysis requires a multi-disciplinary approach starting with information and orchestration technologies, continuing through business intelligence, data-visualization, and analytics, and moving into NoSQL and big-data analysis, third-party data enrichment, and decision-management technologies. Insight-driven business models are of interest to the entire C-suite, but most particularly chief executive officers, chief digital officers,…...

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Infor lays out plans for artificial intelligence and cloud-based business intelligence and analytics. Here’s what customers need to know.

Infor entered the increasingly crowded artificial intelligence (AI) arena July 11 by introducing its Coleman AI platform. Unveild at the company’s Inforum 2017 event in NY, Coleman was described as a language- and image-savvy AI platform that will automate rote tasks and augment human capabilities in a range of industry-specific use cases. Infor also used Inforum to detail its plans for Brist, the cloud-based business intelligence platform acquired in April.

Named for ’60-era NASA data scientist Katherine Coleman Johnson, one of three African American NASA mathematicians portrayed in the 2016 film “Hidden Figures,” Coleman builds on Infor assets including machine learning capabilities for retail acquired with Predictix and the work of the company’s Dynamic Science Labs. The labs have developed apps including a price optimization app for distributors and an inventory optimization app for healthcare providers.

Existing apps and machine learning capabilities are being folded into the Coleman portfolio, and Infor says it’s also well along in developing a unifying data platform for AI. Built on Amazon Web Services infrastructure, including an Amazon S3 data lake, the platform will aggregate petabytes of data available from Infor’s various industry-focused CloudSuites. The data will fuel AI-powered optimization, recommendation, and decision-automation services that will be delivered through Infor’s Ion API-integration platform.

Infor will use the speech recognition and natural language understanding capabilities of the Amazon Lex AI service to power conversational capabilities. This will enable Coleman to serve as a human assistant, answering questions such as, “Coleman, what are the payments outstanding for company X,” or “Coleman, forecast demand for product Y.” Conversational UIs will also support multi-faceted processes with simple requests such as, “Coleman, approve the promotion of Sara Jones.”

With image-recognition capabilities, Coleman will turn smart phone cameras into search tools. Take a picture of a product, for example, and Coleman will be able to identify the product and detail prices, specifications and availability details. Used internally, Coleman will tell workers how much inventory is available, what’s on order, when it will arrive and whether alternatives are available from other suppliers.

MyPOV on Coleman Vision vs. Reality

Infor certainly offered a compelling AI vision, but executives also acknowledged that it’s “early days” for Coleman. Data-pipeline development and modeling is further along in some industries than others, they acknowledged. Smart services for retail are likely to arrive first. As for the ingredients of Coleman, it’s a mixed collection of Infor and third-party IP. It remains to be seen just how it will all come together and when we’ll start seeing smart prediction, recommendation, optimization, and automation services beyond what existed before Coleman was announced.

I’m particularly eager to understand how and whether Infor uses generalized models based on aggregated CloudSuite data and then develops customer-specific recommendations and smart services. With its recent Leonardo launch, SAP talked about combining shared models and customer-specific models. Customers will also want to know whether it’s as simple as “turning Coleman on” from within a CloudSuite, as Infor executives suggested. We have also yet to learn just how much data will be required to generate reliable predictions, recommendations, optimization and automated actions.

Infor’s Birst Acquisition and Plans for Analytics

When Infor announced the acquisition of Birst in April, the first question for customers of the cloud-based BI company was, “will Birst disappear as an independent company?” The answer was an emphatic no. Birst operations continue unchanged under the direction of the existing management team. Birst founder and CEO, Brad Peters, continues as General Manager of what’s now known as “Birst, an Infor Company.”

The first question for Infor customers was, “how will Birst work with my existing Infor BI investments, including Cognos-based reporting tools and Infor BI cubes?” The company laid out detailed integration plans at Inforum.

In the first phase of the three-phase plan, currently underway, Infor customers can swap out like-for-like capabilities that they’ve licensed from Infor for newer, cloud-based capabilities from Birst. For example, customers using Infor’s Cognos-based reporting tools can switch to reporting tools available from Birst. They’ll also be able to add capabilities, at extra cost, that weren’t available from Infor, such as Birst’s ETL engine and self-service data-exploration and visualization capabilities.

