Archive for the ‘Next Gen Apps’ Category

Research Report: Next Gen B2B and B2C E-Commerce Priorities Reflect Macro Level Trends

Recessionary Forces Challenge Organizations To Not Only Right Channel, But Also Personalize

Organizations with e-commerce initiatives face a flurry of competitive forces that challenge existing assumptions put in place a decade ago.  On the operational efficiency front, organizations must battle reduced product margins, shorter product life cycles, greater pricing transparency, and increased friction in multi-channel sales.  From a strategic differentiation point of view, organizations must enhance product offerings with services, improve the customer experience with loyalty top of mind, and tailor personalized experiences that support self-service options and mobility.  In addition, as customers have shifted their buying behaviors, social channels gain importance in how organizations engage their key stakeholders.

E-Commerce Evolves To Meet Next Gen Requirements

Given the landscape, organizations must adjust to less control of their business than the prior decade.  The rules have changed.  Buying behaviors have evolved.  Consequently, organizations must relearn and reengage to revive their e-commerce initiatives.  They should establish trust, not obfuscate through half-truths.  They should focus on influence, not attempt at regaining control.  Consequently, e-commerce must play a key role in the transformation of the customer’s buying experience.  In fact, next generation e-commerce initiatives must address 12 shifts such as (see Figure 1):

  1. Ownership. Governance transitions from a siloed role to part of the overall buying experience.
  2. Approach. Organizations shift from top-down messaging to bottom-up advocacy.
  3. Business requirements. Efforts focus on completing industry vertical specialization.
  4. Marketing style. Initiatives target bolstering brand trust.
  5. Channel management. E-commerce re-integrates back to the overall buying process as a significant entry point to customer lifetime value.
  6. Business process. Functional excellence grows into end to end perfect orders.
  7. Personalization. Improvements in technology enable tailored buying experiences.
  8. Business analytics. Business intelligence moves from basic reporting to real-time decision support.
  9. Social media. Non-existent programs evolve to address one of the greatest trends of the decade.
  10. Product margins. Organizations must evolve to grow profitable revenues.
  11. Product life cycle. Decreasing product life cycles require better inventory management and demand planning.
  12. Deployment options. Multiple options exist and organizations have more opportunities to experiment with try and buy SaaS alternatives.

Figure 1.  E-Commerce Evolves To Meet Next Gen Requirements


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Monday’s Musings: Why Next Gen Apps Must Improve Existing Activity Streams

Upcoming Data Deluge Threatens The Effectiveness Of Activity Streams

Activity streams, best popularized by consumer apps such as Facebook and Twitter, have emerged as the Web 2.0 visualization paradigm that addresses the massive flows of information users face (see Figure 1).  As a key element of the dynamic user experiences discussed in the 10 elements of social enterprise apps, activity streams epitomize how apps can deliver contextual and relevant information.  Unfortunately, what was seen as an elegant solution that brought people, data, applications, and information flow into a centralized real-time interface, now faces assault from the exponential growth in data and information sources.  In fact, most people can barely keep up with the information overload, let alone face the four forces of data deluge that will likely paralyze both collaboration and decision making (see Figure 2):

  1. Massive activity stream aggregation by enterprise apps. Every enterprise app seeking sexy social-ness plans one or more social networking feeds into their next release.  The mixing and mashing of personal and work related feeds will leave users confused about context and lower existing signal to noise ratios.  Yet, proliferation will continue as users seek to bring aggregated sources of information into one centralized feed.
  2. Explosive growth in the Internet of Things (IOT). Beyond just device to device communications, the web of objects, appliances, and living creatures through wired and wireless sensors, chips, and tags will drive most of the growth in the internet in the next 5 to 10 years.  With an estimated 100 billion net-enabled devices by 2020, these networks seek to discover activity patterns, predict outcomes, and monitor operational health.  The massive amounts of sensing data driven into systems will not only overwhelm users, but also handicap the performance of today’s data warehouses, analytics platforms, and applications.
  3. Flood of user generated content (UGC). User generated content continues to grow.  Facebook has over 500 million users populating pages with rich social meta data.  There are over 300 million blogs.  Wikipedia has more than 15 million articles.  Content sources will propagate at geometric rates, especially as BRIC (Brazil, Russia, India, and China) countries up their adoption.
  4. Proliferation of social meta data. Organizations seeking a marketing edge must digest, interpret, and asses large volumes of meta data from sources such as Facebook Open Graph.  Successful identification of social graphs require matching gargantuan volumes of meta data (e.g. likes, check-ins, groups, etc) through introspection across a vast array of objects.  Human centric and object centric events will inevitably coexist and engulf unified activity streams.

