Posts Tagged ‘Data2Decisions’

News Analysis: New #IBMWatson Business Group Heralds The Commercialization Of Cognitive Computing. Ready For Augmented Humanity?

IBM Launches New Business Group In New York’s Silicon Alley

On January 9th, 2014, on top of 4 World Trade Place, IBM CEO Ginni Rommety and long time veteran, but newly minted, IBM Watson Group Senior Vice President Michael Rhodin, announced IBM’s commitment to putting an entire business unit around Watson (see Figure 1).  The arrival of Watson represents a culmination of artificial intelligence, natural language processing, dynamic learning, and hypothesis generation to take vast quantities of data to make better decisions.  The IBM Watson business unit is the tech giant’s multi-year $1 billion initiative to deliver cloud based cognitive computing products for industries such as healthcare, retail, financial services, advertising, travel, and hospitality.

Figure 1. IBM Watson Group’s, Senior VP Mike Rhodin With A Warm Welcome

Source: IBM

Three key insights emerge from the launch:

  • IBM is committed to creating a brand new category and ecosystem. Focused on cognitive computing, over 2000 professionals form the newest business unit at IBM headquartered in New York City’s Silicon Alley.  The Watson ecosystem launched on November 14th, 2013 has over 750 applicants and $100M in equity investment (see Figure 2).  The ecosystem includes the Watson Developer Cloud, Watson Content Store, and the Watson Talent Hub.  In addition, the new business group is headed by IBM veteran Mike Rhodin.  Mike is a senior and well rounded executive who led the software solutions group which included the Business Analytics, Smarter Cities, Smarter Commerce, and Social Business product lines.

    Point of View (POV):
    The ability to self learn enables continuously reprogramming.  Cognitive computing is more than a new category.  These advancements represents a new class of technology to enable human and machine guided decisions.  IBM’s commitment can be seen by the level of executive and the management team chosen to grow a brand new class of software, services, and apps.  Constellation believes that the IBM Watson team has put forth a wide range of innovative ecosystem partnerships across a diverse set of industries.  In fact, the client solutions center and design lab are key to clients experiencing how Watson can create disruptive business models and transform an industry.  Moreover, the establishment of a business incubator is key to attracting crucial talent, technology, and ecosystem to spark new ventures.

 

Figure 1. IBM Showcases The Entire Watson Family and Ecosystem

Source: IBM

  • IBM is putting considerable resources towards the commercialization of products and services. At the unveiling, IBM announced three new cloud-delivered Watson offerings to add to the IBM Watson Engagement Advisor launched on May 21, 2013.  IBM Watson Discovery Advisor uses cognitive intelligence to apply context on vast quantities of unstructured and structured data.  The goal -  identify patterns for research teams to advance their efforts in industries such as pharma, publishing, and education.  IBM Watson Analytics provides capabilities that allow users to verbally ask questions and receive high quality data visualizations and insights.  IBM Watson Explorer provides the toosl to find, extract, and deliver content regardless of format or data source.
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Event Report: #NRF14 Preview – Retail’s Big Show Hints At Lessons Learned In #MatrixCommerce

Retails Big Show Transformed For 2014

Over 29,000 people are expected to gather at the National Retail Federation’s big show (NRF) this Sunday, January 11th, 2014, in New York City.  #NRF14 brings the intersection of new retail business models, products, store concepts, technology, society, and culture together!

