Expand Your Big Data Capabilities With Unstructured Text Analytics

Beware of insights! Real danger lurks behind the promise of big data to bring more data to more people faster, better, and cheaper: Insights are only as good as how people interpret the information presented to them. When looking at a stock chart, you can't even answer the simplest question — "Is the latest stock price move good or bad for my portfolio?" — without understanding the context: where you are in your investment journey and whether you're looking to buy or sell. While structured data can provide some context — like checkboxes indicating your income range, investment experience, investment objectives, and risk tolerance levels — unstructured data sources contain several orders of magnitude more context. An email exchange with a financial advisor indicating your experience with a particular investment vehicle, news articles about the market segment heavily represented in your portfolio, and social media posts about companies in which you've invested or plan to invest can all generate much broader and deeper context to better inform your decision to buy or sell. 
 
But defining the context by finding structures, patterns, and meaning in unstructured data is not a simple process. As a result, firms face a gap between data and insights; while they are awash in an abundance of customer and marketing data, they struggle to convert this data into the insights needed to win, serve, and retain customers. In general, Forrester has found that: 
 
  • The problem is not a lack of data. Most companies have access to plenty of customer feedback surveys, contact center records, mobile tracking data, loyalty program activities, and social media feeds — but, alas, it's not easily available to business leaders to help them make decisions. 
Read more

An Approach To Converge The Worlds of Big Data And BI

Webster dictionary defines a synonym as "a word having the same or nearly the same meaning" or as "a word or expression accepted as another name for something." This is so true for popular definitions of BI and big data. Forrester defines BI as:

 

A set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making.
 
While BI has been a thriving market for decades and will continue to flourish for the foreseeable future, the world doesn't stand still and:
Read more

The Forrester Wave™: Enterprise Business Intelligence Platforms, Q1 2015

The majority of large organizations have either already shifted away from using BI as just another back-office process and toward competing on BI-enabled information or are in the process of doing so. Businesses can no longer compete just on the cost, margins, or quality of their products and services in an increasingly commoditized global economy. Two kinds of companies will ultimately be more successful, prosperous, and profitable:

  • More and deeper insights will generate competitive advantage. Companies with richer, more accurate information about their customers and products than their competitors will gain substantial competitive advantage.
  • Faster access to insights will make companies more agile. Companies that have the same quality of information as their competitors but get it sooner and can turn it into action faster will outpace their peers.
Read more

It's Not Your Grandfather's Open Source BI Market Any Longer

There's never been a question on the advantages of open source software. Crowdsourcing, vendor independence, ability to see and in some cases control the source code, and lower costs are just a few benefits of open source software (OSS) and business model. Linux and Apache Hadoop are prime examples of successful OSS projects. It's a different story, however, when it comes to OSS BI. For years, OSS BI vendors struggled with growth because of:

 

  • The developer-centric nature of open source projects. The target audience for open source projects is developers, which means deals are mostly sealed by technology management. The industry, on the other hand, has gravitated toward business decision-makers within organizations over the last several years. However, business users are less interested in the opportunities that a collaborative open source community offers, and more concerned about ease of use and quick setup. Indeed, Forrester's research constantly finds evidence correlating business ownership as one of the key success factors for effective BI initiatives.
Read more

Build An Agile BI Organization

The battle of trying to apply traditional waterfall software development life-cycle (SDLC) methodology and project management to Business Intelligence (BI) has already been fought — and largely lost. These approaches and best practices, which apply to most other enterprise applications, work well in some cases, as with very well-defined and stable BI capabilities like tax or regulatory reporting. Mission-critical, enterprise-grade BI apps can also have a reasonably long shelf life of a year or more. But these best practices do not work for the majority of BI strategies, where requirements change much faster than these traditional approaches can support; by the time a traditional BI application development team rolls out what it thought was a well-designed BI application, it's too late. As a result, BI pros need to move beyond earlier-generation BI support organizations to:

  • Focus on business outcomes, not just technologies. Earlier-generation BI programs lacked an "outputs first" mentality. Those projects employed bottom-up approaches that focused on the program and technology first, leaving clients without the proper outputs that they needed to manage the business. Organizations should use a top-down approach that defines key performance indicators, metrics, and measures that align with the business strategy. They must first stop and determine the population of information required to manage the business and then address technology and data needs.
Read more

Get Ready For BI Change

To compete in today's global economy, businesses and governments need agility and the ability to adapt quickly to change. And what about internal adoption to roll out enterprise-grade Business Intelligence (BI) applications? BI change is ongoing; often, many things change concurrently. One element that too often takes a back seat is the impact of changes on the organization's people. Prosci, an independent research company focused on organizational change management (OCM), has developed benchmarks that propose five areas in which change management needs to do better. They all involve the people side of change: better engage the sponsor; begin organizational change management early in the change process; get employees engaged in change activities; secure sufficient personnel resources; and better communicate with employees. Because BI is not a single application — and often not even a single platform — we recommend adding a sixth area: visibility into BI usage and performance management of BI itself, aka BI on BI. Forrester recommends keeping these six areas top of mind as your organization prepares for any kind of change.

