The Formula for Analytics Success: Data Knowledge

November 12, 2012

Companies spend a small fortune continually investing and reinvesting in making their business analysts self-sufficient with thelatest and greatest analytical tools. Most companies have multiple project teams focused on delivering tools to simplify and improve business decision making. There are likely several standard tools deployed to support the various data analysis functions required across the enterprise: canned/batch reports, desktop ad hoc data analysis, and advanced analytics. There’s never a shortage of new and improved tools that guarantee simplified data exploration, quick response time, and greater data visualization options, Projects inevitably include the creation of dozens of prebuilt screens along with a training workshop to ensure that the users understand all of the new whiz bang features associated with the latest analytic tool incarnation.  Unfortunately, the biggest challenge within any project isn’t getting users to master the various analytical functions; it’s ensuring the users understand the underlying data they’re analyzing.

If you take a look at the most prevalent issue with the adoption of a new business analysis tool is the users’ knowledge of the underlying data.  This issue becomes visible with a number of common problems:  the misuse of report data, the misunderstanding of business terminology, and/or the exaggeration of inaccurate data.  Once the credibility or usability of the data comes under scrutiny, the project typically goes into “red alert” and requires immediate attention. If ignored, the business tool quickly becomes shelfware because no one is willing to take a chance on making business decisions based on risky information.

All too often the focus on end user training is tool training, not data training. What typically happens is that an analyst is introduced to the company’s standard analytics tool through a “drink from a fire hose” training workshop.  All of the examples use generic sales or HR data to illustrate the tool’s strengths in folding, spindling, and manipulating the data.  And this is where the problem begins:  the vendor’s workshop data is perfect.  There’s no missing or inaccurate data and all of the data is clearly labeled and defined; classes run smoothly, but it just isn’t reality  Somehow the person with no hands-on data experience is supposed to figure out how to use their own (imperfect) data. It’s like someone taking their first ski lesson on a cleanly groomed beginner hill and then taking them up to the top of an a black diamond (advanced) run with step hills and moguls.  The person works hard but isn’t equipped to deal with the challenges of the real world.  So, they give up on the tool and tell others that the solution isn’t usable.

 

All of the advanced tools and manipulation capabilities don’t do any good if the users don’t understand the data. There are lots of approaches to educating users on data.  Some prefer to take a bottom-up approach (reviewing individual table and column names, meanings, and values) while others want to take a top-down approach (reviewing subject area details, the associated reports, and then getting into the data details).  There are certainly benefits of one approach over the other (depending on your audience); however, it’s important not to lose sight of the ultimate goal: giving the users the fundamental data knowledge they need to make decisions.  The fundamentals that most users need to understand their data include a review of

The above details may seem a bit overwhelming if you consider that most companies have mature reporting environments and multi-terabyte data warehouses.  However, we’re not talking about training someone to be an expert on 1000 data attributes contained within your data warehouse; we’re talking about ensuring someone’s ability to use an initial set of reports or a new tool without requiring 1-on-1 training.  It’s important to realize that the folks with the greatest need for support and data knowledge are the newbies, not the experienced folks.

There are lots of options for imparting data knowledge to business users:  a hands-on data workshop, a set of screen videos showing data usage examples, or a simple set of web pages containing definitions, textual descriptions, and screen shots. Don’t get wrapped up in the complexities of creating the perfect solution – keep it simple.  I worked with a client that deployed their information using a set of pages constructed with PowerPoint that folks could reference in a the company’s intranet. If your users have nothing – don’t’ worry about the perfect solution – give them something to start with that’s easy to use.

Remember that the goal is to build users’ data knowledge that is sufficient to get them to adopt and use the company’s analysis tools.  We’re not attempting to convert everyone into data scientists; we just want them to use the tools without requiring 1-on-1 training to explain every report or data element.

Thanks to http://evanjlevy.wordpress.com/2012/11/12/the-formula-for-analytics-success-data-knowledge/


The Predictive Analytics Revolution- Are you sitting on the sidelines?