Figure 1.  Activity Streams Improve Collaboration And Deliver Dynamic User Experiences


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Research Report: The Upcoming Battle For The Largest Share Of The Tech Budget (Part 2) – Cloud Computing

Welcome to a part 2 of a multi-part series on The Software Insider Tech Ecosystem Model.  Part 2 describes how the cloud fits into the model.  Subsequent posts will apply the model to these leading vendors:

      The aggregation of these posts will result into a research report available for reprint rights.

      Cloud Computing Represents The “New” Delivery Model For Internet Based IT Services

      Technology veterans often observe that new mega trends emerge every decade.  The market has evolved from mainframes (1970′s); to mini computers (1980′s); to client server (1990′s); to internet based (2000′s); and now to cloud computing (2010′s).  Many of the cloud computing trends do take users back to the mainframe days of time sharing (i.e. multi-tenancy) and service bureaus (i.e cloud based BPO). What’s changed since 1970?  Quite plenty — users gain better usability, connectivity improves with the internet, storage continue to plummet, and performance increases in processing capability.

      Cloud delivery models share a stack approach similar to traditional delivery.  At the core, both deployment options share four types of properties (see Figure 1):

      1. Consumption – how users consume the apps and business processes
      2. Creation – what’s required to build apps and business processes
      3. Orchestration – how parts are integrated or pulled from an app server
      4. Infrastructure – where the core guts such as servers, storage, and networks reside

      As the über category, Cloud Computing manifests in the four distinct layers of:

      • Business Services and Software-as-a-Service (SaaS) – The traditional apps layer in the cloud includes software as a service apps, business services, and business processes on the server side.
      • Development-as-a-Service (DaaS) – Development tools take shape in the cloud as shared community tools, web based dev tools, and mashup based services.
      • Platform-as-a-Service (PaaS) – Middleware manifests in the cloud with app platforms, database, integration, and process orchestration.
      • Infrastructure-as-a-Service (IaaS) – The physical world goes virtual with servers, networks, storage, and systems management in the cloud.

      Figure 1. Traditional Delivery Compared To Cloud Delivery


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      Research Report: The Upcoming Battle For The Largest Share Of The Tech Budget (Part 1) – Overview

      Welcome to a multi-part series on The Software Insider Tech Ecosystem Model.  Subsequent posts will apply the model to these leading vendors:

      • Overview
      • Cloud Computing
      • Cisco
      • Dell
      • HP
      • IBM
      • Microsoft
      • Oracle
      • Salesforce.com
      • SAP

      The aggregation of these posts will result into a research report available for reprint rights.

      Business Models Converge During Recessions

      Is your technology provider a hardware vendor or a software vendor? Does your System Integrator now provide solutions in the cloud? These questions will continue as models converge.  Hardware, software, and system integration vendors must reinvent new models of revenue.  The economic recession has forced business model shifts at the major technology companies.  The goal – own the largest share of both the business and IT technology budget,  As these sellers attack new profit pools, buyers can expect continued convergence of business models because:

      • Hardware companies seek higher margins. Most hardware vendors face single digit margins in their core business.  To bolster margins, many vendors acquired system integration firms.  For example, HP purchased EDS and Dell acquired Perot Systems.  The next logical step requires the hardware vendors to get into software.  Software margins hover from 10% to 50% depending on the market.  Expect a hardware vendor such as Cisco, Dell, or HP to acquire a SaaS based company to move into the software business.
      • Service providers build differentiated intellectual property (IP) using the Cloud. Service providers should go on the SaaS/Cloud offensive if they want to deliver rapid innovation to customers and break the cycle of dependence on packaged apps vendors.  Service providers can take market share through SaaS by investing in white spaces in the solution road map with verticals and other pivot points that have not been well served.  In addition, expect forms of SaaS BPO to emerge as clients seek best of breed SaaS and hybrid deployments.
      • Software companies use Cloud to transform into information brokers. SaaS and Cloud deployments provide companies with hidden value and software companies with new revenues streams.  Data will become more valuable than the software in the Cloud.  Three areas of growth will include benchmarking, trending, and prediction.
      • Companies by-pass software vendors for competitive advantage. Roper Industries acquisition of iTrade Networks on July 26th, proves a key point.  Smart and innovative companies will put custom development in the cloud to meet last-mile solution needs that packaged apps vendors or system integrators fail to deliver.  Companies may also acquire software vendors if they can’t build the solution.

