Ways To Address BI Skills Shortage

Boris Evelson
Whether you are just starting on your BI journey or are continuing to improve on past successes, a shortage of skilled and experienced BI resources is going to be one of your top challenges. You are definitely not alone in this quest. Here are some scary statistics:
  • “By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.” (Source: May 2012 McKinsey Global Institute report on Big Data)
  • “… trigger a talent shortage, with up to 190,000 skilled professionals needed to cope with demand in the US alone over the next five years.” (Source: 2012 Deloitte report on technology trends)
  • “Fewer than 25% of the survey respondents worldwide said they have the skills and resources to analyze unstructured data, such as text, voice, and sensor data.” (Source: 2012 research report by IBM and the Saïd Business School at the University of Oxford)
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Avoiding Big Data Sand Traps

Michele Goetz

Data management history has shown, it is not what you buy; it is how you are able to use it that makes a difference. According to survey results from the Q4 2012 Forrsights BI/Big Data Survey, this is a story that is again ringing true as big data changes the data management landscape. 

Overall . . .

  • Big technology adoption across various capabilities ranges from 8% to just over 25%.
  • Plans to implement big data technology across various capabilities is as high as 31%.
  • Pilot projects are the preferred method to get started.

However . . .

  • High-performing organizations (15%-plus annual growth) are expanding big data investments by one to two times in many big data areas compared with other organizations.

The key takeaway . . . 

  • For most organizations, big data projects aren't leaving the pilot stage and aren't failing to attain strong return on investment (ROI).
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Intro To Predictive Analytics Reading List

Mike Gualtieri

Predictive Analytics Is Red Hot

Why? What organization couldn’t benefit from making better decisions? Just ask the Obama campaign, which used sophisticated uplift modeling to target and influence swing voters. Or telecom firms that use predictive analytics to help prevent customer churn. Or police departments that use it to reduce crime. The list goes on and on and on. Virtually every organization could benefit from predictive analytics. Don’t confuse traditional business intelligence (BI) with predictive analytics. BI is about reports, dashboards, and advanced visualizations (which are still essential to every organization). Predictive is different. Predictive analytics uses machine learning algorithms on large and small data sets alike to predict outcomes. But predictive is not about absolutes; it doesn’t gaurentee an outcome. Rather, it’s about probabilities. For example, there is a 76% chance that this person will click on this display ad. Or there is a 63% chance that this customer will buy at a certain price. Or there is an 89% chance that this part will fail. Good stuff, but it’s hard to understand and harder to do. It’s worth it, though: Organizations that employ predictive analytics can dramatically reduce risk, disrupt competitors, and save tons of dough. Many are doing it now. More want to.

Few understand the what, why, and how of predictive analytics. Here’s a short, ordered reading list designed to get you up to speed super fast:

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Despite An Affair With My iPad, I Just Can’t Give Up My Laptop. . . Yet

Doug Washburn

A year and a half ago I broke up with Blackberry and started dating iPhone. It was a clean but cruel breakup: AT&T cancelled my T-Mobile contract on my behalf, the equivalent of getting dumped by your girlfriend’s new boyfriend.

This year I’ve been cheating on my laptop with my iPad. But it’s an on-again, off-again relationship. While I tell my iPad it’s the only one, I keep going back to my laptop. When I travel, my iPad is with me meeting clients. Meanwhile my laptop is in the hotel room surfing the online menu for a turkey club.

The iPad beats my laptop on size, weight, connectivity, and battery life. It also improves the human element when I’m having a face-to-face conversation but need to take notes. These are all critically important to me when I'm out of the office visiting clients or at an event.

But my laptop wins when I need to perform other important activities. For example, the larger screen really helps to write and edit research reports (John Rakowski, you’ll have your edits soon!). Or when I need to approve expenses behind the VPN or access files on my hard drive that I haven’t stored in Google Drive (yes, Forrester sanctioned).

Now that I've had a few months of compare both devices, I come back to outcomes . . .

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CeBIT 2013: Enabling Digital Disruptors

James McQuivey

In years past, technology trade shows like CeBIT or its cousin in the US, CES, have been a place for the introduction of new devices. Whether it was Nokia introducing its comeback phone or Sony pushing 3D displays, computing technology and consumer electronics companies have used these shows to introduce the next big thing.

But what happens when the next big thing isn’t actually a thing but is, instead, the arrival of platforms that enable a more effective marketplace? That’s the shift that’s occurring in the world, thanks to digital disruption. Under digital disruption, companies innovate by using cheap (sometimes free) digital tools and exploiting digital platforms to change products as low-tech as the toothbrush or waterless hand soap. They also use those digital tools to alter the way they make and deliver their products and services, including things as analog as fingernail polish, something I heard about today and will blog more on in coming weeks. As a result, every company is now digital, no matter how physical their processes and outputs.

Digital disruption means that the technology companies that provide these digital tools and platforms have more opportunity than ever. Their devices and systems will be necessary in the lives of every consumer as well as every enterprise. Witness the amazing growth of Amazon Web Services as it enables businesses across the gamut with its cheap access to storage and delivery tools.

