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Google Next - Review of GSuite News

Google Next - Review of GSuite News

Google announced several new features around Drive and Hangouts. What are they? How do they compare to the competition? Listen to find out.

On <iframe src="https://player.vimeo.com/video/207951242?badge=0&autopause=0&player_id=0" width="1152" height="720" frameborder="0" title="Google Next - Review of GSuite News" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>

Salesforce Einstein Rolls Out; IBM Watson Awaits

Salesforce Einstein Rolls Out; IBM Watson Awaits

Salesforce this week detailed progress on Einstein artificial intelligence. Less clear was how a new IBM partnership will change Salesforce AI plans. Here’s what's behind the headlines.

What’s the state of Salesforce Einstein, the portfolio of artificial intelligence (AI) capabilities announced last fall? Salesforce generated plenty of media coverage this week with two big announcements. Here’s my take on the realities of a partnership with IBM and what we have yet to understand about the packaging and pricing of Einstein.

Watson Meets Einstein?

The first announcement from Salesforce this week was the unexpected bombshell on a new partnership with IBM that headlines simplified as "Watson meets Einstein." As described by Salesforce CEO Marc Benioff in this CNBC appearance, one key benefit for Salesforce, and perhaps the first and easiest to implement, will be access to IBM cloud-accessible data from the Weather Company and other high-scale sources.

Data is a key ingredient of accurate AI, and in the wake of Microsoft’s acquisition of LinkedIN last year – a real competitive threat -- Salesforce can only benefit from significant data partnerships. Benioff cited a scenario in which weather data could be used by insurers to alert policy holders in the path of a predicted hail storm to park their cars indoors.

Benioff also noted that IBM offers cloud compute capacity and systems integration muscle. Here’s where joint IBM-Salesforce customers are most likely to benefit. IBM amped up its focus on CRM generally and Salesforce specifically last year by acquiring long-time Salesforce partner and systems integrator Bluewolf. And in yet another benefit to Salesforce, IBM committed to using the Salesforce Service Cloud internally. Given the scale of IBM’s 380,000-plus-employee workforce, that’s a significant customer win.

As for the potential combination of Watson and Einstein AI capabilities, we'll have to wait and see what the deal brings. Aside from application-integration and API-level ties expected as soon as next month (and, I suspect, already underway through Bluewolf), both companies stated that we won't see Watson-meets-Einstein synergies until the second half of this year – at the earliest.

MyPOV on the IBM Partnership: Salesforce has no lack of data science talent and capabilities, so I see IBM’s data assets and systems-integration muscle as the lure of this deal from Salesforce’s perspective. As for IBM, it’s way to grow the systems integration business while bringing Watson into the conversation with joint customers.

Einstein Generally Available

This week’s second announcement came in the form of a one-hour “Year of Einstein” videocast led by Salesforce execs including CEO Benioff and co-founder Parker Harris. Digging into the details, Chief Product Officer Alex Dayon talked about the 10 new Einstein AI features released in last month’s “Spring 2017” release. Salesforce now has more than 20 Einstein features generally available (including 16 listed in the slide below).

This slide from the Salesforce "Year of Einstein" video streamed this week lists 17 of
the 20 AI features now generally available from the CRM vendor.?

All 45 of the Einstein features planned for release in 2017 are detailed in my latest research, “Inside Salesforce Einstein Artificial Intelligence.” This 19-page report explores the foundational requirements of AI success, which include high-scale data, massive compute capacity, advanced data-science capabilities and plenty of time to work with all of the above. The report explores Salesforce capabilities on all these fronts, including the two years it spent developing the machine-learning-based predictive data pipeline that will power the vast majority of Einstein capabilities. Finally, it looks at Einstein compared to the cognitive and AI capabilities currently available or, in some cases, in development, within IBM, Microsoft, Oracle and various public cloud service providers.

In Tuesday’s video, Salesforce execs stressed that Einstein is “built into the platform” and now “available to all Salesforce customers.” But packaging and pricing varies by feature and cloud. On the most popular clouds -- Sales, Service and Marketing -- Einstein entails extra cost, and in some cases it’s available only to certain license tiers.

