Instrumenting Your Enterprise for Maximum Predictive Power

By James Kobielus

Business is all about placing bets and knowing if the odds are in your favor.

As I noted in my most recent Forrester report, business success depends on your company being able to visualize likely futures and take appropriate actions as soon as possible. You must be able to predict future scenarios well enough to prepare plans and deploy resources so that you can seize opportunities, neutralize threats, and mitigate risks.

Clearly, predictive analytics can play a pivotal role in the day-to-day operation of your business. It can help you focus strategy and continually tweak plans based on actual performance and likely future scenarios. And, as I noted in a recent Forrester blog post, the technology can sit at the core of your service-oriented architecture (SOA) strategy as you embed predictive logic deeply into data warehouses, business process management platforms, complex event processing streams, and operational applications.

The grand promise of predictive analytics—still largely unrealized in most companies—is that it will become ubiquitous, guiding all decisions, transactions, and applications. For the technology to rise to that challenge, organizations must move toward a comprehensive advanced analytics strategy that integrates data mining, content analytics, and in-database analytics. Already, we’ve sketched out a vision of “Service-Oriented Analytics,” under which you break down silos among data mining and content analytics initiatives and leverage these pooled resources across all business processes.

You may agree that this is the right vision but have doubt about whether there is a practical, incremental roadmap for taking your company in that direction.  In fact there is, and it starts with re-assessing the core of most companies’ predictive analytics capability: your data mining tools. As you plan your predictive analytics initiatives, you should avoid the traditional approach of focusing on tactical, bottom-up project-specific requirements. You should also try not to shoehorn your requirements into the limited feature set of whatever modeling tool you currently happen to use.

To become a fully predictive enterprise, you will need to take both a top-down and bottom-up approach to your data mining initiatives. From the top-down, it’s all about building and integrating alternate models of how your business environment is likely to evolve internally and externally. In our recent report on advanced analytics, Boris Evelson, Leslie Owens, and I sketched out the many business processes that can be enriched by predictive analytics.

So how do you instrument your company to become more predictive? For starters, assess whether your analytics tools support the following capabilities for developing, validating, and deploying predictive models:

• Model multiple business scenarios: You should be able to build complex models of multiple, linked business scenarios across different business, process, and subject-area domains, using such key features as strategy maps, ensemble modeling , and champion-challenger modeling.
• Incorporate multiple information types into models: You should be able to develop models against multiple information types, including unstructured content and real-time event streams, while leveraging state-of-the-art algorithm in sentiment analysis and social network analysis.
• Leverage multiple statistical algorithms and approaches in models: You should be able to develop models using the widest, most sophisticated range of statistical and mathematical algorithms and approaches, including regression, constraint-based optimization, neural networks, genetic algorithms, and support vector machines.
• Apply multiple metrics of model quality and fitness: You should be able to score and validate model quality using multiple metrics and approaches, including quality scores, lift charts, goodness-of-fit charts, comparative model evaluation, and auto best-model selection.
• Employ multiple variable discovery and assessment approaches: You should be able to build and validate models using various approaches for variable discovery, profiling, and selection, including decision trees, feature selection, clustering, association rules, affinity analysis, and outlier analysis.

How is this different from predictive analytics as usual? Traditionally, most predictive modeling specialists focus on the latter three capabilities: statistical algorithms and approaches, model quality and fitness, and variable discovery assessment. Most models are built in narrowly scoped business or subject domains—such as customer analytics for marketing campaign management—and only against structured data sources (such as relational tables). Traditionally, few predictive analytics projects have entailed modeling of multiple business scenarios across diverse domains--such as sales, marketing, customer service, manufacturing, and supply chain-- though in the real world these business processes are often quite interconnected. Also, many data mining initiatives fail to incorporate information from unstructured sources—such as text in call-center logs—though this content may be as important as what comes relational databases and other structured sources.

It’s very important to build multi-scenario predictive models against complex information sets, but becoming a fully predictive enterprise demands much more. To instrument your organization for maximum predictive power, you should also tool your advanced analytics to support the following capabilities:

·         DW-integrated data preparation: To speed up and standardize the most time-consuming predictive modeling project tasks, you should be able to leverage your existing data warehouse, extract transform load, data quality, and metadata tools to support a full range of data preparation features. These features include the ability to discover, acquire, capture, profile, sample, collect, collate, aggregate, deduplicate, transform, correct, augment, and load analytical data sets.