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      Thursday’s Disruptive Tech Showcase: RainStor Tackles The Tough Challenges Of Information Preservation

      Organizations Facing The Big Data Problem Must Solve The TCO Of Data Retention

      The explosion in data volumes from terabytes to petabytes (i.e. 1 quadrillion bytes) drives many organizations to identify cost effective solutions for the retention and on demand retrieval of historical data.  More importantly, organizations must meet a plethora of changing business and compliance requirements.  RainStor’s solution focuses in on the retention of read-only or inactive structured data.  The solution delivers the “Three R’s” of fundamental data management capabilities for its customers by:

      • Reduction. Effective storage requires secure but accessible data reduction that can encapsulate data without loss in content or structure.  RainStor can take structured data sources such as log files, database, and event data and compress to a 40:1 ratio into containers of discrete files.  This means up to a 97% savings in storage costs.  On top of the compression, RainStor de-duplicates data values and detects patterns so values only need to be stored once.  This means information is stored in a tree structure while still maintaining a full representation of the original records.  The result – in repetitive transactions such as call data logs and stock transactions, storage costs drop by geometric proportions (see Figure 1).
      • Retention. Compliance rules create unnecessary complexity in managing retention and purge parameters.  Data in the RainStor solution follows existing policies and remains “as-is” or immutable.  The system preserves the original structure of the stored records.  Users gain control in managing compliance rules and can even store the data in an unstructured data solution such as EMC Centera.  The solution utilizes commodity storage systems and doesn’t require specialized DBA skills.  Organizations can keep their SAN, NAS, DAS, CAS, or even go with cloud storage options.
      • Retrieval. Existing systems remain challenged in preserving schema evolution and often lose context after upgrades from release to release.  In RainStor, the system stores schema and tables to be able to search back in a point in time.  By addressing schema evolution, any changes to new fields, tables, and columns are preserved and present the exact representation of the data regardless of query style.  As an extension repository, RainStor does not store in relational format and can instead point to a SQL statement.  Furthermore, organizations can retrieve data through SQL and BI tools such as ODBC/JDBC at RDBMS performance levels or better

      Figure 1.  RainStor Applies Data De-duplication To Reduce Storage Costs

      Source: RainStor

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      Research Report: Rethink Your Next Generation Business Intelligence Strategy

      BI Solutions Must Address The Information Management Matrix

      A confluence of changing business requirements and on-going vendor consolidation leads many organizations to rethink their business intelligence (BI) strategies.  Many buyers face decisions to move beyond departmental solutions or to stay with an integrated apps based BI solution.  Meanwhile, some buyers must decide whether or not an integrated platform provides the right balance between business impact and cost of technology.  Additionally, most organizations seek support for new data types and new deployment options.  As BI continues to evolve from fragmented and historical reporting to pervasive, predictive, and real-time decision support, an organization’s success increasingly depends on the support for a expanding information matrix of (see Figure 1):

      • New and traditional data types. A proliferation of data types from social, machine to machine, and mobile sources add new data types to traditional transactional data.  Examples include content, geo-spatial, hardware data points, location based, machine data, metrics, mobile, physical data points, process, RFID’s, search, sentiment, streaming data, social, text, and web.
      • Visualization and reporting paradigms.  Users expect more than the traditional charts, gauges, and dials.  Web 2.0 innovations show how Rich Internet Applications (RIA) through tools such as AJAX, Adobe Flash and Microsoft Silverlight can create interactive BI experiences.  New and old paradigms include ad-hoc query builders, business performance management (BPM) systems, dashboards, production reports, scorecards, and advanced visualizations.  New visualization types include matrix charts, network diagrams, bubble charts, tree maps, word trees, tag clouds, phrase nets, and others.
      • Approaches and styles. Analytical techniques continue to improve as data volumes explode.  New and traditional approaches include advanced analytics, business activity monitoring (BAM), BI workspace, decision support systems, low latency BI, meta data generated BI apps, non-modeled exploration and in-memory analytics, scenario analysis, and OLAP.
      • Deployment options. With data coming from so many different sources, users are seeking new deployment options.  Common solutions in the BI portfolio include BI appliances, BI in the Cloud, BI specific DBMS, Mobile BI, open source BI, on-premises packaged BI apps, private BI clouds, and SaaS based BI.