For example, on the Sales Cloud Einstein Opportunity Insights, Einstein Account Insights and Einstein Activity Capture are bundled together for $50 per user, per month, and they’re only available to those with Sales Cloud Enterprise or Unlimited licenses.

On the Service Cloud, Einstein Supervisor is a bundle of the pre-existing Omni-channel Supervisor and Service Wave Analytics apps with the Analytics Cloud Einstein Smart Data Discovery feature. In this case, Einstein is reserved for customers using Enterprise and Unlimited licensing levels and optional apps. Omni-channel Supervisor, for example, is included as part of Service Cloud Enterprise edition and higher. The Service Wave Analytics app is optional and starts at $75 per user per month. Analytics Cloud Einstein Smart Data Discovery, which is optional, is priced based on data volume and user counts. So Einstein Supervisor is “included” with other offerings, but they all happen to be available only to those with Enterprise-grade-plus licenses and an optional add-on application.

Marketing Cloud Einstein Journey Insights and Einstein Segmentation are available with the combination of any Marketing Cloud license and a Krux license. Pricing is based on Krux data collection volumes and storage and data processing use cases.

On some of the newer clouds that Salesforce is hoping to grow, Einstein features are included. Commerce Cloud Einstein, for example, is built into the Commerce Cloud Digital service. And in the Community Cloud, Einstein Recommendations and Einstein Trending Posts are included at no cost with any license. Other Einstein pricing is detailed in this press release.

MyPOV on the Einstein Rollout: It should be no surprise that Salesforce’s most sophisticated, in-demand and potentially labor-, time- and cost-saving capabilities are being tied to higher license levels or optional features. A key goal with Salesforce Einstein is to help people focus on what matters by getting redundant, time-consuming work out of the way or by presenting the lowest-hanging fruit, such as ripe sales leads, based on smart, predictive analysis. As I conclude in my report, the big challenge for Salesforce customers will be calculating the value of Einstein capabilities before turning those features on for lots of users.

Related Reading:
Inside Salesforce Einstein Artificial Intelligence
Oracle Preps AI Apps, Next Steps for Data Cloud
Salesforce Takes Apps-First Approach with Einstein AI

 

Media Name: Salesforce Einstein GA Features.jpg
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Event Report: #GoogleNext17 On Path To Enterprise Ready

Event Report: #GoogleNext17 On Path To Enterprise Ready

Google Cloud Takes Key Steps To Enterprise Class

Over 10,000 customers, prospects, partners, Google developers, and employees gathered in San Francisco’s Moscone West Conference Center for Google’s flagship enterprise event. Of note, Alphabet CEO, Eric Schmidt, bookended the event by highlighting the $30 billion capital infrastructure investment into the overall Google Cloud Platform.   The conference brought together Google’s ecosystem and highlighted Google’s commitment to invest in the enterprise market.  A few proof points on enterprise-ready were on hand:

VIDEO: The 60 Second LowDown On #GoogleNext17

20170308 The 60 second LowDown on #GoogleNext17 from Constellation Research on Vimeo.

  • Google showcases enterprise cred on stage. Customers such as Disney, eBay, Home Depot, HSBC, and Verizon were on hand to share how they made the move to GCP.  Verzion shared plans to move 115,000 employees to G Suite by year’s end.  HSBC’s CIO Darryl West noted how their data scientists found the tools easy to use. Disney’s CTO, SVP Michael White highlighted Google’s machine learning capabilities in their road to AI.  Home Depot’s SVP of Technology Paul Gaffney talked about how Google handled “the smoothest Black Friday ever”.  Colgate-Palmolive shared how they migrated 28,000 employees on to G-suite.

    Point of View (POV): While customers started first using the Google Cloud Platform for G Suite, big data, analytics, machine learning, translation, and big query, success has led to land and expand strategies.  Constellation sees customers and prospects moving legacy workloads in a “lift and shift” fashion.  Organizations fearing Amazon’s cannibalization of their market and those unsure of Microsoft’s ability to deliver on AI have begun pilots on GCP as well as sought choices in partners as Google beefed up their enterprise requirements.  At the leadership summit, many customers and prospects expressed significant interest in setting up POC’s.
  • SAP expands Hana distribution with Google.  SAP’s Bernd Leukert appeared on stage with Diane Greene to announce the official certification that Google Cloud Platform (GCP) technology could run the SAP HANA database and other mission critical SAP applications.  Certification is critical for customers as SAP and Google will ensure that specific performance enhancements for SAP apps and HANA are maintained.  SAP intends to have Hana Cloud Platform working on Google Cloud in the next two months.