A few big trends emerge based on conversations with our clients attending the event:

  1. Building out matrix commerce. Retail faces rapidly changing business models and new payment options that are often misunderstood and poorly integrated. Matrix commerce describes the fusing of demand signals and supply chains in an increasingly complex world of buyers seeking frictionless buying experiences. Channels move from multi-channel to total channels. As the world revolves around the buyer, channels, demand signals, supply chains, payment options, enablers, and big data will converge to create what Constellation coined in 2011 as Matrix Commerce. Matrix Commerce spans across disciplines as people, process, and technologies continue to transform today’s commerce models.  This shift to a buyer centric model will result in continued consolidation of retail technologies as stacks and ecosystems form around real buyer needs.  Lessons learned: There is no single end to end solution.  However, strong open standards and a focus on buyer centricity will help provide guide rails to success.
  2. Dealing with digital disruption. The convergence of the five forces of consumerization described in 2009 and 2010 serve as the five pillars of digital business.  Retailers recognize that they no longer sell products and services, as buyers seek experiences and outcomes. Market leaders and fast followers now democratize the data to decisions pathway to enable innovation at all levels More…

News Analysis: Verint Announces Intent To Acquire Kana For $514M

Verint Adds to Vovici and Contact Center Assets To Expand Customer Engagement Offerings


On January 6th, Melville, NY based Verint® Systems announced a $514M intent to acquire Sunnyvale, CA, KANA Software.  Verint is a software vendor with a core in analytical software.  Verint’s core offerings provide enterprise intelligence and security intelligence.  The acquisition is significant in the market because:

  • Big data and analytics meet customer experience. Verint expects to expand its customer engagement optimization offering with the acquisition of Kana.  Verint’s core capabilites, Vovici’s voice of the customer assets, and Kana’s multichannel customer experience solutions allow customers to move from data to information to insight to action or decisions.

    Point of View (POV):
    Bringing intelligence into customer experience adds context and relevancy. This combination is a key step in moving from systems of engagement to systems of mass personalization at scale.  Constellation expects more acquisitions that combine the 5 pillars of digital business – social, mobile, cloud, big data and analytics, and unified communications.
  • Verint gains key customers and industries. Verint’s key customer base of 10,000 customers gets 900 new customers in six key industires.  Kana’s base includes a variety of marquee brands and public sector agencies in the mid market to enterprise space.  Business service customers include Hyatt, Starwood, USPS, and Priceline.com.  Communications and media customers include O2, Comcast, Cox, Quest, Talk Talk Group, Telekom Austria, Telus, Time Warner Cable,  Tracfone, Virgin Mobile, and Vodafone.  Financial services customers include Admiral, Bank Leumi, Capital One, Chase, Citigroup, Domestic and General HSBC, ING, Barclays,  Standard Bank, and VHI.  Retail and wholesale clients include American Greetings, Avon, Carglass, Conrad, Foot Locker, Hanes More…

News Analysis: Salesforce 1 Signals Support For Digital Business at #DF13

Salesforce Seeks To Tackle Digital Business At Dreamforce

Over 125,000 virtual and physical registrants descend on San Francisco the week of November 17th for Dreamforce 13, a future of technology meets SXSW event.  One day in advance of the largest enterprise software event of its kind, Salesforce.com announces Salesforce 1 (see Figure 1).  The Salesforce 1 customer platform seeks to address a cadre of emerging digital business requirements that customer centric companies face.

Figure 1. Salesforce 1 Customer Platform Intends to Support The Internet Of Customers

Source: Salesforce.com

SalesForce 1 Reflects Much Needed Refresh Of Existing Platform

The new customer platform includes platform services, platform APIs, and the Apps created from the platform.  Salesforce 1 platform services includes refreshes in Force.com, updates in Heroku, and adds Exact Target Fuel.  As expected, Sales Cloud, Service Cloud, Exact Target Marketing Cloud, and Apps Exchange sit on top of the salesforce1.com platform (see Figure 2).

The key analysis of this release include:

  • Internet of Customers support. Salesforce includes social, mobile, cloud, and connected as the key components for The Internet of Things.  In order to meet the requirements of a third wave of computing that moves from Internet of Things to what Salesforce calls the Internet of Customers, the new platform is designed to support this customer centricity convergence.

