Did you know the federal government spends over $75B annually on IT? With that number in mind, you can imagine the enormous amount of manpower it takes to choose, customize, build, deploy, and maintain separate instances of applications to run the government’s operations. I cannot imagine a more perfect environment to deploy cloud computing, and it is apparent that the President “gets it” too.

In keeping with his initiative for lowering the costs of running government, the White House this year launched apps.gov, an online repository for federal agencies to explore and purchase cloud-based IT services. So instead of having to individually seek out vendors, government agencies now have a one-stop shop to get most of what they’re looking for. And guess what – salesforce.com and Google are featured vendors.  

In a year of giant bailouts, it’s about time the taxpayer got a break from politicians, except this time it’s technology that’s doing all the heavy lifting.

You know the cloud computing model has hit it big when the second-largest city in the United States makes the switch. Los Angeles had previously been running Novell’s Groupwise (ouch!) and one can imagine that with the economic downturn drastic cost-cutting measures had to be made. This year they made the move to use Gmail for 30,000 city employees along with Google Docs. So instead of wasting IT resources to maintain an email server, they can now deploy those resources to initiatives that provide more value for the city.

The case for cloud computing was so clear that the LA City Council voted unanimously. Microsoft sent their big guns in to try and derail the Google move, but to no avail. Cloud computing has arrived in major fashion, and it’s become quite clear that vendors must either compete in that arena or they are in trouble.

In February, Google made the news somewhat ignominiously when it’s Gmail service was unavailable for several hours, and then again in September. Our own Reid Carlberg’s response to the issue garnered much interest on sites like Reddit and Stumbleupon: “I don’t care.” 

While his subject line was obviously written for effect, his reasoning is absolutely sound:

• Outages of Gmail are extremely rare
• Their support teams often know about a problem before you do
• You don’t need to buy additional maintenance to fix the problem
• Nobody lost any data

We’re pretty sure you’ve heard these themes before from marketing departments espousing the benefits of cloud computing (guilty!), but this is a prime example of why it works so well.

Anyone who has worked in an enterprise email environment managed by Microsoft Exchange, Novell, Lotus or any of the other major players has seen their work email unavailable but at a much higher frequency than Google. The odds of getting information about those outages from your IT was like pulling teeth, because they don’t want egg on their face.

Switching our corporate email to Gmail not only saved us a large amount of money each year, it has provided rock-solid reliability and a level of support that can’t be found anywhere else. Gmail rocks, plain and simple. 

If ever there was a ringing endorsement for the cloud computing model, it’s when the two 800-lb gorillas of computing join the game. What was considered a joke to most just 10 years ago became a very serious battle for cloud supremacy when Microsoft and IBM announced their entrance.

Microsoft is well known in business circles for its Office and server applications, but hasn’t done much in cloud computing. After a few secretive years of development under the code name Red Dog, Microsoft pulled the covers off of the finished product, “Windows Azure.” 

Much of the same can be said of IBM. Big Blue has been historically known for providing mainframes, servers, and data centers for large enterprises to run their businesses on, but didn’t have much in the way of a platform as a service. That’s now changed with IBM’s large push into cloud computing.

Amazon’s Web Services have been getting better and better, but typically by incremental amounts. Up until now, it’s been a slow trickle of improvements to a solid suite of offerings. Cheap storage, cheap computing power, cheap access to PCI compliance, etc.

This new offering however, may truly be a game-changer for their web services division. Amazon’s Virtual Private Cloud lets companies create their own isolated set of EC2 instances and connect them to their own existing IT infrastructure through a VPN connection.

What does all that mumbo-jumbo mean to the business management people? Simple. Now you can augment your IT’s infrastructure without huge capital expenditures. EC2 already runs Windows Server 2008, SQL Server, Oracle Database 11g, IBM DB2, IBM Websphere and many more.

Amazon’s immensely powerful infrastructure is available as a service at prices that will make you wonder if you should bother with your own hardware anymore.

The fastest growing social media site in 2009 was without question Twitter. The notoriety seemed to explode with the Iranian election and ensuing chaos, where reporters were unable to provide accurate, timely information. With the government lockdown, the citizenry got information out to the world through Twitter on their mobile phones. A new dawn of media became legit overnight.

Twitter users rely on the service for more than just timely information, it has become a platform for open conversations around any topic. Company’s products and services have become fair game for both interested prospects and disappointed customers. Instead of calling a sales or customer service line, people are turning to other users for answers on Twitter – leaving companies in the dark. Anyone who has tried to navigate a customer service "dial 1 for X" menu understands why so many are reticent to use them.

Salesforce.com recognized this growing trend and created a truly elegant application that’s easy to use. Salesforce for Twitter allows companies to participate in conversations actively, and track those conversations within salesforce.com, providing a more complete view of their prospects and customers. This added information gives companies an opportunity to better serve these people, and in the channel of their constituent’s choosing.