      Figure 1.  The Information Management Matrix Drives Next Gen BI


      Explosion In Semi-Structured And Unstructured Data Challenges Existing Solutions

      Along with new business requirements, the old world of structured data must make way for a plethora of new data types in unstructured data.  More importantly, solutions must support a growing number of industry vertical standards in semi-structured data.  Unfortunately, no single vendor can support all the data types that fit into the following three categories (see Figure 2):

      • Structured data. Structured data remains the most understood type of data.  Traditional sources comprise of data in transactional systems such as ERP, CRM, SCM and other database management systems.  Solutions conduct analysis via OLAP and traditional apps centric and database centric BI systems.
      • Semi-structured data. Common examples include flat files in record format, RSS feeds, XML documents, and data in spreadsheets.  Industry-specific XML data standards and cross-enterprise data-exchange standards such as ACORD, EDI, HL7, NACHA, and SWIFT will continue to grow as BI goes vertical.  On the document print stream front, new systems should support ASP, Met code, and PCL.
      • Unstructured data. Sources include natural-language text from e-mail, blogs, SMS, social networking sites, text fields, audio, video, and images.  Unstructured data represents up to 80% of today’s data sources.  Enterprises are challenged in discovering and organizing unstructured data for the real-time delivery of information to the right user.

      Figure 2.  Data Types Fall Into Three Main Categories


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      News Analysis: SAP Bets On Innovation With $5.8B Sybase Acquisition

      Move Signal Seriousness To Acquire Key Innovation Driven Technologies

      SAP announces a $5.8B acquisition of Emeryville, CA, based Sybase.  The acquired entity will remain a stand alone company.  At first customers, prospects, and casual observers will wonder why SAP has agreed to acquire what is perceived as an aging, legacy database company.  However, industry watchers will realize the fit in technology innovation for three main reasons:

      • Sybase is a leader in mobile platforms.  Over the past decade, Sybase has transformed its company to succeed and lead in the mobile space and has extended its BI and analytics capabilities.  Sybase delivers the complete value chain in managing, analyzing, and mobilizing information.  A key solution is Sybase’s Uwired Platform, which provides a mobile development platform, supports heterogeneous deployments on most devices and operating systems, extends back end data, and ensures security and mobility management.  Sybase also brings strong capabilities with real time decision support, predictive analytics, dynamic reporting, and high performance BI.

        Point of View (POV):
        SAP and Sybase already cemented their partnership at CeBIT.  Enabling SAP CRM to work on mobile devices with ease, put some life back in the staid SAP CRM product.  The ability to deliver the same capabilities in the rest of the Business Suite will help SAP achieve a key part of its innovation strategy in mobile.  On the analytics and BI front, SAP will need to provide a clear road map on how the analytics integration will work with the BOBJ teams and NetWeaver architecture.  Customers will want a road map on 90 day, 180 day, and 1 year integration milestones.
      • Massive data volumes require in-memory databases for rapid accessSybase brings a high performance in-memory database (IMDB) to the table. The proliferation of information, devices, and delivery platforms require reduced response times.  Sybase delivers an integrated approach to IMDB.  The offering shares the same SQL language, drivers, and admin tools.  The result – limited code changes, reduced bugs, and quicker time to market.

        Point of View (POV):
        IMDBs represent a key component in both future on-premise based applications and SaaS/Cloud based applications.  While SAP had an offering called Max DB, the product did not appeal to financial services and insurance customers who remained skeptical on its application in massive workloads.  However, Sybase has proven itself with its IMDB offerings and financial services pedigree.  Another key reason for moving to IMDB – SAP resells an estimated $1B of Oracle Database every year. (Clarification 5/14/2010:  The SAP install base buys $1B in Oracle databases every year.)  Any effort to stop funding SAP’s largest competitor is a proactive and perfect reason to move to IMDB.
      • Cloud technologies bring SAP into the future. Sybase has built a strong relationship with Amazon’s Elastic Compute Cloud (EC2), storage, and  virtualization vendors required to support cloud technologies.  Sybase products for mission critical data management, embedded and mobile database, column based analytics, and data movement and synchronization already work in the Cloud.

        POV:
        SAP can take advantage of the advances made from the Sybase team to support both private and public cloud environments.  The private cloud capabilities deliver a must have requirement to meet strict European privacy laws and mitigate concerns of public sector customers.  Sybase is unique in being able to provide the same database management technologies in both the private and public cloud.

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