    (POV): The partnership shows how Google seeks to attract large enterprise workloads and enterprise customers onto the platform.  The deal also addresses key privacy concerns as SAP remains the custodian of the data in the cloud allowing customers to meet data governance and compliance requirements.  Longer term, SAP must decide whether to operate its own data centers or they could rely on Google as their partner.  SAP gains a key ally in delivering much needed compute power and distribution of SAP’s Hana technologies.  SAP will also resell Google’s G-Suite into it’s 345,000 customers.
  • Google improves  support offerings.  New smart tiering engineering support plans, Rackspace partnership, and Pivotal partnership bolster support.  Three new engineering support plans were announced for Google Cloud based on response times.  Level one at four to eight hour response  was set at $100 per user per month.  Level 2 for one hour response was set at $250 per user per month, and Level 3 for one  for a 15 minute response at any hour of the day was set at $1500 per user per month.

    (POV): Constellation sees the new support plans as key to driving value for clients based on their need and usage of engineering services.  The Rackspace relationship helps customers with better managed support options.   Pivotal’s partnerships gives customers running mixed clouds better support with Customer Reliability Engineering.

The Bottom Line: Google Taking Steps In The Right Direction For Customers

Just two years ago, analysis of Google’s enterprise efforts showed very little enterprise credibility.   The sales team barely understood enterprise, the products were rife with transient talent, and customers had no input into the product direction.  With the recent house cleaning in the management and product teams, a commitment to enterprise by Eric Schimdt, and a host of new enterprise class alliances and partnerships, Google is rapidly building a worthwhile option for clients across the five entry points to cloud maturity (see Figure 1)

  1. Migrate workloads.  From test and dev, to key production workloads, organizations can start reducing data center costs and driving down the cost of compute power.
  2. Migrate enterprise.  While certain systems will remain on-premises or in a mix of compute power environments, over time, organizations will shift their enterprise systems onto the cloud.
  3. Access SaaS Apps.  While workloads and enterprises are making shifts, new capabilities in apps will come from a surround strategy.
  4. Manage hybrid cloud.  Organizations will operate multiple clouds on multiple deployment options and this hybrid environment will require governance and management.
  5. Innovate with the cloud.  While the cloud will provide many core capabilities to clients, innovation will come from application development on platforms in the cloud.

As customers use the cost savings in the cloud to fund innovation, expect Google to emerge as an option among the 5 Amigos (Amazon, Microsoft, IBM, Google, Oracle) for full stack cloud capabilities (i.e. IaaS, PaaS, DaaS, SaaS).    Customers are drawn to the machine learning, translation, maps, and analytics opportunities.

However, Google will have to make more acquisitions such as Kaggle and Apigee in order to round out key enterprise requirements.  For this reasons, customers and prospects should watch carefully what partnerships and alliances emerge in the next six to twelve months.  Google is taking steps in the right direction but must move quickly in order to keep its momentum as a worthwhile enterprise class option.

Your POV.

Looking at cloud options?  What do you think of Google Cloud Platform?  Will you rely on Google for your digital transformation efforts?

Add your comments to the blog or reach me via email: R (at) ConstellationR (dot) com or R (at) SoftwareInsider (dot) org.

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Event Report - Google Next 2017 - Google makes progress - but is it fast enough?

Event Report - Google Next 2017 - Google makes progress - but is it fast enough?

We had the opportunity to attend Google’s Google Next conference, happening in San Francisco from March 7th till 11th at Moscone West. San Francisco ‘dressed’ up in Google Next colors already way ahead of the event, it was clear that this would be a much bigger event than last year’s Google Cloud Platform event. And a difference it was, also aided by the combination of Google Cloud and GSuite, the number of analysts jumped from 20 or so to estimated 80+. No official attendee numbers, with a lot of Googlers lining up to attend, too, my estimate is well over 2000, when all are counted. 