    Point of View (POV):
    Constellation sees more than 50B connected devices and at least 150B connected endpoints by 2020.  The opportunity is huge.  While Salesforce.com addresses 3 out of the 5 key components of digital business, the vendor still needs to provide video/unified communications and big data/analytics.  Constellation believes the big data and analytics opportunity is critical to enhancing customer experiences, to benchmarking and brokering data servcies, and to buildoing new business models around big data and analytics.  Customers should encourage Salesforce.com to consider how to enable big data business models in digital business in the next iteration.  Meanwhile, most customers can wait until future releases for video and UC requirements to be met.
  • Next generation apps developer platform. The PaaS layer adds a mobile first orientation that enables a write once and deploy anywhere platform. Developers can now deploy to a range of social, mobile, and connected devices.  The platform services include 10X more API functionality.   Developers can build customer apps, wearable apps, product apps, and salesforce apps.

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Monday’s Musings: The Chief Digital Officer In The Age Of Digital Business

Market Leaders and Fast Followers Prepare for Digital Business In 2014

Conversations at Constellation’s Connected Enterprise last week validate a larger trend in the market place.  The audience of 220+ early adopters with 75% representing line of business and 25% in IT highlighted the convergence of the five forces of consumerization described in 2009 and 2010.  This convergence of these five pillars of digital business now form the foundation of all future digital business strategy and drive customer experience, matrix commerce, future of work, data to decisions, consumerization of technology, and digital marketing (see Figure 1.).  In fact, market leaders and fast followers have embraced this strategic direction in their 2014 planning.

Figure 1. Convergence Of The Five Pillars Drive Digital Business Strategy

Emerging Trends In 2014 Digital Business Strategy Reflect The Shift To Digital Business

As Constellation works with leaders to define their 2014 business strategies, digital transformation plays a key role.  Many organizations will:

  1. Recognize that they no longer sell products and services, as buyers seek experiences and outcomes.
  2. Democratize the data to decisions pathway to enable innovation.
  3. Realize that B2B and B2C are dead. It’s a P2P and M2M world.
  4. Focus on context as right time relevancy beats real time information overload.
  5. Shift from engagement to personalization at scale.

(A full update will be posted in Harvard Business Review soon)

The Bottom Line: Organizations Can Expect The Rise Of Chief Digital Officers

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News Analysis: The Vibe On Informatica’s Virtual Data Machine

Informatica Launches Vibe, A Virtual Data Machine For New Business Models

At Informatica World 2013 in Las Vegas, Informatica announced the Vibe Virtual Data Machine (VDM).  The VDM consists of 4 parts and an SDK (see Figure 1):

  1. Transformation library contains pre-built libraries for actions such as combine, transform, cleans, match and mask.
  2. Optimizer enables effective resource usage and efficient run-time.
  3. Executor is the run-time execution engine.
  4. Connectors provide access to multiple upstream and down stream data source.
  5. Vibe SDK enables a partner ecosystem.

Figure 1. Inside Vibe, the Virtual Data Machine

Source: Informatica

The VDM release is significant because Vibe:

Polls and Surveys: Who’s Missing In Our 2013 #BigData landscape?

Big Data Vendors Seek To Move From Data To Decisions

The move from Data to Decisions examines the enablement of data-driven decisions across the entire organization.  Holistic, data-informed decisions require a multi-diciplinary approach that incorporates performance monitoring with traditional business intelligence technologies. Gather key insights from your data, transform insights into actionable information, and then make the right decisions (see Figure 1).

Figure 1. The Shift From Data To Decisions

Source: Constellation Research, Inc. (right click to see the expanded image)

Four Sub Categories Emerge In The Big Data Landscape

Little shortage of solutions and vendors exists in the burgeoning big data  market. At last count, Constellation found 200+ vendors claiming to provide solutions.  As part of our research, we’re looking at big data in 4 sub categories (Figure 2):

  • Data sources. Information providers, structured data, content management, and unstructured data.
  • Information and orchestration. Acquisition tools, BI Appliances and VLDW, No SQL/New SQL, and governance.
  • Insight. Analytics and BI Visualization Tools.
  • Decisions and actions. Decision management, BPM, and CEP.

