Tuesday, December 14, 2010

The Kindle effect in BI

With the popularity of eBooks in multiple formats, offered by multiple vendors, we find ourselves in a world where libraries are literally becoming obsolete. When you can access and read any book that has been published from your tablet device, there is no reason to ever open a paper book again, is there? As this blogger discovered, sometimes either newer books or older books (whose rights are still retained by the authors) are not available in digital format yet. If you browse through the bookseller s review section, you will find that many times when a new book is released and there is no “eBook” version, people will rate the item poorly, independently of how good the book might or not be. While this is heavily criticized by many of the book loyal followers, I found it true that it disrupts the reading experience.
In business, as in our professional lives, it is amazing to notice that what we take for granted today did not even exist a few years back, but once the new technology is introduced it becomes permanent part of our lives to the point that we no longer enjoy the experience of flipping pages in a book and start complaining about the dead weight of paper and its effects in the environment. We can rationalize it anyway we want, but when you really like look at it is all about convenience, what do we get for the effort we put in. As an international road warrior it becomes a matter of practical survival, how many 800 pages books can you carry on a flight from Frankfurt to Bangalore and still make it practical to move all that weight around?
I found out that the Business Intelligence world behaves in a very similar fashion; the user experience often dictates how much value the business users derive out of the information. The more intuitive and responsive the user interface becomes the more that I find people using their reports and analytical applications as part of their daily routine. Think about it, how many reports can a manager print and still find the relevant data points that he/she needs to make a business decision? In fact, the kindle effect is becoming so prevalent in BI that many Fortune 500 organizations have invested heavily in mobile applications that enable their mangers real time access to the information through the blackberries, iPhones, iPads and other smart devices. The key, again, becomes simplicity and speed to analyze all the organizational information you need in a few seconds. However, If you company is thinking about implementing similar functionality, just be careful, make sure that once you embark in the journey you travel all the way through the most remote destination (or useful piece of data in the organization). Remember there is nothing more frustrating that having a mobile platform that cannot be used to analyze the latest release of the data, it will just irritate your users, like a publisher with a no kindle version.

Wednesday, November 10, 2010

How to leverage off-shore effectively in BI assignments

If you are reading this blog, you or your company are probably considering leveraging off-shore for your BI projects and you are still trying to decide if this is a good idea or not. You probably have heard several horror stories of companies who tried and failed miserably. However, did you know that for every horror story there is out there, there is an equal success story that balances things out. So, if leveraging off-shore is as likely to sink a project as it is to save it, what are the things that we need to do differently to ensure success?
I am sure there are consultants out there making a living on this. In fact a few weeks back a friend of mine asked me to co-author a book on this subject. Having spent over a decade on both sides of the fence, I can honestly said that while all vendors have similar technical capabilities the difference lies on the operating model and how you interact with your account team.
Let us take a deep dive in the subject and explore what is an operating model and why it is important. An operating model is how the service provider will organize its people to provide specific capabilities to a client. For example: While the vendor team might be internally organized in technology capabilities, geographic location or business domains, the service provider might decide to propose creating a single team seeded with people from different internal COEs to address the requirements of a particular project. The most important aspect of an operating model is to define how people will join, participate and transition out of a project; without the right structure, a client might spend weeks with a particular set of consultants getting them up to speed in their applications just to see them leave at the end of a project because of a short gap in getting the next project approved. Also important is the time it takes to secure resources once a project is approved, if the vendor does not have a pool of resources committed to your account, it will probably take a longer timeframe to identify the right talent, thus impacting the project timelines and potential commitments to the business.
So, if we define the right operating model why do we even need to bother about who the account team is and how we interact with them? At the end of day, independently of the vendor capabilities and how good (or bad) their power point presentations are, business is done among people. It boils to the fundamental question if you trust the people who are across the table and believe that they can partner with you to help you achieve your goals. Never underestimate what a good client representative can do, he/she can exercise significant influence within their organization to represent your interests and more importantly he/she can align the organization resources to achieve your required outcome.
Last but not least, try to visit the outsourced team at their base location (whereever in the world this might be). I recently came from a trip where I had the opportunity to witness firsthand the impact that a CIO created when addressing the outsourced organization directly; after the CIO addressed the team they became energized and behaved passionately about their work as they understood the value the client placed on it and they knew who the client was.

Sunday, August 29, 2010

Has Business Intelligence become a commodity?