·         Deep application and middleware integration: To deliver models deeply into whatever heterogeneous SOA-enabled platform you happen to use, your predictive analytics tool should deploy on and/or integrate with a wide range of enterprise applications, middleware, operating platforms, and hardware substrate. You should be able to deploy models seamlessly into your data warehouse, business intelligence, online analytical processing, data integration, complex event processing, data quality, master data management, and business process management environments. And to play well in your SOA, your predictive modeling tools should support application programming interfaces, languages, tools, and approaches such as Web services, Java, C++, and Visual Studio, as well as emerging languages such as SQL-MapReduce and R.

·         Consistent cross-domain model governance: To avoid fostering an unmanageable glut of myriad models, your predictive analytics solution should support a wide range of tools, features, and interfaces to support life-cycle governance of models created in diverse tools. At the very least, your tools should enable model check in/check-out, change tracking, version control, and collaborative development and validation of models. To realize this promise, it should support a full range of tools, standards, and interfaces for import and embedding of models from other tools, as well as export and sharing of models to other environments.

·         Flexible model deployment: To execute modeling functions--such as data preparation, regression, and scoring—on the widest range of data warehouses and other platforms, your tools should support in-database or embedded analytics. And to scale to the max, your predictive analytics tools should deploy models to massively parallel data warehouses, software-as-a-service environments, and cloud computing fabrics.  Your advanced analytics tools should also support development of application logic in open frameworks—such as MapReduce and Hadoop—to enable convergence of data mining and content analytics in the cloud.

·         Rich interactive visualization: To deliver their precious payload—actionable intelligence—your advanced analytics tools should support interactive visualization of models, data, and results. Ideally, you should be able to visualize all of this in your preferred business intelligence tool, or in the predictive modeling vendor’s integrated visualization layer. Of course, you have every right to expect the full range of visualization techniques--histograms, box plots, heat maps, etc.—regardless of who provides the visualization layer.

As you can see, this goes well beyond data mining as usual. Forrester has a slightly different perspective on the development of the predictive analytics market than you’re likely to get from other sources. We see a robust, flexible, SOA-enabled data mining tools as the centerpiece of advanced analytics for fully predictive enterprises. The competitive stakes are too great for businesses to take the traditional silo-mired approach when implementing this mission-critical technology.

What do you think?

Informatica Evangelizes Its Increased Business Relevance With Latest Release

By Rob Karel

Last week Informatica announced the release of Informatica 9, its data integration/data management platform that continues to evolve its flagship PowerCenter and PowerExchange data integration and access technologies into a much more comprehensive data management platform going well beyond the scope of traditional, batch-oriented ETL that remains Informatica’s bread and butter.  

The three main themes Informatica has pitched for this release include:
- Pervasive Data Quality
- Business-IT Collaboration
- SOA-based Data Services

While these themes and capabilities - reusability, SOA-compatibility, real-time, business engagement - are not necessarily new to the broader data integration or data quality software markets, few organizations have been effectively able to execute on them.   For the purposes of this blog post, I’d like to focus a bit more on the DQ and business/IT collaboration parts of the announcement.

With pervasive data quality, Informatica wants its customers to extend the use of data quality software well beyond the limits of data warehousing.   Informatica 9 provides role-specific tools that can be leveraged by both the IT and business stakeholders involved in defining, analyzing, testing, and implementing data quality logic.   Informatica has also included advanced postal address verification and global matching from its acquisitions of AddressDoctor and Identity Systems, respectively.   

I’m a huge fan of Informatica’s goal of centralizing the definition and management of data quality rules that can then be delivered as real-time data services to any part of the enterprise.  But as I discussed in my “It’s Time To Invest In Upstream Data Quality” research last year and most recently with Forrester BPM analyst Clay Richardson in “Warning: Don’t Assume Your Business Processes Use Master Data”, the biggest inhibitor to enabling this is not technical.  Business process owners responsible for the capture and update of critical enterprise information are too often more concerned with process efficiency than data quality issues that may impact downstream processes. 