Figure 2. The Big Data Solutions Landscape

Source: Constellation Research, Inc. (right click to see the expanded image)

Your Help Requested

Between now and May 15th, we’re looking to complete this market overview and mapping. If we’ve missed a vendor or solution you are using, please let us know. In return for your time, we will add you to our Newsletter and include you in our Big Data Research panels (if you are a buyer).  For vendors who think we’ve missed them, we’re more than happy to take a look and see what you have.  Click here to mail feedback

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Although we work closely with many mega software vendors, we want you to trust us. For the full disclosure policy, stay tuned for the full client list on the Constellation Research website.

* Not responsible for any factual errors or omissions.  However, happy to correct any errors upon email receipt.

Copyright © 2001 -2013 R Wang and Insider Associates, LLC All rights reserved.
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Tuesday’s Tip: Focus On The Business Outcomes, Not Technology With Big Data

The Why Behind Big Data Starts By Asking What’s The Business Outcome

So organizations have lots of data.  New techniques have emerged to correlate big data.  Enamored by the potential of big data, leaders are now reinvesting in technologies to find hidden nuggets of insights with the business goals of:

  • Mitigating regulatory risks
  • Identifying operational efficiencies
  • Improving revenue growth
  • Creating market differentiation
  • Expanding the brand presence

These big data use cases often follow the business hierarchy of needs, which are based on concepts pioneered by Maslow (see Figure 1).  More importantly, a key question in big data has been to ask the right question.

Figure 1. The Business Hierarchy of Needs Drives Many Big Data Use Cases

An Information Flow Approach Moves The Discussion From Data To Decisions

Unfortunately, the problem is most organizations start by talking about outcomes and then get mired in the technologies to achieve these outcomes.  Big data technologies include advanced business analytics, application of existing technologies such as data warehousing and business intelligence.  In many cases, application of decision automation, semantic technology and collaborative tools are also needed. Yet, from Data to Decisions requires the integration of quite a few disciplines.

Data to decisions is about taking data sources, transforming them into useful information, gathering key insights, and then making the right decisions (see Figure 2).  Data sources, information, and orchestration belong in the realm of IT and hopefully will be delivered via the cloud.  Insight, decisions, and actions are line of business driven areas which deliver the most value add:

  • Data sources. Expect a mix of structured, semi-structured, and lots of unstructured.
  • Information and orchestration. The mix of information types include physical, virtual, machine, and contextual.
  • Insight. Information translated to insight considers performance, deduction, inference, and prediction.
  • Decisions and actions. The outcomes are driven from next best action, prevention, suggestion, and even no action.

Figure 2. The Flow From Data To Decisions

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Monday’s Musings: Trends In The Top Software Insider Posts of 2012 (#softwareinsider)

Thank You For Your Support

SoftwareInsider.org generated almost 10 million page views in 2012 (see Figure 1).  This does not include syndication through Constellation Research, Forbes (discontinued in 2012), Enterprise Irregulars, Computerworld UK, and other great media partners.

Figure 1.  Software Insider Achieved 9.8M Page Views for 2012

Classic Posts Address The Key Fundamentals In The Disruptive Technology Shift

Four posts have made the all time favorite list and address the 5 consumer technology forces that influence enterprise software.

  1. Monday’s Musings: How The Five Consumer Tech Macro Pillars Influence Enterprise Software Innovation
  2. Research Report: The 18 Use Cases of Social CRM and The New Rules of Relationship Management
  3. Tuesday’s Tip: Understanding the Many Flavors of Cloud Computing
  4. Best Practices: Five Simple Rules for Social Business

2012 Top 40 Reflects A Broader Shift To Business Outcomes And Technology Adoption

Analyst Relations and the World of Influence - The top blog post of 2013 discussed the future of the industry analyst versus legacy analyst firms.