With this application, if someone expresses interest in your company, you can respond to them on Twitter through salesforce.com. Likewise for customer service situations. I don’t believe there’s such a thing as a 360˚ view of a customer, but having more information on hand certainly allows companies to provide more relevant service.

Check the video demo out below:

In late 2008, Google surprised the tech community by launching their own browser. Rumors swirled about the direction of the company, since this was Google’s first significant foray into building applications that run locally. What could they do in 2009 to top that? How about an entire operating system.

Google Chrome OS is built on the idea that other operating systems were designed in an era where most computing was done offline (Microsoft, Apple, are you listening?). Everybody knows the common complaints of those systems: expensive, heavy resource hogs that get slower and slower the more they’re used. Since many (if not most) common computing situations are now performed online, having a bloated operating system doesn’t always make the most sense.

The implications are clear. Google wants you running their operating system, using their browser, and accessing their online office applications (Google Docs). In keeping with their mantra "don’t be evil," Google claims there are multiple options from competitors to keep the DoJ from getting too keen on anti-trust issues. Google has clearly learned from Microsoft’s example.

Judging by the video below – this major undertaking is well under way, and if history is any indicator it will be highly polished upon full release.

Yes, seriously, Sales Chatter from salesforce.com. If you were at the Dreamforce user’s conference this year, then you already know what this is about. If not, picture an application that combines functionality of Facebook, Twitter, and salesforce.com apps. You can update your status for co-workers to see, and you get a news feed of not only what others are up to, but what’s new in your favorite apps such as Content library updates.

You might think it’s too early to call this one of the biggest stories of 2009, but it is big news from the biggest player in enterprise cloud computing. Just as no one knew just how quickly Twitter would grow, I have a feeling we’re at the same point with Chatter. This could be truly huge.

For a quick video on what’s included and how it works, check out the video below.

Each business morning until the end of the year we’ll be highlighting what we think are the top 9 cloud computing stories that either took place or became more significant in 2009. Be sure to either check back here on the blog or follow us on Twitter @ModelMetricsInc for each update.

At number 9 on our list, cloud computing itself makes it as a top story of 2009. The year that has seen businesses and consumers alike continually stifled by the credit crunch has also seen the dramatic rise and growing acceptance of cloud computing as a legitimate enterprise alternative to more costly on-premise applications.

What was once viewed as pure marketing hype (and famously lampooned by Oracle’s Larry Ellison) is now the fastest growing sector in enterprise technology. In 2009 cloud computing pioneer salesforce.com became a billion dollar company, with no signs of slowing down despite significant economic headwinds.

Independent research firm IDC projects that from 2009 – 2012 the market for cloud computing will triple in size, exploding to US$42B. Their research supports the notion that companies are continually looking to lower their technology costs, and finding those cost reductions with cloud computing technology from salesforce.com, Google, and Amazon Web Services.

Anyone who has ever owned a home knows the feeling of moving into a clean, empty space.  Initially, everything is in order, and everything has a place.  Over time, however, things begin to change… clutter starts to collect, carpets begin to wear, small things start to break, paint starts to peel, etc.  Left its own devices, a home that is not maintained will eventually collapse and become part of the dirt as it is weathered and worn.

Home ownership has a number of striking parallels to CRM custodianship.  Initially, we architect things exactly the way we like them and we load our clean, fresh data into the system so we can begin using it.  Over time, despite our best intentions, the quality of the data starts to diminish…duplicates emerge, incomplete records are entered, new attributes are added without backfilling into existing records, other functional areas make changes to the system that create inconsistency.  As the pattern continues, the usefulness of the system begins to decline because the outputs are unreliable.  Eventually, user adoption is negatively impacted, collaboration is lost, and “the system” is blamed as a failure.

There has been much written on the topic of how much bad data can cost an organization.  I recently did a Google search on the “Cost of bad CRM data” and received almost 2.5 million results.  I have not read them all, but I know that this is a significant issue, but one that can be managed.  The cost can be illustrated by asking questions like:
-    How much time is spent following up on unqualified leads?
-    How much marketing effort is spent marketing to stale contacts?
-    What is the bounce-back rate for campaigns?
-    How much time is spent trying to segment data for marketing?
-    How do you reconcile duplicate records?
-    Can you accurately score your leads?
-    Is there really a single view of the customer?
-    How much “automation” are you able to get from your sales automation tool as result of bad data?

One rule of thumb that we often use to illustrate the cost of bad CRM data is the 1:10:100 rule.  This rule proposes that for every dollar spent on proactive data maintenance would equate to $10 spent to reactively clean up.  To ignore the problem and continuously work around dirty data bumps that number up another factor of ten to $100.  In other words, prevention is key and procrastination is very costly.  Furthermore, we know that, on average, up to 25% of personal information (phone numbers, email addresses, etc) go stale on an annual basis.  Without continual updates, the cost of doing nothing is high.