 


So take a look at my musings on the event here: (if the video doesn’t show up, check here)

 

No time to watch – here is the 1-2 slide condensation (if the slide doesn’t show up, check here):
 
 
Want to read on? 
 
Here you go: Always tough to pick the takeaways – but here are my Top 3:
 
Google Next 2017 Holger Mueller Event Report Constellation Research SAP HANA Schmidt Greene Leukert
Schmidt shares his 3 step program for moving to the cloud

Google is serious about Enterprise – It was already clear from the hiring of Greene and last year’s event. But it’s one thing to say it and then to deliver on it. Greene shared that the division is the fastest growing in headcount with over 1000 new hires, Schmidt shared today that over time Google has invested 30B+ US$ into the cloud infrastructure. As Greene shared earlier the ‘business’ things are easy – the basic ‘blocking and tackling’ – but it still needs to be executed. So Google for the first time had a partner event with the conference and showed it has attracted interest from all the large SIs. It’s a lot of progress on the partner numbers, but a totally different ball game than with the other two key players. It was also good to have more enterprise customers on stage, talking to Greene on different carefully selected use cases – Disney for an ‘All in’, HSBC for a data warehouse decommission an move to cloud, Home Depot as a website / commerce reference and eBay as an enterprise showcase for an inhouse built next gen app – a Google Home powered eBay application. 
 
Google Next 2017 Holger Mueller Event Report Constellation Research SAP HANA Schmidt Greene Leukert
Greene talks Google Cloud


Machine Learning remains the carrot – Not surprisingly, Machine Learning remains the core attraction for Google Cloud. Disney’s CTO clearly labelled it as the reason why Disney is building apps on Google Cloud. Newly minted head of AI / Machine Learning Fei Fei Li shared the visions and unveiled (next to the Cloud Speech, Vision, Translate and Natural Language APIs) the new Video Intelligence API. No surprise given YouTube is part of Alphabet, but very powerful to index and find things in video, e.g. all the beach scenes in your vacation videos. Can’t wait for it to come to Google Photos. Or find out how many of my videos where in cars, at airports or somewhere else. But the key announcement – with long term impact – is Google’s acquisition of Kaggle, the analytics, machine learning, AI community, famous for its competitions. A key acquisition that could – if well executed – further bolster the Machine Learning / AI leadership of Google: It’s not enough to have great software capabilities, you also need to educate people about them and win their hearts and minds as a community. The strategy is clear here, now Google will have to show that it can create, foster a vendor independent ecosystem around Machine Learning. 
 
Google Next 2017 Holger Mueller Event Report Constellation Research SAP HANA Schmidt Greene Leukert
Google'e Fei Fei Li announces the Kaggle acquisition


Google gets SAP HANA – The major news in regards of ‘meeting the enterprise, where the enterprise is’ (the slogan from last year) was that SAP HANA is now certified on Google Cloud. Leukert was there to unveil the news with Greene, certainly a good move, that shows SAP’s multi vendor cloud strategy. You can / will be able to run SAP products on all three major IaaS. The SAP Hana Express developer product is available, too, with SAP Cloud platform coming later. And when Colgate came on stage, it was clear that SAP to GSuite integration is also on the roadmap. More options for SAP customers is a good development, it may make it easier for SAP to sell more HANA going forward. And Google gets load for Google Cloud. The usual ‘SaaS vendor picks IaaS’ move. The only downside: SAP is working hard to get its customers to HANA – so it is not the bulk of the current load where SAP customers are from an on premises install base. That would be SAP customers running mySAP ERP etc. – mostly on Oracle. 
 
Google Next 2017 Holger Mueller Event Report Constellation Research SAP HANA Schmidt Greene Leukert
Google's Greene and SAP's Leukert on SAP HANA coming to GCP


MyPOV

A lot of good progress from Google on the Google products for the enterprise, both Cloud and GSuite. The conference has only started – so more is going to come for both products in the days to come. The Google Enterprise team is working hard, no doubt and has made progress in the last 12 months with partners, support and create more unique offerings e.g. the site reliability engineer for customers, a start up program etc. etc.