Consumerization of Technology and The New C-Suite – The impact of technology on the C-suite has never been greater.  As business strategy relies more on technology, CMOs, CFOs, and other line of business heads can expect to work more closely with the CIOs and CTOs.

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Market Maker 1:1: Steve Miranda, Oracle Fusion Applications Update – The Inside Story

The Inside Story On Oracle Fusion Apps At The End of 2012


Constellation sat down with Steve Miranda, Oracle’s Executive Vice President of Oracle Applications Product Development to discuss the state of Oracle Fusion Apps in a no-holds barred honest conversation about what’s working, what’s not, and what to look forward to in 2013.

R “Ray” Wang (RW): Steve Miranda is Executive Vice President of Oracle Applications Product Development. He is responsible for leading all aspects of product strategy, product development, and product delivery for Oracle’s applications and related cloud services. This includes Oracle Fusion Applications and Oracle’s newest products for customer service and support, commerce, and talent management.

Mr. Miranda joined Oracle in 1992 and has held a variety of leadership positions within the development organization. In 2007 he was asked to lead the engineering of Oracle’s next-generation suite of software applications, Oracle Fusion Applications. Under Mr. Miranda’s leadership, Oracle has continually delivered on its promise to help its applications customers innovate and remain competitive while leveraging their existing IT investments and increasing the value of those investments with new Oracle products and services.

Prior to Oracle, Mr. Miranda worked at GE Aerospace. He holds degrees in mathematics and computational sciences from Stanford University.

 

CATCHING UP ON ORACLE FUSION APPLICATIONS TRACTION

(RW): As 2012 is coming to an end it is a good time to reflect on how Oracle Fusion Applications has been doing this year. It would seem that Oracle’s been quite quiet about Oracle Fusion Applications throughout the year. Is the product selling? What’s the state of the Oracle Fusion Applications product lines?

Steve Miranda(SM): Oracle Fusion Applications is doing very well. We’re actively selling the product. In fact, we already have over 400 customers on Oracle Fusion Applications. We’re doing better than Salesforce.com when they started. Keep in mind, we have a rich customer base looking for innovation.

RW: When you say “Oracle Fusion Applications is selling well”, is that the whole suite or components of Oracle Fusion Applications?

SM: We are actively selling the product. More than 400 customers are on Oracle Fusion Applications, that’s any part of Oracle Fusion Applications, not including RightNow, Taleo, Oracle Business Analytics, or Oracle Fusion Middleware. Two thirds of the customers have chosen to deploy in a SaaS model. Then the second largest deployment model but far below are on-premise and the rest are hosted in our managed services.

RW: Does “managed services” means they own their own license, right?

SM: That’s correct. What’s powerful about these deployments patterns is that customers are accessing innovation faster than before. We are at over 100 live customers and are averaging one go-live a day right now.

RW: I understand that Oracle deployed Oracle Fusion Applications internally? How was that experience in “drinking your own champagne”?

SM: Ray, that’s correct. We did drink our own champagne and we are now using Oracle Fusion CRM internally instead of Siebel.. We have a global single instance for the business. When we deployed, we started out with 2 instances to show case a co-existence approach and an end-to-end Oracle Fusion Applications approach. As of June 1, 2012, Oracle Fusion CRM was up around the world. All the territories, forecasting, quotas, sales force automation, and contacts are in Oracle Fusion CRM globally.

RW: Is it one instance now?

SM: Yes. We also went live w/ Oracle Fusion Financials Accounting Hub on the back end. We replaced Hyperion and Oracle E-Business Suite GL and also went live June 1, 2012. We’ve already done several month-end closes and we also have Oracle Fusion Talent Performance Management up live. Employees and managers are now doing goal setting and appraisals.

RW: To be honest with you Steve, we aren’t seeing Oracle much in head to head competitive new deals. We don’t see big press releases about new wins. Where are the customers? Who’s buying what and why?