The good news is that there is a way to keep your cloud based CRM system out of the dirt through a well planned and managed data maintenance strategy.  This critical step can make the difference between long-term CRM success and short-term fanfare. 

Governance
The first step in a data management process is governance.  The role of governance is to define for your organization the standards that will be required of your data.  This includes the creation of business rules and definitions that will be used to cleanse and monitor results.  For example, the governance group shall define:
-    How will data quality be defined?
-    What criteria will be used to define a duplicate contact?
-    What distinguishes a lead from a contact?
-    What level of activity (or inactivity) will be used to define whether a record is stale?
-    What is the strategy to deal with stale records?
-    What defines a complete record?
-    What type of data enrichment processes or technologies will be used?
-    What is an acceptable bounce back rate?
-    How will leads be scored?
-    What are the acceptable thresholds of duplicates as a % of the overall database?
-    How will data be segmented?
-    What is an acceptable rate of incomplete records?
-    What is the threshold for timeliness?
These sample questions provide some direction as to the type of governance policies that need to be in place to align the data strategy with the business goals, set benchmarks for performance, and create standardization.

Analysis/Profiling
Prior to building a house, an architect creates a detailed blueprint of the structure. Unfortunately, most data quality projects don’t take this same approach to building better data. Data profiling helps you determine the current state of your data and enables the discovery of issues.  These issues might be related to structure, completeness, redundancy, relationships, etc. By understanding the strengths and weaknesses of your data, particularly as they relate to the metrics that have been established by the governing body, profiling gives you a starting point for making substantial improvements.

As part of profiling, it is helpful to blueprint your CRM system to identify trends and high level inconsistencies.  The longer the system has been in use, the more likely it is that there are data discrepancies that have gone unnoticed over time.  These issues may range from major architectural problems to invalid pick-list entries or orphaned data element.

The ability to profile data and conduct a through analysis is as much related to the experience and ability of the analyst as it is the tools that are used.  Each situation and strategy requires careful consideration so be cautious of any silver bullets in this area.

Cleansing
Once patterns have been identified, the next step is to prioritize and address the highest impact issues.  On an initial pass, it may be necessary to assess the dependencies that exist between fixes and quantify the value behind addressing individual problems before you dive in.  Every decision has an opportunity cost associated with it, so it makes sense to make sure you are getting the highest value for your efforts.

Data cleansing is a general term merging duplicate records, purging/archiving outdated or invalid data, and generating exception files for those records that require some manual inspection.   Overall, this process is akin to housecleaning in that, the more often you do it, the less painful it is.  If you are the type that procrastinates all year until it is time for Spring cleaning, chances are it takes significant time and energy to get through the entire house.  However, if you develop a disciplined pattern of reviewing and cleansing on an ongoing basis, the process becomes much more manageable (and less disruptive to end users).

I alluded to the fact that some cleanup is manual.  This is a fact that is most commonly seen for de-duplication of data.  Two contacts exist with the same name, address and phone number; which is the “master”?  Sometimes these cases require manual inspection and such an effort should be built into your plan and governance policy.

Integration
One of the best ways to maintain clean data after an initial clean up is a sound integration and automation strategy.  Integration to a back end system helps to define and maintain integrity, uniqueness, and completeness of data.  The fact that some data records are often maintained in multiple systems is useful in establishing checks and balances, but be sure to clearly identify the system of record for all data components.

Common examples of data integration include product master integration or integration with an external marketing automation tool.  Both of these prove to enhance the end-user experience by establishing a single access point for all customer data.

Enrichment
Data enrichment extends data quality and integration by supplementing existing data with additional information from external sources.  The power of web services makes enrichment easy and establishes a synergy between your own organizations data and that of a third party.  For example, D&B, Hoovers and Jigsaw all offer data solutions that intelligently synch with your CRM solution to provide users with IP that they don’t have to source!

Data enrichment represents the best of both worlds when it comes to CRM and web services.  However, too much of a good thing can have a price.  It is the role of the governance team to provide direction to the organization as to which external data sources will be used for enrichment, how they will be used, and who is authorized to use them.  A sound strategy will help establish meaningful customer interactions and prevent abuse of your customers’ information.

Monitoring
Data quality issues are not solved once the system is set up.  Just like owning a home, it is necessary to continually observe changes, identify needs, and prioritize projects.  Maintaining high quality data requires diligence to prevent the atrophy of your solution and your end-user confidence.

The process of monitoring data should be supported by a series of key dashboards that support the data quality metrics of the organization.  In addition to these know metrics, the work to establish new standards should persist as changes to the CRM strategy require.  The house you move into today may not support your needs a few years from now, so it makes sense to keep your eyes open for changes that will impact your strategy, impact your data, and impact your approach to ensuring that your organization can successfully transform that data into information and knowledge.