Data to Decisions « A Software Insider's Point of View

Posts Tagged ‘Data to Decisions’

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

Published on April 25, 2013 by R "Ray" Wang

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.

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Event Report: Informatica Analyst Day Reveals A Growth Strategy

Published on March 18, 2013 by R "Ray" Wang

Informatica Sets The Stage For A New Chapter In Its History

Informatica held its annual industry analyst day February 26th to 27th, 2013 at the Rosewood Sandhill in Menlo Park. The event showcased Informatica’s go-forward strategy and road map for growth over the next three years. Key highlights include:

Capturing a $6.5B market opportunity in license and subscription revenues. Marge Breya, Informatica’s new CMO, set the stage with a vision of how Informatica is poised to capture a $6.5B addressable market. Key use cases include analytics, operational integration, cloud integration, master data management, and data governance. Achieving these results will require $3.6B in installed base plays, $1,9B in new logo plays, and $1B in geographic expansion. Key markets for geographic expansion include replacing hand coding in Brazil, China, Japan, Mexico, and Russia.

Point of View (POV): Constellation estimates a $300B enterprise software market for 2013 with $130B in applications and $170B in infrastructure software. Informatica intends to go after a $6.5B addressable market that includes analytics, cloud data integration, operational data integration, master data management, and messaging. Success will require an expansion in focus from the traditional IT leaders and developer buyers to the emerging needs of business leaders.

Supporting a world of Hybrid IT. Juan Carlos Soto, SVP & GM for Informatica Cloud, discussed how clients now see Hybrid IT as the new norm. In fact, cloud based adoption has shifted from line of business (LOB) owned to IT led adoption of cloud over the past three years. Soto sees three pillars of success that include delivery of a platform for hybrid IT, cloud services for all, and Informatica inside. Key features for 2013 include data masking, process automation, integration with Microsoft Dynamics AX, integration with NetSuite, integration with Workday, integration with Oracle CRM On Demand, integration with Amazon RedShift, and integration with Ultimate Software (which was announced March 13th).

(POV): In a world of Hybrid IT, Constellation expects integration to be a core requirement for success. Consumerization of IT has led to a proliferation of mobile and cloud endpoints that require sophisticated data integration capabilities among all possible connections, data flows, business processes, and access. Informatica’s success depends on its ability to attract the cloud integration decision makers and users for basic cloud integration for enterprise and those seeking more complicated enterprise cloud integration use cases. The platform for a Hybrid IT play via a Virtual Data Machine (VDM) has the most potential for success in creating new business models. Informatica Inside will succeed so long Informatica is seen as “the Switzerland” for integration in cloud stacks and solutions.

Providing the integration and quality requirements for a big data world. Ash Kulkarni, SVP & GM for Data Integration and Data Quality, addressed the analytical integration, operational integration, and data governance strategy. Informatica’s themes for next generation data integration include agility in development, flexibility for deployment, and confidence in management. New features in analytical data integration include built-in data virtualization, complex event processing, support for decision making, and big data integration for Hadoop customers. The data governance features include improved inference for data domain discovery, automated enterprise data discovery, business friendly glossaries with rich metadata lineage, streamlined workflow and task management, data masking, visual exception auditing, audit data retention policies for production and legacy apps archiving,
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Tuesday’s Tip: Focus On The Business Outcomes, Not Technology With Big Data

Published on February 26, 2013 by R "Ray" Wang

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

Published on December 31, 2012 by R "Ray" Wang

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

Published on December 2, 2012 by R "Ray" Wang

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:

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.
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.
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.
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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News Analysis: Spigit Buys CrowdCast To Corner Innovation Life Cycle Market

Published on October 6, 2012 by R "Ray" Wang

On September 18, 2012, Pleasanton, CA based Spigit, a social innovation vendor acquired Crowdcast, a San Francisco based social business intelligence pioneer for an undisclosed sum. Crowdcast Founder/CEO Mat Fogarty and Chief Scientist Leslie Fine will join Spigit’s executive team as part of the acquisition. Crowdcast is backed by Menlo Ventures and Alsop Louie Partners.

Spigit, which has raised over $26M to date, brings 1200+ worldwide customers that can benefit from the Crowdcast offering. Key customers include MetLife, American Express, Walmart, GE, Pepsico, Nike, Merck, Sprint, Farmers Insurance, CapGemini, and Warner Brothers. Crowdcast customers include SAP, Boeing, Hershey’s, iARPA, and Electronic Arts.

This acquisition signifies larger trends for customers in the crowdsourcing and innovation market who:

Seek the ability to move from crowd sourced data to actionable decisions. Founded in 2007, Crowdcast allows companies to crowd source organizational knowledge and intelligence from employees and partners to improve decision making. Crowdcast tracks and rewards employees for their accuracy in predictions. Meanwhile, Spigit Engage provides the key tools to match social collaboration with traditional work flow. Spigit ICON supports ideation via a question and answer format. As part of the agreement, Spigit will add four Crowdcast patents to its patent portfolio.

Point of View (POV): Spigit’s core customers expect to move beyond social collaboration and ideation in isolation. Spigit’s integration with Sharepoint, Yammer, Jive, and Facebook will expand the reach of these solutions through partnerships. In addition, Spigit’s core offerings, Engage and ICON, support the innovation process from concept to execution while Crowdcast delivers innovation from post execution to prediction. Pairing these two powerful capabilities closes the loop from data to decisions. With informed people and processes, organizations can seek follow-through to decisions and actions from crowd sourced data. Should the combined entity achieve integration, customers will achieve this end to end capability.

Expect to transform innovation from art to discipline. As part of the agreement, Spigit will add all of Crowdcast’s patents to its portfolio. The combination allows customers to take traditionally qualitative approaches and craft repeatable and quantifiable results.

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

Published on September 13, 2012 by R "Ray" Wang

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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