• The problem can be solved better by a crowd where it can be solved faster
• The open innovation platform provides you access to more experts than any consulting expertise can provide
• Costs can be better managed in an open contest where the solution has a fixed price and timeline

In my last post I outlined the importance of IT making the change from being application-centric to becoming data-centric. What does this mean? And what are the steps IT should take to become data-centric? I will address this in my next series of posts.

The first step is to determine what your business data is. Occasionally, IT has performed business data investigations an exercise to determine which applications contain certain data such as customer data. This was an exercise to identify which applications use and/or change this data. While it is necessary to know these things, this is not the way to become data-centric.

Back to Step 1 for becoming data-centric: To determine what your business data is requires that business data be (1) named; (2) defined; and (3) published. Let's look at these individually:

• Named business data - This seems trivial yet very few organizations have a list of the data used by the business. Naming the data is the first action.

• Defined business data - Defining the data is the second action. This is a descriptive definition for the meaning of each datum and the rigorous specification of the rules to which the datum must adhere for it to have the basic level of integrity, that is satisfy the constraints on the values or the datum that allow it to be considered valid outside of further business contexts.

• Published business data - In order to be data-centric, it is necessary to be able to interact with the universe of data used in the business. This means a business glossary, a directory of business terminology, or another definitive form of published information about the data.

Taking this step will require IT to implement a data discipline and governance program that commits to the published business data as the means to interact with the business community on their data and information usage and needs. Another way to think of this is as defining the semantic layer between the business and the data and information IT delivers to the business.

Using a published business glossary will also change the way in which business requirements are gathered and the way in which business applications are designed and managed. But these are topics for future posts.

The role of analytics in sports isn't a particularly new story. Back in 2003, Michael Lewis - in his book Moneyball - chronicled how the use of analytics helped baseball's Oakland Athletics win a World Series.  The story became so popular that it was made into an Academy Award nominated film in 2011.  While the application of analytics in football has been less publicized, one of the biggest success stories of analytics in professional football will be on display this weekend at the Super Bowl: The New England Patriots.

Before delving into analytics, two quick caveats. First, before any New York Giants fans (or Patriots haters) send any nasty emails, this post isn't an endorsement of any particular football team, but rather an attempt to examine the benefits of analytics through the lens of sports.  Second... well, go Pats!

Setting the Stage for Super Bowl Analytics

In the 1990s, the National Football League introduced two significant changes to the league: free agency and the salary cap. Free agency allowed players, once their contracts with one team had expired, to sign with another team.  The salary cap essentially limited the amount of money a team could spend on its players. The intention, and net effect, was to create parity among all the teams in the league.  In other words, in a hyper-competitive industry, all participants had relatively equal access to talent and resources.

Yet within this environment of parity, the New England Patriots have appeared in (six, counting this weekend's game) and won (three) more Super Bowls than any other franchise over the same period. Many have attributed this success, all other things being equal, to the use of analytics by the Patriots. Here are a few of the ways head coach Bill Belichick and the Patriots have been able to use analytics for competitive advantage.

Understanding the Value of Resources through Analytics

In 2000, the Patriots drafted a relatively unknown quarterback named Tom Brady in the sixth round, the 199^th player selected overall. The Patriots current roster features 18 players who weren't drafted by the NFL when they left college. In case you don't follow football, Tom Brady has gone on to become one of the greatest players of all time (according to NFL Network), and those 18 undrafted players are now playing for football's grand prize.  While all teams have access to a wealth of data on these players, the Patriots have the ability to look at that data in a unique way, and fit it into their overall system. In other words, they understand the processes that drive success for their organization and have been able to quantify and evaluate the available resources that will most positively impact those processes.

Applying Analytics to Structured Processes

The rules for American football are fairly well established: there are a fixed number of players on each side (11), and a finite number of ways for one to advance the ball (pass, run or kick), yet teams are constantly finding novel ways to combine how those eleven players advance the ball on each play. The Patriots have been known to take the application of analytics in play calling to new heights, allowing them to select plays based on sound information given a myriad of factors in a given situation rather than relying on "conventional wisdom." Of course, this use of analytics doesn't always work out, but given that the Patriots have the highest winning percentage in the NFL for the past decade, this application of analytics has seemed to work for them.