October 18, 2012

Predictive analytics (or Big Data) is here to stay. You may not understand it. You may not believe that it really works. But the reality is this: your competitors (and it may be just one or two of them) are using predictive analytics to chew up market space as you remain on the sidelines.

Don’t believe me? Consider the retail space. Who is the undisputed king of retail? That’s right, Wal-Mart. What’s their secret? What has given them the edge for so many years over their competitors? Data analysis. They live and die by data and have been for decades. Wal-Mart knows their customer data better than anyone and have the market share to prove it.

Recently the Dollar stores took on Wal-Mart by providing cheaper supplies like toiletries and medicine. Their strategy started to see some success and Wal-Mart even started to lose market share. But the retail giant went back to their data for a solution. The data said that many Wal-Mart customers started pinching pennies at the end of each month and needed a few basic items to get them over until payday. The solution, stocking shelves with thousands of items under $1 at the end of each month. Customers lured to the Dollar stores for such items were back in the Wal-Mart fold.

Target has also jumped into the game with their own consumer analytics program. The most famous example is how they used in-store data to pick out pregnant women through their shopping habits. They used this information to send marketing material promoting baby products. It worked…almost too well.

Wal-Mart, Target, and online stores like Amazon have forced everyone in this market make a decision, if you want to compete in retail you had better jump into the data science and predictive analytics game or a going-out-of-business-sale is in your near future. Sitting on the sidelines is not an option.

This isn’t isolated to just retail. There are stories everyday in the news about companies in a variety of markets taking a second look at their data and finding a treasure trove of valuable information.

Despite the hype and the proof that predictive analytics can give companies a competitive edge, the sidelines are full of businesses that are still not sure about getting in the game.

The New York Times reported that a handful of universities are using their data and predictive analytics to help them find students who are about to drop out of school. These schools know that higher enrollment means more money. These early adopters are reaping the benefits and aren’t afraid to tell everyone. Why? The vast majority of their competitors haven’t given this type of data analysis a second thought. Just like the example above, a few colleges will charge ahead and reap the benefits of higher enrollment while other universities…sit on the sidelines.

You can find the same thing in the health care industry. The Wall Street Journal published an article by Dr. Marty Makary of Johns Hopkins pleading with hospitals to make better use of their data to save lives. You can almost hear the frustration in his voice when he writes, “Medical mistakes kill enough people each week to fill four jumbo jets.” Even though there are 98,000 deaths due to medical errors in the United State, most hospitals and medical facilities are slow to adapt any type of data analytics.

A few forward thinking hospitals and health care facilities will see the opportunity and do what Dr. Makary suggests. Using the data visualization and predictive analytics, the trend setters have improved patient care, are keeping costs down – and most importantly – saving lives in the process. But just like the universities, the majority of hospital will remain on the sidelines. (I hope I can take my family to the forward thinking hospital!)

Why are so many still sitting on the sidelines?

The Harvard Business Review may have the answer. In an an eye opening survey they reveal the source of the bottleneck. (I highly recommend reading this entire study.) The study shows that the hype and awareness about data analytics is at an all time high.

According to the survey, a vast majority of companies are planning Big Data initiatives:

  • 85% of organizations reported that they have Big Data initiatives planned or in progress.
  • 70% report that these initiatives are enterprise-driven.
  • 85% of the initiatives are sponsored by a C-level executive or the head of a line of business.
  • 75% expect an impact across multiple lines of business.
  • 80% believe that initiatives will cross multiple lines of business or functions.

But here is where the rubber meets the road. HBR reports that:

  • Only 15% of respondents ranked their access to data today as adequate or world-class.
  • Only 21% of respondents ranked their analytic capabilities as adequate or world-class.
  • Only 17% of respondents ranked their ability to use data and analytics to transform their business as more than more than adequate or world-class.

The majority of companies are on the sidelines because they think they can’t readily access the data they have, they don’t have in house tools or talent to analyze it and don’t have the ability to put the data to use anyway. In other words, they don’t think their data is good enough.

Don’t let this kind of thinking keep you on the sidelines. I talk to business owners everyday who think they don’t have enough data for predictive analytics or even just analytics. Most of time, just the opposite is true. Many of our clients were pleasantly surprised when we told them they had more than enough data to jump into the game.