Infor has already integrated Birst with Infor Ming.le collaboration and single-sign-on capabilities, but phase two, expected to be completed in September, will bring even deeper levels of integration. For example, customers using Infor BI will be able to use Birst as a cloud-based environment for analysis and reporting. This will enable Infor customers to leverage their Infor BI cubes while also blending in external data sources and taking advantage of Birst’s modern data-exploration and visualization capabilities. Integration is also underway between Infor’s Amazon S3- and Athena-based data lake environment and Birst. This will extend Birst’s big data analysis capabilities.

In phase three, Birst will add predictive capabilities from Infor’s Dynamic Science Labs unit. We’ll also see deeper integration of Birst-powered analytic services into the Infor XI platform as well as ties to Coleman AI services. The delivery date for phase three was unspecified.

MyPOV on Birst Integration

Infor is doing its best to preserve existing customer investments while providing an upgrade path to newer and more extensive Birst capabilities. On the reporting front there’s not a migration path for existing operational reports, so customers will likely gradually phase out existing tools supporting legacy reports while building new reports on Birst. The deeper and more significant value is in Infor BI, so it’s a big win for customers to see those cubes integrated with Birst’s cloud-accessible, self-service analytical environment. Overall, Birst brings significant upgrades to Infor’s analytics layer that will help support the company’s move into big data and artificial intelligence.

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Cloud Configure Price Quote Solutions Deliver 10 Compelling Benefits - My New Report

Cindy Zhou

CMO
Level Access

Cindy Zhou is a practicing CMO.  Prviously, she was Vice President and Principal Analyst at Constellation Research covering Digital Marketing Transformation and Sales Effectiveness. With over 18 years of practitioner experience in corporate marketing, product marketing, product management, and sales operations, Zhou has spearheaded marketing transformation at multiple technology companies. She advised Constellation’s clients on strategies to light-up demand generation, prove revenue contribution, and maximize sales productivity. Prior to joining Constellation, Zhou was Global Senior Vice President of Marketing and Sales Operations at BackOffice Associates, a global provider of data quality and information governance solutions to the Fortune 1000 and SAP SolEx partner. Before…...

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• Understand the value CPQ solutions can deliver
• Data to help you build a business case
• Questions to ask when selecting a vendor
• Success stories for inspiration
• Implementation tips and best practices

Microsoft 365 Plus the Always Expanding Office 365 Portfolio

Alan Lepofsky

Vice President & Principal Analyst
Constellation Research

Alan Lepofsky - VP and Principal Analyst, Constellation Research. With almost two decades of experience in the collaboration software industry, Lepofsky helps organizations improve the way their employees work together to get their jobs done. Lepofsky’s primary research area The Future of Work, focuses on: integrating collaboration and business processes (Purposeful Collaboration), structuring work via Social Task Management, leveraging analytics and digital assistants to work more productively, the strategic impact of mobile computing on business transformation, and measuring workforce culture based on Digital Proficiency instead of age. Twitter: @alanlepoLinkedIn: https://ca.linkedin.com/in/alanlepo     , Title: Big IdeasIntelligent Collaboration: The Intersection of…...

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July 10th at Microsoft Inspire, their Worldwide Business Partner conference, Microsoft introduced Microsoft 365, a new purchasing model that bundles Windows + Office 365 + Enterprise Mobility and Security.

They also introduced three new (SMB focused) business applications... plus made MileIQ available to select O365 plans.

• Microsoft Connections—A simple-to-use email marketing service.
• Microsoft Listings—An easy way to publish your business information on top sites.
• Microsoft Invoicing—A new way to create professional invoices and get paid fast

Microsoft Continues To Strive for the Modern Workplace

I was very pleased to see Microsoft continue to push the messages around the intersection of Personal Productivity/Team Collaboration and Artificial Intelligence. In the keynote, they demonstrated several scenarios where Office365 is being enhanced with automation from Cortana and Microsoft Cognitive Services. Perhaps the most impressive (Future of Work) demo was how Microsoft combines Yammer and Stream to hold all company town hall meetings, where the talks are transcribed and translated in real time by Microsoft's AI tools.

Here is the information I collected during the keynote:

DisrupTV Dissects the Top Headlines on AI, Digital Transformation & Data Breaches

Aubrey Coggins

Constellation Research

Aubrey (Levinstone) Coggins manages Constellation's marketing and communications programs and is the producer of DisrupTV, a weekly Web series on innovation and the enterprise.  She previously served as a senior manager of corporate communications at Egnyte and held account roles at Access Communications and The Hoffman Agency. Born and raised in Texas, she received a bachelor's degree in Public Relations from The University of Texas at Austin – Hook ‘em!   ...