Similarly, I think Informatica is on the right track with its Business-IT Collaboration theme, but has a lot more work to do from evolving this from vision to reality.   Informatica 9 provides some useful business-oriented capabilities including browser-based tools designed for business analysts and data stewards to participate more actively in the data profiling and DQ rule definition phase of a data quality initiative.   And from a collaboration standpoint, the shared metadata environment ensures both business and IT have access to the same information, and the ability to bookmark and share views of analysis and business rule output, along with comments, is a great feature that eliminates the old method of exporting results to a spreadsheet and attaching to an email.   My primary concern is that Informatica has not yet created a pre-packaged interactive collaborative environment.  For example, there are no predefined approval, escalation, and validation workflows.  

Interestingly, almost every major data quality and master data management vendor I speak with is investing quite heavily in what some are trying to define as the Data Governance Technology market. Or in other words, tools used to support both business and IT stewards in the data governance process.   Of course data governance is not a technology market, it is a business responsibility that must manage the people, process and organizational challenges required to get business value from data assets.   But there are enabling technologies that can support data stewards from both the business and IT side during certain steps of the data governance lifecycle, and the jury is still out on what approach to this technology will be the most effective. 

But the biggest challenge for enterprises trying to embrace data governance has nothing to do with the tools.  It’s getting the business to participate in the first place!   In a recent Forrester survey asking MDM and DQ professionals to rate their organization’s current level of data governance maturity, 79% said they did not have a data governance organization that included active participation from all the necessary business stakeholders. Unfortunately, there is very little that a software vendor can do to change this culture, so I’m not expecting widespread adoption from the business of Informatica’s or anyone else’s data governance tooling until that maturity improves.

Podcast: The Top 19 Customer Management Technologies To Watch

Our latest featured podcast is Bill Band's "The Top 19 Customer Management Technologies To Watch".

In this podcast, BP&A Vice President and Principal Analyst Bill Band describes what technologies comprise the customer management applications ecosystem, and which ones offer the most value based on Forrester’s most recent research.

We look forward to your questions and comments.

---

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What Makes BI SaaS Architecture Multitenant?

By Boris Evelson

I'd like to drill into some more details on my BI SaaS blog from September 2009. A key critical point to "what differentiates one BI SaaS vendor from another" discussion is what really constitutes multi-tenant architecture. Here are some initiall thoughts to stimulate the discussion:

• DBMS. There's got to be back end, DBMS architecture that allows for one of the following:
• • Automatically generate a separate DBMS instance for each client  
  • Use same DBMS instance for multiple clients, but automatically generate a set of unique tables for each client  
  • Use same DBMS instance and tables for multiple clients, but automatically assign unique keys to to each client so that they can only update and retrieve their own rows  
• Application. Similar functionality has to exist in the application tier:
• • Automatically connect to the appropriate, client specific DBMS instance, or 
  • Automatically use views that only point to client specific tables, or
  • Append "where" clause to each SQL statement to only retrieve client specific rows  
• Provisioning. All of the above functionality has to be automatically executed at a push of a button, a swipe of a credit card, with zero involvement from vendor support staff or internal IT organization.

I believe that these features truly differentiate self service BI SaaS from hosting, virtualization, private clouds, etc, that some vendors are also trying to position as BI SaaS. All these other services and architectures are important, relevant and applicable to multiple situations and requirements, but they are not BI SaaS IMHO. I'd love to hear everyone's thoughts on what else is relevant here.

How To Differentiate Advanced Data Visualisation Solutions

By Boris Evelson

I get many inquiries from clients on how to select a data visualization vendor / solution. The criteria that my clients often site are

• Thick and thin client
• Dynamic visualizations, not just static charts 
• Ability to pull data from multiple sources
• OLAP-like functionality

All these criteria are pretty much a commodity these days. The real differentiation will come once you start looking at advanced (key word "advanced") visualization features such as