Don’t be one of crowd still sitting on the sidelines. Be one of those early adopters in your market space that uses predictive analytics to jump ahead of the competition. Would you like to learn more?

Thanks to http://blog.canworksmart.com/predictive-analytics/the-predictive-analytics-revolution/?buffer_share=e125e

 


Mastering Big Data

October 3, 2012

Date: Thursday, November 1, 2012
Time: 14:00 – 15:00 GMT

Big data analytics has already turned entire industries on their heads. To date, many big data analytics are associated with “machine generated” data like trade information, location data, etc. However, 80% of organizational data lives on file servers, NAS devices and email systems in the form of spreadsheets, presentations, audio files, video files, blueprints and designs—human generated content.

Learn how big data analytics helps organizations better leverage, manage, and protect their human generated content:

  • Identify areas of high risk
  • Optimize workflows
  • Connect disparate teams and data sets
  • Discover new patterns, flag potential abuse
  • Enhance data access control, ownership, classification, entitlements and authorization processes

Please see link below to the webinar

http://www.varonis.com/partner/uk/promo/1?utm_source=VAR-C24-UK


Data Science: Beyond Intuition – The Movie

August 31, 2012

Data science is changing the way we look at business, innovation and intuition. It challenges our subconscious decisions, helps us find patterns and empowers us to ask better questions. Hear from thought leaders at the forefront including Growth Science, IBM, Intel, Inside-BigData.com and the National Center for Supercomputing Applications. This video is an excellent source of information for those that have struggled trying to understanding data science and its value.


Information Big Data Video

March 21, 2012

A nice, short, 2 minute video from edCetra Training with some good facts about big data and data analysis.

The digital universe is 10 times the size it was in 2005
Greater literacy and cloud computing are helping fuel big data
80% of companies data is unstructured – difficult to analyze
Employees spend 2 hours per day searching for the right information


Data and how it is growing

January 24, 2012

Rise of Data

Widely discussed and referred to as Big Data the recent explosion in the amount of information available is causing many businesses problems, yet for some it’s providing opportunity.

I recently presented to an audience of IT decision makers at Manchester City Football Club on the subject of Data; Big Data, Bad Data, Data Security and Data Analytics. A wide topic to cover and one that is close to the hearts of many businesses it was clear that everyone in the audience recognised that data volumes are on the increase. Within the group there seemed to be several different schools of thought on how to deal with the problem; some were considering archiving solutions, some were looking into cloud based back-up solutions and some were simply adding new storage hardware as and when it was needed.

Although storage and back-up requirements have always been high on the IT Departments radar and data volumes have always been on the increase something is different now. The exponential growth of worldwide data volumes over the last five years has come as a shock to many businesses. No-one is quite certain exactly how much but it’s generally accepted that we create the same amount of data every 2 days as we did between the dawn of time and 2003. That relates to around 90% of the world’s data being created in the last two years, startling facts for companies who invest increasing amounts of capital and operational costs to store and recover business critical data.

Gartner predicts that data will grow 800% over the next five years, as Einstein once said, “You can’t expect different results doing the same thing”
The increase in the amount of data interests me, not just because I’m involved with a company that provides data management solutions but because I can see the hidden value that this new data offers to those prepared to look for it. But first we need to understand where this explosion of data is coming from and more to the point, where’s it’s going to take us.

It is estimated that 80% of the world’s data is unstructured; unstructured data being information that does not fit within a pre-defined format or model such a free written text, blogs, photos etc. One explanation for the increasing amount of unstructured data is the marked increase in Social Media and Blogging activity over the last five years.