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From “Black Friday in July,” to conference after conference, and a not-so-small data breach, this week was jam-packed with news and chatter from some of the biggest companies across industries.

We were lucky to catch up with Larry Dignan, editor in chief at ZDNet, on DisrupTV this week. He joined our hosts Vala Afshar and R “Ray” Wang to provide some blunt and entertaining commentary on the major news items that topped the headlines this week – from Amazon, SAP, Workday, Microsoft, Infor, and OpenText, Verizon and Wendy’s.

Jump into the video below at 39 minutes for the start of Larry’s segment.

DisrupTV Episode 70: Scott Hartley, Avi Goldberg, Larry Dignan from Constellation Research on Vimeo.

Blockchain or Distributed Ledger? Defining the requirement, not the technology

Andy Mulholland

Vice President and Principal Analyst, Constellation Research
Constellation Research

Andy Mulholland is Vice President and Principal Analyst focusing on cloud business models. Formerly the Global Chief Technology Officer for the Capgemini Group from 2001 to 2011, Mulholland successfully led the organization through a period of mass disruption. Mulholland brings this experience to Constellation’s clients seeking to understand how Digital Business models will be built and deployed in conjunction with existing IT systems. Coverage Areas Consumerization of IT & The New C-Suite: BYOD, Internet of Things, IoT, technology and business use Previous experience: Mulholland co authored four major books that chronicled the change and its impact on Enterprises starting in 2006 with the well-recognised book ‘Mashup Corporations’ with Chris Thomas of Intel. This was followed in…...

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Currently Blockchain is firmly established on the hype curve, and as with all technologies at this stage it seems this is the answer to, well just about everything. At this early stage of the hype curve the exciting possibilities always exceed the tested deployed solutions. Reality arrives with early adopter experiences showing the real technology capabilities that match genuine business case requirements, with corresponding deployable product sets.

You don’t have too read too many articles to sense the lack of cohesion in technology views as to what the various pluses and minuses of Blockchain technology may be. Nor to realize the generality of the concepts as to the business value it brings. However these arguments can be better understood and rationalized by examining the two basic Business requirements, which are fundamentally different from each other.

Instead of launching into the usual definition and description of Blockchain, (inevitable in some way linked to Bitcoin), lets start with the basic capability requirements for the business solutions. It is for a shared Asset Register of transactions, but transformed from existing Asset Registers by Digital Business/Markets requirement for no single centralized controller to support its ‘any to any’ operating model. Event driven and optimized interactions rely on finding the right partners for any deal unconstrained by the need for pre-established relationships.

It sounds simple, but full-scale market places operating in a fully decentralized manner using, on demand any to any interactions business and technology model is a new phenomenon. However not all Digital markets have the same characteristics so the simple common requirement definition splits into two major, different requirements introducing the split between the two major technology approaches; Blockchain and Distributed Ledger Technology, known as DLT.

Two major Business requirements;

1. Fully Secure and Authenticated Transactions; usually associated with FinTech, (financial technology) and the commercial settlement of financial transactions. Here the basic mechanisms of Blockchain are a key aspect of the attraction, and the challenge is to overcome the associated limitations.
2. Mass Updates of Asset Registers; usually associated with IoT endpoints data transfers and associated micropayments. In this role there are questions as to the basic suitability of Blockchain architecture leading to the development of other techniques, including ‘Blockless’ Blockchain.

Though the differences between the two are substantial the basic task of managing and updating an Asset Base with transactions is common; as is the challenge of its distributed across a network of participants. The question is the tradeoffs between the two requirements concerning what is transacted and the manner in which every participant’s copy is maintained to be identical. The numbers of participants, the size of updates, their timing and manner of updating, the secure approach used, together with the form of cryptography are all variables to be ‘adjusted’ according to the exact business requirement.

There is one fundamental difference between Blockchain supporting FinTech and Distributed Ledger Technology supporting IoT. Participants in the former are permanently connected to the network to maintain their registers and authentication, whereas IoT devices are often only periodically connected to conserve battery and bandwidth usage. The basic Blockchain architecture requires the participants to maintain connectivity and abilities to update as a key part of its security authentication, IoT focused Distributed Ledger Technology solutions seek to overcome this.