Some strategic business events, like mergers, are high-risk initiatives involving major changes over two or more years; others, such as restructuring, must be implemented in six months. In the case of BI, some changes might need to happen within a few weeks or even days. All changes will lead to either achieving or failing to achieve a business. There are seven major categories of business and organizational change:

  1. People acquisitions
  2. Technology acquisitions
  3. Business process changes
  4. New technology implementations
  5. Organizational transformations
  6. Leadership changes
Read more

BI-Self Service Will Close The Business And Technology Gap In 2015

Two epic battles have been going on for decades in the world of Business Intelligence and Analytics. Who has the ultimate control of these domains, Business or Technology? And which in the grand scheme of things has a higher priority, customer facing vs. back office analytics? Well, in what Forrester calls the age of the customer (AOC), the results are in. Customer facing priorities trump back office priorities and business users rule. Battle fought and won. Period. End of story.
 
It should be no surprise to our readers that the top five predictions we picked for BI by triangulating our AOC and Agile BI research with client interactions and survey results are all about empowering business users with tools and applications to be self-sufficient, effective and efficient in their unrelenting quest to win, serve and retain customers.
 
#1 Managed BI Self-Service Will Continue To Close The Business And Technology Gap. Traditionally, technology management-driven enterprise BI and business user-driven, self-service BI have gone their separate ways, wrestling each other for scalability, a single version of the truth, and reduced operational risk versus agility, flexibility, and faster time-to-market. Forrester predicts that these two camps slowly by surely will learn how to live happily ever after in 2015 by deploying technologies, architectures, and best practices that allow technology management to monitor business-user-generated BI content and selectively productionalize it.
 
Read more

Categories:

Agile, flexible, modern BI deployments often require help from the professionals

Digitally empowered customers — both businesses and consumers — wield a huge influence on enterprise strategies, policies, and customer-facing and internal processes. With mobile devices, the Internet, and all-but-unlimited access to information about products, services, prices, and deals, customers are now well informed about companies and their products, and are able to quickly find alternatives and use peer pressure to drive change. But not all organizations have readily embraced this new paradigm shift, desperately clinging to rigid policies and inflexible business processes. A common thread running through the profile of most of the companies that are not succeeding in this new day and age is an inability to manage change successfully. Business agility — reacting to fast-changing business needs — is what enables businesses to thrive amid ever-accelerating market changes and dynamics.

Read more

Salesforce.com Enters The BI Market With Wave, The Salesforce Analytics Cloud

There just might be another 800-lb gorilla in the Business Intelligence market. In a year.

The popular cult book “Hitchhiker's Guide To The Galaxy” by Douglas Adams defines space as “. . . big. Really big. You just won't believe how vastly, hugely, mind-bogglingly big it is. . .” There are no better words to describe the size and the opportunity of the business intelligence market. Not only is it “mind-bogglingly big,” but over the last few decades we’ve only scratched the surface. Recent Forrester research shows that only 12% of global enterprise business and technology decision-makers are sure of their ability to transform and use information for better insights and decision making, and over half still have BI and analytics content sitting in siloed desktop-based shadow IT applications that are mostly based on spreadsheets.

The opportunity has provided fertile feeding ground to more than fifty vendors, including: full-stack software vendors like IBM, Microsoft, Oracle, and SAP, each with $1 billion-plus BI portfolios; SAS Institute, a multibillion BI and analytics specialist; popular BI vendors Actuate, Information Builders, MicroStrategy, Qlik, Tableau Software, and Tibco Software, each with hundreds of millions in BI revenues; as well as dozens of vendors ranging from early to late stage startups.

Read more

The Good The Bad And The Ugly Of Enterprise BI

Unified information architecture, data governance, and standard enterprise BI platforms are all but a journey via a long and winding road. Even if one deploys the "latest and greatest" BI tools and best practices, the organization may not be getting any closer to the light at the end of the tunnel because:
  • Technology-driven enterprise BI is scalable but not agile. For the last decade, top down data governance, centralization of BI support on standardized infrastructure, scalability, robustness, support for mission critical applications, minimizing operational risk, and drive toward absolute single version of the truth — the good of enterprise BI — were the strategies that allowed organizations to reap multiple business benefits. However, today's business outlook is much different and one cannot pretend to put new wine into old wine skins. If these were the only best practices, why is it that Forrester research constantly finds that homegrown or shadow BI applications by far outstrip applications created on enterprise BI platforms? Our research often uncovers that — here's where the bad part comes in — enterprise BI environments are complex, inflexible, and slow to react and, therefore, are largely ineffective in the age of the customer. More specifically, our clients cite that the their enterprise BI applications do not have all of the data they need, do not have the right data models to support all of the latest use cases, take too long, and are too complex to use. These are just some of the reasons Forrester's latest survey indicated that approximately 63% of business decision-makers are using an equal amount or more of homegrown versus enterprise BI applications. And an astonishingly miniscule 2% of business decision-makers reported using solely enterprise BI applications.
Read more