On the concern side, it is not clear if this will be enough, I asked the Greene leadership team on what they will do to catchup from ‘Bronze to Gold’ and they all came up with good and plausible answers (check out my Storify of the analyst event here). But in a year where we may see VMware running on AWS and Oracle making its cloud work first time – this may not be enough for Google to get on premises load of scale. So it all comes back to the speed of Google being able to attract enterprise load for the next few years, and the speed of the enterprise moving to cloud.

In the meantime, when enterprises have to build new software, the Google capabilities are very attractive for the next generation application use cases the 21st century demands. So in the short run this could well mean that Google can attract more next generation application use cases than attract traditional enterprise IT loads. We will be watching, stay tuned.

Want to learn more? Checkout the Storify collection below (if it doesn’t show up – check here). And if interested in the Analyst Summit from Tuesday this week - there is a Storify collection here.




 
More about Google:
  • New Analysis – Google enables citizen developers and developers with Google App Maker - read here
  • First Take - Google enters enterprise software space with Google Jobs API - read here
  • Event Report - Google I/O 2016 - Android N soon, Google assistant sooner and VR / AR later - read here
  • First Take - Google Google I/O 2016 - Day #1 Keynote - Enterprise Takeaways - read here
  • Event Preview - Google's Google I/O 2016 - read here
  • Event Report – Google Google Cloud Platform Next – Key Offerings for (some of) the enterprise - read here
  • First Take - Google Cloud Platform - Takeaways Day #1 Keynote - read here
  • News Analysis - Google launches Cloud Dataproc - read here
  • Musings - Google re-organizes - will it be about Alpha or Alphabet Soup? Read here
  • Event Report - Google I/O - Google wants developers to first & foremost build more Android apps - read here
  • First Take - Google I/O Day #1 Keynote - it is all about Android - read here
  • News Analysis - Google does it again (lower prices for Google Cloud Platform), enterprises take notice - read here
  • News Analyse - Google I/O Takeaways Value Propositions for the enterprise - read here 
  • Google gets serious about the cloud and it is different - read here
  • A tale of two clouds - Google and HP - read here
  • Why Google acquired Talaria - efficiency matters - read here
 

Find more coverage on the Constellation Research website here and checkout my magazine on Flipboard and my YouTube channel here.
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20170308 The 60 second LowDown on #GoogleNext17

20170308 The 60 second LowDown on #GoogleNext17

Insights into Day 1 at #GoogleNext17 from Constellation Research Analyst R "Ray" Wang.

On <iframe src="https://player.vimeo.com/video/207647722?badge=0&autopause=0&player_id=0" width="1280" height="720" frameborder="0" title="20170308 The 60 second LowDown on #GoogleNext17" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>

20170308 2 Minute Low Down Oracle Cloud ERP Analyst Day

20170308 2 Minute Low Down Oracle Cloud ERP Analyst Day

Insights from Constellation Analyst R "Ray" Wang from the Oracle Cloud ERP Analyst Day held at the Ritz Carlton San Francisco on March 8th, 2017

On <iframe src="https://player.vimeo.com/video/207646850?badge=0&autopause=0&player_id=0" width="1280" height="720" frameborder="0" title="20170308 2 Minute Low Down Oracle Cloud ERP Analyst Day" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>

Digital Business Distributed Business and Technology Models Part One; Understanding the Business Operating Model

Digital Business Distributed Business and Technology Models Part One; Understanding the Business Operating Model

Any definition of a Digital Business emphasizes the requirement to be marketplace responsive with Enterprise wide dynamic agility to optimize reactions to events, and opportunities. As business buyers and consumers both become adept at finding exactly what they want mass volume product and distribution becomes configurable software Products and Services. To increase revenues Enterprise have to become equally adept in the finding, and aligning the people, knowledge and operating assets to match.

The Digital Enterprise is driven by market ‘pull’, recognizing its assets in a granular model with orchestration of its capabilities and assets to meet the demands. In many ways this is a reversal of the focus on optimizing the ‘push’ model delivering a narrower range of more standardized products efficiently through defined streamlined processes. Revenue models based on Services can have wider consequences across the Enterprise in many areas, a point clarified latter.