• If it’s a thin client does it have Web2.0 RIA (Rich Internet Application) functionality (Flash, Flex, Silverlight, etc)?
• In additon to standard bar, column, line, pie charts,etc how many other chart types does the vendor offer? Some advanced examples include heat maps, bubble charts, funnel graphs, histograms, pareto chats, spider / radar diagrams, financial market specific charts (candlesticks, etc), project management specific charts (gantt, etc), scatter plots, relationship diagrams, overlapping sets, cluster analysis, and others?
• Can the data be visualized via gadgets/widgets like temperature gauges, clocks, meters, street lights, etc?
• Can you mash up your data with geospatial data and perform analysis based on visualisation of maps, routes, architectural layouts, etc?
• Can you have multiple dynamically linked visualization panels? It’s close to impossible to analyze more than 3 dimensions (xyz) on a single panel. So when you need to analyze >3 dimensions you need multiple panels, each with 1-3 dimensions, all dynamically linked so that you can see how changing one affects another
• Animations. Clicking through 100s of time periods to perform time series analysis may be impractical. So can you animate/automate that time period journey / analysis?
• Multi dimensional charts. Can you have a 3rd, 4th, 5th, etc dimensions, such as a size of a bubble, color of a buble on an XY axis?
• Subsets ands supersets. Can you select a point, rectangle, or a "lasso" (irregular region) and drill down into the subset or roll up into a superset (if selecting across several charts)?
• Can you have microcharts (aka trellis or sparklines) – a two dimensional chart embedded in each row or cell on a grid?
• Can you do contextual or gestural (not instrumented, not pushing buttons, or clicking on tabs) manipulation of visualization objects, as in video games or iPhone like interface?
• Is the data that is being analyzed
  a) Pulled on demand from source applications?
  b) Stored in an intermediary DBMS
  c) Stored in memory? This last one has a distinct advantage of being much more flexible. For example, you can instantaneously reuse element as a fact or a dimension, or you can build aggregates or hierarchies on the fly.
• Is there a BAM-like operational monitoring functionality where data can be fed in into the visualization in real time?
• In addition to historical analysis, does visualization incorporate predictive analytics components?
• Portal integration. If you have to deliver these visualizations via a portal (SharePoint, etc) do these tools have out of the box portal integration or do you need to customize.
• Can you reuse metadata, such as KPIs, KPMs, that was already setup in your BI or ETL or DW models?

What did I miss?

Next Gen BI Is Here Today

By Boris Evelson

As I promised in my last year “BI Crystal Ball” blog, BI will look very different in the near future. Indeed most of the 20 next generation BI trends that I list in this blog are actually here today! And, as my colleague Alex Cullen wrote in his recent research document on 15 Technologies That Matter(where of course BI is front and center), these are the technologies that indeed matter. I picked these 20 trends not because the market labels them as trendy, but because I have tons of evidence that the buy side of the BI market can use these technologies today. These technologies can address the real pain points, gaps and challenges that most knowledge workers are faced with today.

 

So what has really changed? The “what-has-to-be-done” of BI has not changed, and will probably not change in the foreseeable future. One would still need to discover, ingest, persist, measure, analyze, report, deliver and act on information. The real trick is “how-it-will-be-done”. I categorize all major next gen BI trends under 4 categories: Automation, Unification, Pervasiveness and No Borders / No Limitations. Here’s my take on what they are:

 

Automation

• Automated Information Discovery. Automatically discover source data based on metadata, content and rules.
• Actionable and Collaborative. Automate actions on results gleaned from BI reports and analysis.
• Contextual (process, desktop, visual). 1) Process: BI is aware of process context; 2) Desktop: BI is aware of desktop (open documents, open emails) context; 3) Visual: gestural, not instrumented visualization manipulation (akin to video games).
• Built-in expertise. Sensing what the user is doing and providing proactive hints.
• End-to-end lifecycle management. Automatically changing and updating all interdependent BI components.
• Decision Management. Automatically documenting and automating all business decisions.
• Self learning and adaptive. Automatically modifying data model based on reporting and analysis usage.

Unification

 

• Logically unified sources. Logical views independent of physical data location and model
• Data and content. Seamless integration of structured data and unstructured content
• Disk and streaming. Seamless integration of data stored in disk based DBMS (historical, batch) and in streaming, in memory DBMS (real time)
• Historical, current and predictive.Seamless integration of historical, current, and predictive reporting and analysis
• Metadata. Unified ETL, data quality, BI, portal, content, process, rules metadata

Pervasiveness

•  Within processes.BI in processes, automatically comes up when a decision needs to be made by a human
• Within Information Workspace. Integration with all IW components: search, ECM, email
• Self Service.Casual user and power user self service, including, but not limited to BI SaaS.
• Offline, disconnected. Seamless operation in offline / disconnected mode
• Mobile. Delivery and analysis on mobile devices

No borders

 

• On-demand data models.Reporting and analysis without limitations of underlying data models, aka “post discovery”
• Unlimited dimensionality. Ability to visually analyze many dimensions at the same time
• Exploration + analysis.Seamless integration of search-like technology to find the data and BI-like technology to report and analyze the results of the search

Drop me a note if you’d like more details on each of these trends, including top vendors that even today have capabilities in these areas.