Many of us in the consulting field will probably answer no, giving examples of multiple projects that have failed because people did not know how to properly execute them. From an industry perspective however, the Fortune 500 CXOs who see IT as an expense could not care less who or how they BI projects are being executed as long as the cost is right. What started as a differentiated capability to provide business the "extra edge" over the competition evolved into one more of the IT tools that need to be maintained, ideally at the lowest cost.
So, to put it in Austin Power’s terms, has BI lost its “mojo”?
All the Fortune 500 companies that I have had the opportunity to visit have some kind of BI tool, many of them have multiple tools and probably some of them have all the commercial BI tools. The BI team might range in size from a few individuals working on-site to full floors of analysts and developers in India but most want to reduce it – both in size and in cost. In contrast, very few companies have initiatives to get more out of their BI investment. However those that truly believe in BI are using it to drive their business transformation.
How is this possible? On one hand we seemed to have reached a plateau where everybody has BI capabilities and it is looking to reduce the cost. On the other side of the spectrum, we seem to have a few outliers that don’t believe they have reached the maximum potential out of their BI investment and are pushing the organization to continue to re-invent itself based on information.
In my experience, what differentiates these leading edge companies are not the BI tools, or their budget but rather their vision. In particular there is a champion in the organization who is driving change through BI. This visionary can articulate the value of the information and provide the business with business driven solutions that can improve performance (both revenue and profitability) by suggesting very concrete and actionable ideas that are the result of properly measuring and analyzing the information.
So, while the tools might be a commodity, how you use them is certainly not. The key to success is not to have the best tool technologies, but rather have the right mindset and business experience to create value beyond IT. As Austin Power’s realized in his movie, the “mojo” is always within, it is just a matter of knowing how to tap into it.

Monday, July 26, 2010

The role of Master Data Management and Business Intelligence in the Business Transformation

The value of a transformation initiative is not in the transformation itself, but on how the transformation will enable the organization to get ahead of the competition in a changing market place. A transformation initiative connects organizational silos and empowers them to collaborate and share information, resulting in a better and more holistic appreciation of the market challenges and the establishment of an integrated platform which facilitates a faster response than the competition. Many of the transformations initiatives that we are seeing in the market today come as a result of mergers and acquisitions; these companies are starting to realize that in order to capitalize in the synergies that mergers and acquisitions can provide the firms involved have to be integrated in soul and body (culture and systems). In order to achieve this integration new processes have to be established, which are usually enabled by the implementation of new tools. The introduction of new tools and process requires the organization to experience change, change that in order to be successful needs to be driven by a vision; a vision of what the new organization wants to achieve. This vision will set the direction of the transformation and help align everyone’s effort to achieve the goals; goals that will be achieved incrementally over time through release waves. Each release wave will help the organization to manage its assets better; perhaps the most important of these assets being the data, which becomes the blood of the transformation, helping connect the legacy systems with the new set of tools.

II. Master Data Management

The data will be shared across all locations, business areas and corporate entities bringing them together as part of the value chain. However, as with humans having different blood types (A+-, AB+-, O+-, etc), organizations also have different ways of creating, interpreting and analyzing the data. In the legacy world, it did not matter that two organizations used fields with similar names like Customer differently (e.g. one business area would use this field for the customer name, while another one would use it for customer ID), as most systems worked independently and if information sharing was required, workarounds were built to allow these two independent systems to exchange limited information. However, as part of the transformation initiative, these two organizations are expected to use the field the same way, consistently from beginning to end. A new process is established clearly specifying what information should be in this field. Imagine the surprise of the transformation architects, when they discover the field is being used inconsistently across the board and worse, when this field is being fed to the downstream applications which are constantly failing because of the bad quality of the data. Because their application modules are not working properly, there is a need to revert back to their old legacy systems which creates the need for additional data interfaces and synchronization which in turn creates even more data quality problems in the new system. What is the root cause? Is it the new tools, the process or perhaps training? The answer is all and none, what this transformation needs is a Master Data Management strategy that defines the critical fields up-front and establishes the right practices to populate this information, including the use of checkpoints, data profiling, and most importantly work-flow tools that allow for an audit log on the data changes (Who, when and from where). Having a centralized governance group that is empowered to designate single owners of the data across the organization will quickly address the compliance issues as people will have a better understanding on how their actions will directly impact downstream application modules and more importantly will provide a channel for them to suggest alternate solutions and possible improvements to the process. Master Data Management becomes a key transformation enabler that goes beyond implementing a technical solution to establish a holistic approach on how data is seen in the organization, effectively changing the data/blood Type to O- allowing for universal compatibility.