Enterprise management is naturally concerned that this granular, orchestrated approach de-centralizes the Enterprise and risks its carefully constructed management governance. If the same controls were maintained this would be true, but the increased visibility of assets, the use of enhanced intelligence, and the use of OpEx financial management all increase management operational efficiency. The foundation of the Digital Business is built on, and maintained by, a similar change through deploying the new Technologies together to form what could be termed a ‘Business Infrastructure’.

A recognizable current change in Go to Market Business activities introduces increasing number of Cloud based Apps; Less recognized is the impact of distributed Apps requiring both localized Enterprise Edge Clouds in addition to large scale centralized Clouds. The addition of IoT provides both hyper connectivity internally, and externally, as well as the Digitization of physical objects/events supporting interactive ‘read and respond’ Smart Services. AI is just starting to make its commercial presence felt bringing near real-time optimization of these new Enterprise operations supplementing the historic reporting role of BI reporting.

Added with other changes in working practice through the adoption of Collaboration and Social Tools, Drag and Drop composition of localized processes by Line of Business managers, etc., to see the full impact in the role of Technology in enabling Enterprise Business activities. The existing Enterprise IT infrastructure was designed to support the stability of centralized Enterprise Applications. It can be cost reduced, and made more efficient, but it’s a challenge to believe it can operate in support of such a fundamental change in both Business and Technology use.

Business Technology is becoming the term used to describe the technologies of Apps, Clouds, IoT, and AI, deployed in an integrated combination to enable Digital Enterprises. A McKinsey outline of eight ways in which Business Technology trends are radically changing the capabilities of an Enterprise also serves to demonstrate how Business Technology differs from traditional IT.  It logically follows that Business Infrastructure would be the logical term for the Infrastructure that supports Business Technology. For simplicity the term Business Infrastructure is used as broad and general reference, and for similar convenience the converged technologies of Clouds, Apps, AI, Services and (io)Things are referred to by the acronym CAAST.

The technologies of CAAST together provide the transformation in capabilities that create Digital Business.  The market place, business activities, events, and assets are all represented as Digital data that an Enterprise can read and make the optimized responses in reply.

The Business advantage lies in the Enterprise becoming part of the real World able to directly relate marketplace events to internal operations. An Enterprise business model based on product selling does not have the extended relationship requirements that a Services business model requires.  To successfully maintain a service revenue stream from the installed products requires IoT connectivity, with Cloud event processing, using a new approach to Business Infrastructure.

Consider the shift from Sales to Services against the example of a manufacturer of Air Conditioning units supplying the Building Management market, a notable early adopter of IoT based solutions.  The design and manufacture of air conditioning units continues, but the revenue stream changes from selling the ownership of units to providing the market with ‘cooling’ as a Service. This business model shift introduces not only a whole range of activities necessary to keep air conditioners at work, but also changes to existing core activities.

The consequences of the shift from a Product Sales business model to a Services business are more than is perhaps immediately obvious. Selling an Air Conditioner as a product places the design and manufacturing focus on the sales price and on marketable competitive features. Continued product ownership with revenue from low cost operation changes the design and manufacturing emphasis towards increased reliability, durability and serviceability, with initial cost and additional features becoming of less importance.

The Air Conditioning unit naturally gains inbuilt IoT sensor connectivity to manage operational deployment, and provide data for predictive service maintenance, or to report a breakdown. Additionally the Digital Enterprise will need to use the full scope of the capabilities provided by CAAST to support new Enterprise wide range of Operational activities. The reorientation towards a Services model, as an example, may introduce Digital Twin models, and drive a new effort towards flexible and Lean Manufacturing. Market led Service-provisioning calls for tailoring the units produced to match the exact conditions of deployment, rather than batch production for stock or distribution.

The organizational structure of a Digital Enterprise has to accommodate an increased number of functional activities able to operate in loose-coupled relationships driven by events. (As opposed to the tight coupled fixed relationship of a process driven Back Office Enterprise IT). The diagram below illustrates;

Those familiar with the organization of complex manufacturing will recognize the concept of ‘cells’, (used to allow different manufacturing tasks to achieve individual optimization, within a synchronized environment), but now expanded across the Digital Enterprise beyond manufacturing. The term Activity Pool is used to avoid confusion with the term Cell as defined in Industrial Automation.