Ten Strong Hints Your Enterprise May Not Have A BI Strategy

By Boris Evelson

You know that you don't have an enterprise BI strategy if:

1. Your end users keep pointing to IT as the source of most BI problems
2. Your business executives view BI as another cost center
3. IT staff keep asking end users for report requirements
4. Your BI is supported by IT help desk
5. You can’t tell the difference between BI and Performance Management
6. You can’t measure your BI usage
7. You can’t measure your BI ROI
8. You think your BI strategy is the same as your DW strategy
9. You don’t have a plan to develop, hire, retain and grow BI staff
10. (My personal favorite) You actually don’t know if your enterprise has a BI strategy!

Want more hints and best practices? Take our BI maturity self assessment test. Then if you actually want to compare your BI strategy and BI maturity against other Forrester clients, take our BI maturity survey. Good luck!

BPM Promises "Simplicity" In 2010. Is This "Hope We Can Believe In" Or Still A Pipe Dream?

By Clay Richardson

Time flies when you're having fun - and 2009 was a really fun and successful year for the BPM industry.  Nearly all BPM vendors reported double digit revenue growth over the first three quarters of 2009 and many are already reporting strong pipeline growth for 2010.  Most importantly, some BPM practitioners are beginning to reign in the bloat and complexity traditionally associated with BPM implementations.  

 

Over the past few months I've been on a bit of a world tour - numerous BPM industry and vendor conferences mixed in with customer meetings - listening to customers discuss their BPM hopes and challenges and listening to vendors outline their roadmaps and plans for 2010.  If I translated all of my conversations over the past few months into a tag cloud, "Simplicity" would jump out as the most prominent term mentioned on both sides.  

 

BPM customers and prospects are clamoring for the simplicity of Web 2.0 functionality for their BPM initiatives - and some are actively requesting enhanced collaboration capabilities offered by social technologies. In a previous blog post I highlighted the convergence of BPM, Web 2.0, and social - commonly referred to as "Social BPM". In a recently published report, fellow Forrester analyst Alex Cullen, highlighted Social BPM as one of the Top 15 Technology Trends to watch for enterprise architects and business process professionals.

 

Specifically, in preparing for 2010 enterprise architects and business process pro's should evaluate four key Social BPM components that help simplify and streamline BPM initiatives:

• Process Mashups - Lightweight BPM tools that support rapidly building and deploying structured and unstructured business processes. Process mashup platforms include only bare-bones functionality provided by BPM suites: execution engine, process modeling, Web-based forms, worklists, and administrative functions. Tech-savvy business analysts are using these mashup platforms to quickly deliver process solutions that IT doesn't have the bandwidth to tackle.
• Process Wikis - Process wikis allow distributed teams to easily build and maintain institutional knowledge about a particular business process or collection of business processes. Process wikis provide simple Web-based modeling and documentation capabilities that encourage input and collaboration across all roles that participate in process discovery: end users, process analysts, stakeholders, developers, and architects.
• BPM-as-a-Service- Web-based BPM platforms and solutions that allow users to model, develop, and/or execute business processes in public or private cloud environments. Companies are using BPM-as-a-Service platforms as a cost-effective "try-before-you-buy" approach to BPM.
• Process Personas - In 2010, this will be a key area to watch for BPM.  Leading vendors such as Global360 are simplifying the user experience by providing pre-built templates that provide identified process roles (e.g., supervisor, line manager, etc.) with just the features and functionality they need - no more, no less.

Ultimately, the Social BPM trend and the push towards BPM simplicity are connected to a broader trend towards "simplicity" in society.  To illustrate this, a few weeks back I was driving in my car listening to an NPR segment outlining food trends to watch in 2010.  The host highlighted the movement towards "simple foods" as a major trend that would gain greater momentum in 2010.  The basic premise behind "simple foods" is that there should be as few ingredients as possible in the foods we eat.  After listening to the segment, I thought "Hmmm, that's novel..." but didn't think much else of it.