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Mobile BI And Cloud BI Evaluation Criteria

Boris Evelson

Mobile BI and cloud BI are among the top trends that we track in the industry. Our upcoming Enterprise BI Platforms Wave™ will dedicate a significant portion of vendor evaluation on these two capabilities. These capabilities are far from yes/no checkmarks. Just asking vague questions like “Can you deliver your BI functionality on mobile devices?” and “Is your BI platform available in the cloud as software-as-a-service?” will lead to incomplete vendor answers, which in turn may lead you to make the wrong vendor selections. Instead, we plan to evaluate these two critical BI platform capabilities along the following parameters:

Mobile BI

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Don't Establish Data Management Standards

Michele Goetz

A recent survey of Enterprise Architects showed a lack of standards for data management.* Best practices has always been about the creation of standards for IT, which would lead us to think that lack of standards for data management is a gap.

Not so fast.

Standards can help control cost. Standards can help reduce complexity. But, in an age when a data management architecture needs to flex and meet the business need for agility, standards are a barrier. The emphasis on standards is what keeps IT in a mode of constant foundation building, playing the role of deli counter, and focused on cost management.

In contrast, when companies throw off the straight jacket of data management standards the are no longer challenged by the foundation. These organizations are challenged by ceilings. Top performing organizations, those that have had annual growth above 15%, are working to keep the dam open and letting more data in and managing more variety. They are pushing the envelope on the technology that is available.

Think about this. Overall, organizations have made similar data management technology purchases. What has separated top performers from the rest of organizations is by not being constrained. Top performers maximize and master the technology they invest in. They are now better positioned to do more, expand their architecture, and ultimately grow data value. For big data, they have or are getting ready to step out of the sandbox. Other organizations have not seen enough value to invest more. They are in the sand trap.

Standards can help structure decisions and strategy, but they should never be barriers to innovation.

 

*203 Enterprise Architecture Professionals, State of Enterprise Architecture Global Survey Month,2012

**Top performer organization analysis based on data from Forrsights Strategy Spotlight BI And Big Data, Q4 2012

Don't Establish Data Management Standards

Michele Goetz

A recent survey of Enterprise Architects showed a lack of standards for data management.* Best practices has always been about the creation of standards for IT, which would lead us to think that lack of standards for data management is a gap.

Not so fast.

Standards can help control cost. Standards can help reduce complexity. But, in an age when a data management architecture needs to flex and meet the business need for agility, standards are a barrier. The emphasis on standards is what keeps IT in a mode of constant foundation building, playing the role of deli counter, and focused on cost management.

In contrast, when companies throw off the straight jacket of data management standards the are no longer challenged by the foundation. These organizations are challenged by ceilings. Top performing organizations, those that have had annual growth above 15%, are working to keep the dam open and letting more data in and managing more variety. They are pushing the envelope on the technology that is available.

Think about this. Overall, organizations have made similar data management technology purchases. What has separated top performers from the rest of organizations is by not being constrained. Top performers maximize and master the technology they invest in. They are now better positioned to do more, expand their architecture, and ultimately grow data value. For big data, they have or are getting ready to step out of the sandbox. Other organizations have not seen enough value to invest more. They are in the sand trap.

Standards can help structure decisions and strategy, but they should never be barriers to innovation.

 

*203 Enterprise Architecture Professionals, State of Enterprise Architecture Global Survey Month,2012

**Top performer organization analysis based on data from Forrsights Strategy Spotlight BI And Big Data, Q4 2012

Impressions From Mobile World Congress 2013: Emphasize Usage Scenarios To Retain Relevancy

Dan Bieler

 

In light of my expectations (http://goo.gl/ZIU9d), Mobile World Congress contained few real surprises this year. This is not to say that MWC was boring: It provided valuable insights into the state of the mobile market from an enterprise perspective:

  • No single theme dominated. However, it felt as if everybody was talking about some combination of cloud, mobility, and big data. Many providers and vendors added the theme of customer experience to the mix and seasoned it with many acronyms. Unfortunately, in most cases this was not enough to trigger real excitement. The lack of a single new hot trend indicates that the mobile industry is maturing. Mobility has arrived center stage.
  • Most vendors are addressing consumerization only in the context of BYOD. In my view, BYOD is only one aspect of consumerization. I believe we will see the broader impact of consumerization in the near future. Consumers increasingly expect to work in a manner reflecting communication methods that are familiar in the context of friends and family. Also, consumers are increasingly asking to work when and where they want. Although some companies, including Yahoo (good luck!), are reintroducing the traditional concept of "the team works in the office," the overall trend is toward a more fragmented and consumerized working environment. In turn, this offers potential for mobile workplace solutions.
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Open Data Is Not Just For Governments Anymore...

Jennifer Belissent, Ph.D.

. . . Nor has it ever really been. Government data has long been a part of strategic business analysis. Census data provides insights into local standards of living and household budgets, health needs, education levels, and other factors that influence buying patterns for all kinds of goods and services. The US Bureau of Labor Statistics and the International Labour Organization provide data on employment and the availability of skilled labor that helps inform decisions on where to locate manufacturing or other facilities. The World Bank and UN data provides insights into global trends. 

Moreover, the release of government data has itself spurred billion-dollar industries. Think weather data released in the 1970s by the National Oceanic and Atmospheric Administration – which gave birth to the weather industry and services like Accuweather, weather.com, wunderground, and newer services like ikitesurf.com’s “wind and where.” Data from the US Global Positioning System (GPS) was opened to civilian and commercial use in the 1980s and has given rise to thousands of location-based services. Think FourSquare, Yelp, and Where’s The Bus?

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