SM: Well, first of all, many of our existing customers are coming to us about Oracle Fusion Applications. Second of all, and you may not believe this, we’re not focused on publicity, but rather we want to ensure customer success.. Each go-live is very important to us. In our first set of go-lives, we have 10,000 customers who want to talk to the first 10 go lives. We also don’t want to overwhelm our initial customers.

Let me give you some details and examples so you understand the breadth and depth of what the Fusion Apps base looks like and so there’s no confusion. Here’s a selected slice:

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Monday’s Musings: Understand The Four Organizational Personas Of Disruptive Tech Adoption

Pace of Innovation Exceeds Ability To Consume

Rapid innovation, flexible deployment options, and easy consumption models create favorable conditions for the proliferation of disruptive technology.  In fact, convergence in the five pillars of enterprise disruption (i.e. social, mobile, cloud, big data, and unified communications), has led to new innovations and opportunities to apply disruptive technologies to new business models.  New business models abound at the intersection of cloud and big data, social and mobile, social and unified communications, and cloud and mobile.

Unfortunately, most organizations are awash with discovering, evaluating, and consuming disruptive technologies.  Despite IT budgets going down from 3 to 5% year over year, technology spending is up 18 to 20%.  Why?  Amidst constrained budgets, resources, and time limits, executives are willing to invest in disruptive technology to improve business outcomes.  Consequently, successful adoption is the key challenge in consuming this torrent of innovation.  This rapid pace of change and inability to consume innovation detract organizations from the realization of business value.

Organizations Fall Into Four Personas Of  Disruptive Technology Adoption

A common truism in the industry is “Culture trumps technology”.  As organizations apply methodologies such as Constellation’s DEEPR Framework in improving adoption, leaders must first determine which of the four personas best fits their organization’s appetite for consuming and innovating with disruptive technologies.

The personas of disruptive technology adoption assess organizational culture in two key axes (see Figure 1).  The first is how incremental or transformational an organization looks at applying disruptive technology to business models.  The second assesses how proactive or reactive an organization is in carrying out new initiatives.  Based on these dimensions, the four personas include:

  1. Market leaders. Market leaders prefer to drive transformational innovation.  They look at technologies as enablers in disrupting business models.  They see competitive differentiation in delivering outcomes to customers. Market leaders accept failure as part of the innovation process.  They fail fast and move on.
  2. Fast followers. Fast followers prefer to react to the success of market leaders and their experiments.  When they sense success, they tend to jump in.  Fast followers do not like to fail and rapidly apply lessons learned from market leaders into their road maps.  Fast followers tend to deliver scale in the markets as a counter balance to arriving later in the market.
  3. Cautious adopters. Cautious adopters proactively deliver incremental innovation.  They tend to take a more measured approach and spend more time studying how they can improve an existing success than creating a transformational change.  Cautious adopters often come from regulated industries where security and safety are paramount objectives.
  4. Laggards. Laggards tend to procrastinate on applying innovations to their business models.  They prefer not be bothered by trends and will only react when the trends have moved beyond mainstream.  They see value in waiting as prices will drop over time as success rates increase over time.  Laggards enjoy waiting.

During the interviews and discussions with the 2012 Constellation SuperNova award participants, key questions emerged in the decision process on whether to adopt or pass on a disruptive technologies.  These questions aligned well with the four personas of disruptive technology adoption.

Figure 1.  Organizations Should Understand Which Persona Of Disruptive Tech Adoption Describes Them Best

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Market Maker 1:1: Beyond #BigData, The Shift To Decision Management w/ James Taylor (@jamet123)

From Data to Decisions – The Shift To Decision Management

Organizations have faced a constant technology arms race to achieve basic levels of decision management.  From data warehousing, to data marts, to reporting tools to BI, and now Big Data, organizations and leaders have been inundated with technology fads.  While the the latest buzz in technology may come and go, Constellation Research believes organizations seek a path from data to information to insight to action.  This path from Data to Decisions drives the science and discipline behind decision management.