 

Then a few days later, I tuned in to a Fox News (hey, they do have some news) segment on the excessive amounts of sugar in kids cereals.  I was amazed to learn that all of the cereals in our pantry made Fox's top 3 list of cereals with the most sugar.  To my daughter's disappointment, my wife and I immediately cleaned out the cupboard of these oversweetened cereals and marched off to Whole Foods to buy the "Envirokids Amazon Frosted Flakes" recommended in the Fox segment.  

 

While it was interesting to see that the Envirokids cereal only had half the sugar of the other cereals, what really blew my mind was that Envirokids only had 3 ingredients listed on the side of the box:  corn meal, evaportated cane juice, sea salt.  And according to my daughter (and online reviewers) it tasted pretty decent  - although I also tried a bowl and thought to myself "I already miss my Honey O's..."

 

Why It Matters?

 

Ultimately, society (as illustrated in the case of "simple foods") is demanding greater transparency and control over the makeup of what we buy, bring into our homes, and put into our bodies.  This is the same force driving the Social BPM trend - business users want greater control over assembling, updating, and communicating their business processes, with minimal support from IT.  And many vendors are beginning to heed the call.  

 

Last week at Appian Forum (Appian's annual user conference), I listened in as Appian's CEO, Matt Caulkins outlined the future direction of the company's flagship BPM offering:  I believe Matt used the term "simple" at least two dozen times in his presentation.  And other vendors such as Global360 and Software AG are also investing heavily to make BPM "simpler."

Through the years, BPM's promise of "ease-of-use" and "business empowerment" rang hollow and left business users cold and disappointed.  In 2010 the BPM industry will begin to deliver on this promise by providing concrete methodologies, capabilities, and tools that simplify all aspects of continual process improvement - and Web 2.0 and social will form the foundation of this move towards simplicity in the BPM industry. 

Enterprise architects and process professionals planning for 2010 should add Social BPM to their list of emerging methodologies and tools that will have a significant impact on the enterprise's ability to deliver value and minimize waste.

 

What's Your Take?

 

I want to hear from you.  Let me know if you think the BPM industry will finally deliver on it's promise of "simplicity" in 2010 or whether this is just a pipe dream?   If you're an enterprise architect or a process professional, let me know if you're beginning to explore leveraging some of the Social BPM capabilities highlighted in this post. I'm also interested in hearing your thoughts on the "simple foods" (and the larger societal) trend towards "simplicity".  Post your thoughts in the comments section or feel free to shoot me a quick e-mail at crichardson@forrester.com.

PeopleSoft Seeks A New Place In The CRM Sun With Release 9.1

By William Band

Since the acquisition of PeopleSoft by Oracle in 2004, the PeopleSoft CRM solution seemed to go underground. Relatively little has been heard about the product since that time. However, Oracle has been continuing to invest. PeopleSoft CRM 9.0, a major step forward, was released in August 2006, and the company will soon announce PeopleSoft CRM 9.1.

My take on Oracle's PeopleSoft CRM in the past has been that the product line has a significant base of loyal customers who value the usability and benefits of integration to PeopleSoft's HR and ERP suites. It offered a broad range of functionality across all the major components of CRM, with particular strengths in sales, customer service, and analytics. It had less robust, but sound, capability for marketing, field service, eCommerce, and customer data management.

Although, the solution does not offer a SaaS deployment option, it provided unique support for specific industries such as the public sector, particularly education. It also provided strong support for the financial services, utilities and telecommunications sectors. All-in-all, PeopleSoft CRM was well-suited for existing PeopleSoft customers who need a broad-based CRM platform to build on.

The release of 9.1 demonstrates Oracle’s commitment to deliver an up-to-date solution for its steadfast PeopleSoft customer base. And, it will to capitalize on the industry sectors for which the solution is particularly well-tuned. The most notable improvements include features to improve user effectiveness such as a “Web 2.0” user experience, new collaboration tools, and reduced clicks and page transfers. The product has enhanced functionality in the marketing and customer service areas. And, it offers added additional capabilities that deepen already strong support for the Higher Education and Telecommunications sectors.

Mindful, of the growing popularly of SaaS CRM solution, the PeopleSoft 9.1 release also targets reducing the cost-of-ownership. For example, it features greater ease of application configuration than past releases. And, it has been tuned to improve system performance, and offers greater interoperability with expanded web services.