Some obvious examples of major activities Pools are shown, note that this can include externalized, even shared, activity Pools such as the Building Management System, BMS, in which “cooling as a Service’ is deployed. A BMS is an integrated set of Services providing a Building with the cohesive infrastructure functions ranging from Heating, Cooling, Lighting, Plumbing, Security, etc. In a Smart Building these Services may come from several companies, but must operate 24/7 integrated as an independent Pool using localized interactions and processing. The Services providers will receive periodic historic data uploads on performance of their Services items, or event alarm triggers.

A Digital Enterprise will have deployed Services in many such external Activity Pools, as well as its own internal distinct Activity Pools. In each CAAST provides the Business Infrastructure of interactive connectivity within the Activity Pool supported by necessary local, or edge, based processing, and rules to identify event data streams to be forwarded to other Activity Pools.

Localized, or Edge processing, (sometimes called Fog Computing), reduces latency in responses, can increase security, as well as offering standalone reliability. In the Building Management example emergency situations, such as a fire, or flood, could cut external links, and are sensitive to latency in responses, would benefit from localized Cloud* processing. More common benefits are a reduction in the amount and cost of network traffic flooding across network links.

* Cloud technology should be recognized for its ability to provide ‘run anywhere on demand’ processing technology rather than thought of as being solely linked to massive data center consolidation of operations.

In the diagram below the Activity Pools are shown as Localized CAAST deployments allowing individual optimization, together with an Enterprise IT large scale Cloud, (probably from an external Cloud Service Provider). The red lines indicate the Activity Pools that would interact through an event data stream indicating Service Maintenance is required for an Air Conditioner located in the Building Control Group.

A further important addition is the use of AI to optimize the huge number of real-time events and circumstances that would be happening across the entirety of a Digital Enterprise. BI continues to provide the intelligent historic data analysis on which many of the Enterprise operating Rules will be based.

The Business and Technology models of a Digital Enterprise are effectively a single common model, deployed as a true loose-coupled Business Services architecture to provide optimization operational responses to real World events and circumstances. This is a radically different environment from Transactional IT, which has, and will continue to have, the task of providing stabile compliance in recording, maintaining and using the Enterprise Data records.

CAAST provides event driven orchestration of the Enterprise responses to the real World through the management of its Assets and capabilities. IT manages the integration of optimized processes to ensure the Enterprise tracks and maintains its compliant governance and core data.

The Business Infrastructure capable of supporting the inherent dynamic flexibility of the Digital Enterprise and its business model is crucially important as is the training and knowledge of how to assess its deployment in association with the Business model.

 

Part Two; The Technology and Business Infrastructure identifies three leading Technology vendors, outlining their vision and the capabilities each currently provides.

Cisco Converged Infrastructure a combination of Cisco Software Defined Networking and Cisco ASAP Hybrid Cloud Data Centre.

Dell Internet of Things Infrastructure citing the benefits of the merged product portfolios of Dell and EMC; whilst

HPE Composable Infrastructure aiming to support both traditional IT as well as the new demands of Business Technology.

 

New C-Suite

New Release: Latest Lists for Q1 2017 Constellation ShortList Program

New Release: Latest Lists for Q1 2017 Constellation ShortList Program

Back in October, we announced the new Constellation ShortList™ program. It offers guidance across our different coverage areas and helps buyers of technology identify the services and products they need to achieve digital transformation.

As a company, we advise early adopters using disruptive technologies on how to achieve business model transformation. Products and services named to each Constellation ShortList meet the threshold criteria as determined by our analysts through client inquiries, partner conversations, customer references, vendor selection projects, market share and internal research.

We are unveiling our new and updated lists today and will continue to provide valuable updates each quarter. Why so frequently? Most of these markets change frequently with mergers, acquisitions and other company changes. We will provide the latest updates to help you make decisions with the most up-to-date information available.  

Below are the lists we released today:

For more information, visit https://www.constellationr.com/shortlist.  