Creating Long Term Value through Analytics

The Patriots are one of the most valuable franchises in the NFL according to Forbes. And while the team ranks third for overall value behind the Dallas Cowboys and the Washington Redskins, it's seen a higher increase in value (245%) over the past decade than either.  Winning certainly helps, but many attribute the Patriots' increase in value to the emphasis the team places on fan satisfaction analysis. The Patriots organization uses analytics to determine and improve the "total fan experience." They even go so far as hiring 20-25 people for each home game to make quantitative measurements of stadium food, parking, personnel and bathroom cleanliness.  Many people credit the Patriots for their "attention to detail." I think what sets them apart, however, is their analytics of the details.

What Does it All Mean?

Many organizations, in any industry, wish they were as successful as the New England Patriots.  Are analytics the only factor that has lead to their success? Of course not. But any organization looking to gain competitive advantage through analytics can benefit from the Patriots example. Companies can use analytics to better understand their competitive landscape and evaluate available resources; they can apply analytics to defined processes for improved performance; and they certainly can analyze customer information for increased loyalty. Will the Patriots winning the Super Bowl help to validate the value of analytics? No... but it sure would be nice.

By Adrian Alleyne, Patriots Fan and Director of Market Research

© 2012, DecisionPath Consulting

Last week, I posted “Can Organizations Get Business Analytics Strategy Right?” which looked at a recent Gartner report that predicted that more than 70% of companies wouldn’t be able to successfully connect analytics and business strategy.

Gartner followed up this report with their 2012 CIO survey. One of the interesting findings was that business intelligence/business analytics jumped back up to the number one priority for CIOs after slipping to 5th place in 2011.

There are a number of reasons why this shift occurred: virtualization projects have wrapped up, or 2011 projects were more focused on cost savings vs. growth, for example.  We thought it would be amusing to take a look at how the shift took place in the following video:

While this is a somewhat tongue in cheek look at the role analytics is playing for CIOs, and for that matter organizations in general, it does underscore a theme that the two Gartner reports keep coming back to: business analytics has the potential to play a major role in supporting and shaping business strategy.

Within the past week two very different performance management vendors have received millions of dollars of outside investment. I say very different because one is generating excitement due to its application of the latest technology, and the other is getting attention because of its new approach to solving a long standing business challenge. The companies are Tidemark and XLerant. You can read what we have recently written about each of them here and here. They are both good companies with a solid vision and very experienced teams. Venture capital guys tend to like to get in on the next big thing. Performance management is an established big thing so why the investments now? For one, they must expect continued growth. In addition, each of these companies does have a 'next big thing' element. Tidemark is wedding the proven principles of performance management to the next generation of technology. They are still relatively early stage, but the potential is huge. In the case of XLerant they are approaching the crowded, but still in high demand, budgeting solutions area from a new angle. There certainly is room for both of these companies to succeed. These investments also bode well for the established performance management vendors as it is just one more validation that performance management is an important and growing area. In particular Adaptive Planning and Host Analytics, pioneers in bringing the latest technology to performance management, should see interest in their solutions increase as the investment and related coverage of Tidemark may help more companies recognize the value of this approach.

XLerant received 3 million, and Tidemark 24 million.

This blog will investigate putting data first rather than having business data be treated as exclusive to applications. While functionality is important, software functionality is based on consistent operations on data or groups of data. The application-centric view holds this consistency within the boundaries of one or more, but not all, applications. The problems that arise from application-centric IT are well known: disparate data in data silos, making it difficult to share data across applications; inconsistent and redundant data; and the need to transform and integrate data for enterprise reporting and analytics.

A data-centric view maintains that any consistent operations on data or groups of data must hold for all applications, eliminating data transformations and making it easy to share data across applications. Putting data first means we ensure the data is what we want it to be for the business and all its business uses before we build any functionality. The consistent operations become data rules that are employed whenever an operation, such as data entry or reporting, occurs. Thus software functionality is no more that the execution of pre-defined data rules combined with usage rules for the user interface, such as for a web page, report, or query, a function is performing.