In an interesting twist for a CRM product, Oracle is taking advantage of its strong presence in the HR community and will offer “CRM-like” capabilities for this audience. PeopleSoft CRM delivers two products targeted at the Human Resources community: HelpDesk for Human Resources for workforce service delivery and the new Workforce Communications. HelpDesk for Human Resources was introduced in 2004 with integration to PeopleSoft HR. Workforce Communications was introduced earlier this year. And in 9.1, both of these products will provide delivered integration to eBusiness Suite HR release 12.1.

Oracle is investing in the right things that customers care about: a “Web 2.0” user experience, collaboration tools, marketing and service functionality improvements, and making upgrades easier. I am sure the PeopleSoft fan club will be glad they now have a fully up-to-date CRM solution available to them.

Telepresence Jumpstarts Video Collaboration

By Claire Schooley

Telepresence is the life-size, true color, no latency video meeting technology that creates a “wow” reaction from participants, especially those who have experienced some traditional videoconferencing that gave poor picture quality, out-of synch audio/video, and added no sense of presence to a meeting.  Here are some factors that make telepresence different:

• Video provides high quality 1080p pictures with hidden cameras placed to achieve eye contact no matter where people are seated around the conference table.
• Audio is full duplex with microphones and speakers that allow sound to come from the direction of the speaker.
• The environment is purpose-built with lighting arrays, speakers, and cameras all configured for the optimum experience.  Conference tables, chairs, and even the wall paint are the same at all sites to convey a uniform sense of presence.
• Managed service and support assure that this expensive system is going to work. Many organizations buy a concierge-type service model so participants just need to push a button to start the videoconference.

These kinds of telepresence rooms show up most often in board rooms and CEO conference rooms. The early traction of telepresence has been in connecting the global offices within an enterprise. However, the future lies in the external interoperability among different businesses and even competitors that use telepresence solutions from different vendors. This is only easily possible today among some vendors. Just as you can use your telephone to call people without thinking about the telephone carriers, companies need to have the same flexibility from telepresence providers.

While telepresence rooms have created the big stir, many companies can not afford such an expensive investment and don’t need such a large video presence.  This is where Telepresence is driving the advent of smaller HD conference room solutions, office units, and even desktop units that give the same high quality images and sound but don’t have quite the same ambiance as the large telepresence room. All units integrate so employees can take part in a multipoint call no matter what size unit they have. 

As my colleague Alex Cullen points out in his recent report, “The Top 15 Technology Trends EA Should Watch”, there has been plenty of buzz around the technology but business leaders are still unfamiliar with it. However, as the telepresence movement re-ignites interest in videoconferencing especially upgrading to HD units, these are the major reasons for the renewed interest in videoconferencing:

• Travel is expensive and it also eats up work time. Once companies make the culture shift to using videoconferencing whenever possible rather than travel, the savings on travel costs is the largest cost saving factor in determining ROI. But the video quality must give users a “you-are-there” experience to be successful.
• Today’s global reach of companies means that workers on the same team are often located in many different countries. Videoconferencing allows them to do things like view a product packaging together, decide on the best colors, and in the end be more productive.
• The new generation of workers is comfortable with video and welcomes the opportunity to collaborate with a stronger sense of presence.
• One of the strongest growth areas is desktop videoconferencing. Spurred on by high quality HD desktop units, large companies are evaluating what knowledge workers will benefit most from this technology.
• In the future with complete B2B and B2C interoperability you can expect:
• Accelerated commerce, globalization and outsourcing
• Less business travel which will impact financially airlines and hotels
• Expanded places where knowledge workers can live and work
• Major changes in business, education, medicine, branch government interaction, and entertainment

Pilots for many of these are underway now. For example, financial institutions are conducting wealth management or mortgage discussions with customers through bank to home videoconferencing. With the explosion of broadband to the home, there’s no reason to go to the bank when you can talk with a mortgage officer from your home HD unit. Medical experts located in facilities miles away can remotely review charts, and examine and talk with the patient remotely, and make a virtual diagnosis. And what about this one -- go out to a virtual dinner with friends located in a different city. Share conversation and discuss the food through the restaurants’ telepresence units!  (I would miss the bouquet of the wine from my friend’s selection.)