Rise of the Blogger


Blogging comes in many different guises, Video Blogging, Photo Blogging, Web Blogging and of course Micro Blogging (Twitter, Facebook). Recent figures indicate that around 30% of people now blog in some form or another increasing blog posts to around 34million, a figure that is expected to double every six months.
Facebook alone has 30 billion pieces of content added every month and YouTube see over 48 Hours of footage uploaded every minute. These Social Networking sites make it as easy as possible for us to share our favourite video, photo or poem across multiple platforms within our own private networks or, for the world to see. This process of sharing information across our networks creates multiple copies thus further adding to the pool of worldwide information.
It’s estimated that around 70% of the world’s data is a copy of a copy of a copy and whilst Social Media can’t be held entirely responsible for the dramatic rise in data volumes it is most definitely a major influencer. Some sceptics suggest that the Social Media Tsunami is receding and although it’s been reported that Facebook have lost 8 Million users this last couple of months it has also been reported that Facebook is likely to reach 1 Billion users by Autumn 2012.
That’s a 1/6th of the population of the Globe sharing, liking, posting and creating data – just on Facebook.
It’s not just Facebook that is experiencing an increase in attention. Twitter adds 6 new accounts every second and Stumbleupon has doubled its members in just one year to over 20 million. The blogging site Tumblr experienced a 172% increase in traffic from October 2010 to October 2011 and new sites like Pin Interest are enjoying mass sign-ups resulting in a 512% increase in use over 6 months in 2011. In addition, Google+ signed a staggering 625,000 new accounts every day during the Christmas period of 2011 catapulting them to 90Million users within a year of launch.
It’s hardly surprising that “big data” and “social media” now appear at the top of corporate meeting agendas around the globe. They are inherently twisted together in the fabric of our on-line lives and will continue to mature together as close allies, for it’s this data, the data that we post that is valuable.

Wikipedia and Google share a similar outlook on this data: To empower and engage people to document the sum of all human knowledge, and to make it available to all humanity, in perpetuity.
At a recent C24Ltd presentation almost everyone who attended rather uncomfortably agreed that if they lost their data that they would more than likely be out of business within a couple of years. Businesses do recognised the VALUE of data, even if it is on a pure survival level but is that enough in today’s competitive mobile driven marketplace? Perhaps then it’ll come as a surprise to learn that 43% of businesses do nothing more than this, holding the value of their hard earned business data as nothing more than a get out of jail free card in the event of system failures.

In contrast, those companies who value and understand their data have found themselves to be much better off than they were before and are 4.5 times more likely to outperform companies that don’t. It’s this competitive advantage that today’s data offers businesses that are prepared to embrace it. It provides them with an insight that empowers them to make more accurate and informed decisions.

The Wisdom of Crowds


Take Amy, she’s 19 years old has a good circle of friends and carries her smart phone with her everywhere she goes. She checks into shopping malls, restaurants, cinemas and bars tagging friends she’s with. She’ll like places she has a good time in and leave comments on the Facebook walls of restaurants. She logs her travel experiences on Trip Advisor and blogs about her academic experiences on Tumblr, tweeting out her thoughts as she meanders through her day.
Amy will hold her friends’ recommendations and views in high regard, as we all do with valued friends so she’ll take notice when one of them publically recommends a product or service through a social plugin immediately increasing the possibility of Amy visiting the shop or “checking out” that service. She may even follow the smart links, “like” the page and follow the twitter account ensuring that she receives updates and offers direct to her device. And so the circle of influence continues.

Reward for influence.


Some retail brands will use this type of recommendation and offer reward; perhaps a discount on the next visit, some points on a card or an increase in online social kudos in a similar way to Trip Advisor.

Recently I used a well know web comparison site for a car insurance renewal. I was so pleased with the service I sent a tweet to the world hashtagging (#) the service name. 30 minutes later I had a reply direct from the provider expressing their delight and offering me a small reward. The same happened with a leading fast food restaurant, except this time I was voicing my displeasure at the quality of the food I’d been served.
There’s been many a success story about building brand loyalty from using a clearer understanding of your customer’s habits; Tesco’s Dunnhumby perhaps being the most publicised in recent years.
Successfully exploiting the massive amount of data that surrounds us is the key to driving business forward. Understanding what drives your customers (or your competitors customers) to make a purchase, book a table or change their brand will become all the more relevant (and available) as we move to mobile devices. Rewarding customers for influencing their friends will become all the more important as the mobile powered, geo-tagged shopper has the power to influence a highly engaged audience right in their hand.

Thanks to Lee Duffield


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