The benefits of this are clear: data-centric data is standardized and correct across all applications and uses; there is easy sharing of data across applications; there is little, if any, need to transform or change data before it can be used with other data; data rules are known and applied consistently across all uses of data; all data is ready to be used for new reports, business uses, and software functionality; and, most importantly, new software functionality is purely incremental, comprised of new data, new data rules, and usage rules for new user interface components that build upon existing data, data rules, and usage rules without replicating, duplicating, or redoing any data or data rule.

While becoming data-centric may sound like it is an ideal that is impossible to achieve, we are at a time when technology exists to make this possible. I will explore these in future articles and blog posts. The challenge for IT is to move from its current application-centric environment where all old applications are legacy silos, and that any new application immediately becomes, to a data-centric environment where data, rules, and usage are unified, consistent, and always good-to-go. We know the problems of application-centric IT cannot be overcome easily--we live with them every day. It's time to make IT data-centric.

Can Organizations Get Analytics Strategy Right?

In a new report released by Gartner last week, the most salient finding was that more than 70% of BI initiatives will consist of analytics metrics that lack synchronicity with overarching business strategy.  According to the report: "Organizations often develop and deploy hindsight-oriented reports and/or query applications focusing on metrics that users may find interesting, but they don't represent the operational or strategic controls used to facilitate business performance." The report's author, Andreas Bitterer, goes on to say "The immediate future of the BI landscape is one of a disconnect between marketing hype about pressing challenges on the one hand and reality on the other."

I'm not as quick to castigate the marketing function of major BI vendors for building the hype around BI technology; some might argue that many analysts have been equally enamored with what's next on the horizon for BI technology rather than on the business problems BI can help solve. 

The Real Disconnect Between Business Analytics and Business Process

The disconnect Gartner talks about is something we've seen for with our clients for years.  What's interesting is that the report predicts that this disconnect will be widespread (over 70%) for the foreseeable future. We've been evangelists and advocates for making the connection between business analytics and business for bottom-line impact for close to a decade, yet the issue persists.

The real disconnect comes the perception that analytics is primarily a technology tool from business users. Our own research shows that many business users think they understand and have adequate analytics to support their core business processes; while nearly three-quarters of business users we surveyed indicate that they use traditional reporting, only 40% report using advanced or predictive analytics. Another example of this disconnect is the fact that these business users prioritize other business initiatives over analytics.  In other words, they aren't able to connect BI with true business value.

Making the Business Analytics to Business Process Connection

I suppose the good news for any organization looking to leverage analytics to improve business performance is that most of their peers aren't doing it...yet. But making the connection doesn't happen overnight.  It takes an assessment of the organization's state of readiness to leverage business analytics.  Is there a culture around process improvement and analytically driven decision making?  Is there a partnership between IT and business (e.g. is the CIO business savvy, and are departmental executives - CFO, COO, etc... - technically savvy)? Is the IT and analytics infrastructure in place to allow the organization to leverage analytics. 

If the answer is no for any of the above, then some remediation has to occur to even have a chance to move out of Gartner's "misaligned" 70%. To then move into the ranks of the minority of companies that use analytics for competitive advantage, an organization must then look at analytics from the top down, knowing the answers to some basic business questions:

1. What competitive and external factors influence my business?
2. What business strategy do I employ to compete in this environment?
3. What business processes drive this business strategy?
4. How do I measure the success of these business processes?

With the answers to these questions in place, an organization's analytics team (and by team, I mean a collaboration between IT and line of business leadership) can then start to look at opportunities where analytics can improve how these business processes are measured. This in turn allows one to do things like provide better root cause analysis and predictive analytics.

So...Can Organizations Get Analytics Strategy Right?

While I agree with Bitterer's observation about where companies are right now in terms of business and analytics alignment, I'm not sure that I'd agree that the majority wouldn't be able to get there by 2014. Organizations just need to take the time to establish the process of understanding their readiness to leverage analytics, and then determine the opportunities that business analytics can offer.

By Adrian Alleyne, Director of Market Research
© DecisionPath Consulting, 2012