Bitcoin illustrates some of the challenges in deploying Blockchain Technology based solutions. Bitcoin requirements suit its role as a specialized crypto currency, but with increasing popularity the limitations of transaction updates, and network/processor demands becoming obvious. The tendency for many articles to use Bitcoin’s success as the basis for Blockchain’s suitability other requirements frustrates those with detailed expertise, creating further confusion around ‘Blockchain’.

Bitcoin proves that it is possible to implement and deploy a global decentralized Asset Register and Transaction Recording solution that is automatic, autonomous, auditable, and securely authenticate by allowing all participants to understand the integrity of the process. This established starting point has created huge interest in the potential of using the mathematical principles of ‘Blocks’ as the basis of developing solutions for Business requirements.

Whatever the requirement; FinTech, or Asset Register; Blockchain or Distributed Ledger there are four common basic capabilities required in a commercially acceptable solution, and the challenge is to achieve this whilst enabling the other specialized requirements.

1. Permanent unbreakable relationship between the Asset and the mathematic Authentication; a substantial and unacceptable risk lies in the two being separate entities that can be exploited and combined separately.
2. Sophisticated Identity Management; able to support full identity authentication to the direct participant’s in individual transactions, whilst ensuring the individual transactions updating the distributed Asset Registers are totally anonymous.
3. Complex Transaction Management; capable to ensuring the form of transaction is standardized, transparent, and distributed to all Ledgers within the determined time frame.
4. Consensus based Trust model; to ensure that all participants collectively are able to verify all transactions through common comparison of their Asset Ledgers.

Examining just the most simple basic requirements for FinTech Transactions versus Mass Update Asset Registers illustrates just how different the Business solutions and resulting the technology development are;

As a generality the development of Blockchain with its secure use of ‘Block’ technology suits the primary requirements of FinTech, whilst the inherent limitations that Blockchain imposes make it less suitable for the development of Mass Update of Asset Registers solutions. (HyperLedger, one of the most popular Blockchain consortiums, has now started ‘Performance and Scalability Working Group’, PSWG, to address this topic).

Whilst a great deal has been published about the development of Blockchain based solutions, (see appendix for Constellation Research reports and blogs), very little has been said about alternatives. Whilst there are a number of existing traditional centralized approaches for Asset Register management even if they could be modified in some way they would fail at least some of the four basic principles outlined earlier.

The Trusted Internet of Things Alliance, aims to rectify the lack of attention to the need for Mass Update Registers solutions for IoT market places by building on the work of one of its founding partners IoTA. Founded by David Sonstebe, with a group of mathematicians who had worked on Blockchain, the focus is on the IoT challenge. The initial Whitepaper on its approach can be found here, but the following quotes by its founder provide a simple explanation as to the goals of the IoTA’s Tangle Ledger approach;

At heart Hyperledger is a permissioned ledger, and that’s the antithesis of IoT, which has to be open to realize its potential. IoT cannot be a closed ecosystem because that is literally the opposite of interoperability. IoTA Tangle Ledger is a Directed Acyclic Graph, as opposed to the linear Blockchain design, allowing the systems to settle transactions with zero fees and allow trading in specified resources on demand.

The recent IoTA announcement entitled ‘IoTA’s Tangle meets IOT requirements better than any Blockchain’, sums up the issues to be addressed and compares Blockchain technology with the IoTA Distributed Ledger Technology. The detail makes clear the deep differences that have to be addressed and is a must read for anyone contemplating involvement in IoT solutions. There are more issues than just the often remarked through put and scaling difficulties including the need to support periodic connect and disconnection of participating devices that appear to render current Blockchain architecture unsuitable.

Blockchain has the headlines, and in Bitcoin has convincingly demonstrated that it can meet the difficult requirements for an any to any decentralized business transaction solution. When applied to Business requirements that require the rigors of secure authenticated decentralized transaction management between known Ledger participants then Blockchain has compelling features.

But there are other types of requirements for decentralized transaction solutions which require high volume, low cost, good enough secure Transaction management, often with periodic connection. Here alternatives to Blockchain based on Distributed Ledger Technologies are emerging

Reversing the approach by defining the basic business requirements helps rationalize the frequently confusing statements being made. As an example anyone involved in the design and deployment of IoT solutions should investigate alternative developments such as IoTA Tangle.

Additional Material; Constellation Reports and Blogs

Update on HyperLedger with release of Fabric 1.0 for the use of solution developers

Report; Blockchain explained in plain English

Video; Blockchain myths and realities

Blog; Distributed Business Service Models