 

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CEN Member Chat: Blockchain Revealed

CEN Member Chat: Blockchain Revealed

Constellation Research VP & Principal Analyst, Steve Wilson, clarifies the myths and truths about blockchain and highlights key industries that can benefit. If you are not a Constellation Executive Network member yet, join our analysts in this private community to talk shop and solve business problems in real time. 

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A new global player emerges in Continuous Authentication

A new global player emerges in Continuous Authentication

Persistent Systems - an Indian e-business product engineering firm, serving global customers in digital business transformation, banking and healthcare - today announced a breakthrough deal with the USAA group of American financial services companies to access and productize USAA’s patent portfolio in secure authentication. The immediate outcomes of the agreement will be diverse new Risk Based Authentication (RBA) methods available across multiple channels and multiple devices. 

This development crystalises USAA’s strong commitment to the FIDO Alliance www.fidoalliance.com and leverages Persistent’s long relationship with Nok Nok Labs and other authentication specialists.

USAA’s market mainly comprises military personnel in need of banking, insurance, investments and retirement fund.  This is generally a highly mobile customer base, and certain online expectations are particularly hard to meet.  Help desk and password resets are especially challenging when defence personnel are in the field; network connectivity can’t be taken for granted, and classical “Knowledge Based Authentication” (KBA) breaks down when you are far from home and can’t access paperwork.  Some six years ago, USAA started a search for end user identity management components to deploy to its people, but were not satisfied by anything on the market.  So the company decided they had to build their own capability, and from the ground up, they researched and developed a dynamic risk based authentication platform.  This technology will now be available to Persistent’s global user population.

We will likely see Persistent emerge as a new and powerful player in the ever-evolving Identity Management marketplace, with innovative authentication options appearing as standard in Persistent’s wide range of original branded and OEMed e-business solutions.

USAA has amassed a major patent portfolio and now desires that its IP become available across the financial services sector, to its competitors, and far beyond.  USAA CSO Gary McAlum explains “we are stronger together than we are apart”.

In my view this is a ringing endorsement that security is like public health – it’s in the interests of everyone to be safe.  Really no company should compete on the basis of safety (or hygiene) for that it not the sort of world we want to live in.

Going forward, Persistent’s work in Risk Based Authentication (RBA) is guided by Five Principles:

  1. Customer access should be simple and secure, regardless of the channel they choose.
  2. Better knowledge of individuals will reduce authentication overhead when recognising customers.
  3. Authentication should adapt dynamically according to risks quantified from the customer’s context, history and behaviour.
  4. Modular ongoing risk assessments allow organisations to adjust authentication as real world environments continue to shift.
  5. Authentication technologies must be pluggable and configurable in the infrastructure, to best mitigate new threats as they unflold.

From what I’ve seen, the early fruits of Persistent’s deal with USAA will include password-less logon for multiple devices and network environments, and new continuous authentication capabilities.  From truly mobile apps through to the Internet of Things, continuous authentication will be one of the most crucial security capabilities.  

These sorts of authentication tools bring privacy benefits too. Most obviously they help cut the extraneous flow and retention of personal information entailed by KBA. More fundamentally, systems which deal in low level authentication signals help designers break the identification act down into minimal information exchanges. The focus shifts from a default interest in who someone is, to a more precise inquiry about what they are (in terms of less personally revealing attributes). 

Increasingly, devices and applications will constantly monitor what their users are doing and where they are doing it, the state of their hardware and even their surroundings, to enable automated risk-based decisions about what it is safe for them do next.  USAA’s solutions integrate different signals about how users access services, the history of access, geolocation, multi-modal biometrics, and diverse second factor mechanisms.  The focus is on the types of signals that cannot be stolen or easily spoofed (after all, in the push to get rid of passwords, we must not open up new and even more subtle vulnerabilities to identity takeover).  A key element of USAA’s IP is new scoring algorithms for weighting combinations of signals, to quantify the true state of the user, in context, in real time.

We are witnessing the slow but steady embedding of intelligent authentication into applications and personal devices.  The need for human intervention (be it by the user themselves or their supporters) will keep falling, as new digital technologies deliver the right services to the right people at the right time in the right place. 

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