Consequently, decision management in the data to decisions world examines the necessary tools, steps and methods for deriving insight from data and acting on it.  These tools are useful creating informed people and processes, but the continuation and follow-through to decisions and actions demands a robust set of performance monitoring and management practices. Those are the table stakes.  In many cases, application of decision automation, semantic technology and collaborative tools are also needed.   Data 2 decisions is about moving from insight to action and moving to fact based decisions making at all levels of the organization.

I sat down with James Taylor, a thought leader in this space to hear his insights on the latest trends.

The Inside View With James Taylor – One of The Leaders In Decision Management Systems


R “Ray” Wang (RW): James is the CEO and a Principal Consultant of Decision Management Solutions. He is the leading expert in how to use business rules and analytic technology to build Decision Management Systems. James is passionate about using Decision Management Systems to help companies improve decision making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision making technology. James has spent the last 20 years developing approaches, tools, and platforms that others can use to build more effective information systems. He has led Decision Management efforts for leading companies in insurance, banking, health management and telecommunications.

James is the author of “Decision Management Systems: A practical guide to using business rules and predictive analytics” (IBM Press, 2011). He previously wrote Smart (Enough) Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions (Prentice Hall) with Neil Raden, and has contributed chapters on Decision Management to multiple books including “Applying Real-World BPM in an SAP Environment”, “The Decision Model”, “The Business Rules Revolution: Doing Business The Right Way” and “Business Intelligence Implementation: Issues and Perspectives” as well as many articles to magazines.

In addition to strategy and implementation consulting, James delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world such as the Decision Management Summit, Business Rules Forum, Predictive Analytics World and IBM’s Business Analytics Forum.

James was previously a Vice President at Fair Isaac Corporation where he developed and refined the concept of decision management. The best known proponent of the approach, James helped create the emerging Decision Management market and is a passionate advocate of decision management. He understands how companies buy and use these technologies and he has helped companies successfully adopt these technologies and apply them in the context of Business Process Management and Business Intelligence initiatives.

1. I noticed that you are tying Decision Management to the Customer Relationships? What are some basic principles that someone knew to this space should know about?

James Taylor (JT): Historically Decision Management got applied primarily in risk and fraud but the energy recently has shifted to customer decisions. Decision Management works best on high volume, repeatable decisions. For most organizations, decisions about customers are the ones they take most often. Focusing on how to manage these decisions offers companies tremendous value in becoming more customer-centric and improving their customer engagement and relationships. At the end of the day your customer relationships are driven by their reaction to the decisions you make about them. Developing systems to manage these decisions that are agile enough to change when that is necessary, that embed analytics to improve these decisions, and that are adaptive so they can improve over time is a critical need for better customer relationships. Managing customer decisions is not the only thing you can do with Decision Management, just a great place to start to unlock customer value and drive the customer journey.

2. What’s been the big shift in the journey from Data to Decisions?

(JT): I think there have been three big shifts. The first is an increase in the use of more advanced analytics. Where reporting and perhaps dashboards used to be the primary way to use data, now more organizations are using data mining, predictive analytics and advanced visualization techniques. We see a tremendous growth in these more advanced analytics. Second we also see a focus on operations and operational decisions, with more organizations trying to improve decision-making at the front-line of their organization – where they interact with customers and their supply chain – not just in their back office. Finally we are beginning to see organizations becoming explicit about the decisions involved. Instead of just putting data out there, summarizing it and perhaps visualizing it and hoping that someone will be able to make better decisions, organizations are explicitly identifying the decisions that they need to improve. Then they are building the right kind of decision support or decision management system to ensure that decision gets done right. This last topic is a personal interest and one of the most exciting sessions for me is the hands-on session where folks will actually get to do some decision modeling.

3. Where are we with this fad and hype around #bigdata? Is this just the beginning or will we morph?

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