III. Business Intelligence

Once blood/data is flowing again properly through the body/organization, the transformation initiative can continue. A transformation is not complete, until it enables the company to deliver additional value to its customers and to itself. While having all the entities, business areas and locations using the same systems and sharing the same definitions of the data provides some operational efficiency, the true value of the transformation is in how the organization will convert the data into insights that turn into competitive advantages in the market. Business Intelligence will become an integral part of the transformation by providing the know-how on how to make that data actionable. Business Intelligence will enable the organization to analyze the data to form a holistic view of the market and indentify opportunities for new products, better promotions, better allocation and distribution, and perhaps bundles of items that provide value added to its customers. The proper Business Intelligence strategy will enable the organization to more close align with the business model of its business partners, creating win/win scenarios where the company can solidify or consolidate their leadership for the segments and brands they compete with. Business Intelligence provides the capabilities to understand the motivations and drivers of the consumers and can point out how to make internal changes that will drive consumption and thus additional revenue: such as localized or improved packaging. Having the right Business Intelligence strategy is thus key for success of any transformation initiative as companies deploy it to free the power of data.

Tuesday, July 6, 2010

Beyond Self Service BI

In the past few years there have been significant changes in the BI Industry: acquisitions, consolidation and evolution of graphical capabilities leading to a paradigm change on how the BI tools are being leveraged in the market today. This paradigm change has provided many companies with the opportunity to introduce a Self Service business intelligence strategy, albeit for different reasons. Some companies wanted to try the Self Service model to give a fresh approach to BI, as previous attempts of building an information driven culture had failed, and the new BI manager was looking for a way to make their mark and re-engage the business stakeholders: The Do-Overs. Other companies were trying to get rid of the “problem”, it was very expensive for IT to keep responding to all the changes the business folks needed to make; it would be a lot easier (and cheaper for IT) if they were able to do those reports by themselves: The Cost Cutters. There were some national and global companies which wanted to appease complaints that they were not nimble enough and that IT was not satisfying the local reporting requirements, as they were concentrated only on corporate reporting: The Peace Keepers. It was really a very small group of organizations, usually lead by a visionary business leader, which were looking at BI Self Service as a way to empower the organization to make the right decisions across all levels: The Next Gen. This article will explore what kind of results each of these groups of companies achieved in their journey to Self Service BI and shed some light on the different levers Business Intelligence professionals can pull in their own organizations to influence their journey towards Self Service BI. These four companies groups are depicted in the diagram below.

The Do-Overs
Companies in this group want to re-do their BI implementation because something did not go well in the past; they are trying to run from their mistakes and use the excuse of implementing a new tool or technology to do over their failed implementations. They want to implement Self Service BI because they think it would give the new toolset they are planning to implement a fresh approach and make it feel differently to the business stakeholders. You might be wondering, does this work? The answer is absolutely Yes, Self Service BI can actually be used to position a whole new different paradigm for BI. The problem is not Self Service BI, or the new toolset, but rather the people in these companies are so worried about not repeating the same mistakes from they predecessors that they do not realize that Self Service BI can only be implemented under the proper BI ecosystem: the technology platform is stable, the data quality is good and the business users want to learn how to pull the information themselves. Starting from the top outlining roles, responsibilities and tool permissions or capabilities will get the business people excited at first, but invariably when the business users realize that the metrics they need are not well defined, the data is incorrect and the system is very slow, the new BI program looses all credibility and it is time to Do-Over again.

The Cost Cutters
It is fair for any IT department to look for ways to decrease cost and optimize resources. Given the economy today, this is something that many CIOs will be expected to do this year. However, like when doing pruning, you need to know where to cut and how much to cut. Positioning Self Service BI might help lower IT costs in the long run, but it most likely will demand a heavy investment in time & resources upfront that these companies fail or refuse to plan for. If the business users are habituated to going to IT for any single report change, no matter how small it is, it becomes very difficult to break this dependency. In most companies with this situation, business sees IT as a black box of tremendous complexity with an army of people that work behind the scenes to make things work. They see IT as being at a different plane of existence where they are not worthy of understanding what happens there. So imagine their surprise when they get to work one day and find an email in the magic box (aka computer) telling them that from now on they will be responsible for creating their own reports and managing their own changes. It is like telling the mortals that the gods no longer consider them worthy of fire and now they will have to live in the dark. Following this analogy, if the users have never seen how IT creates and modifies reports, they do not know of SQL or MDX, the users most likely will never be able to figure out how to leverage the BI Self Service capabilities on their own. Many companies have spent millions in infrastructure, licenses and training just to find out six months later that nobody is using the new Self Service system and the business has hired a bunch of data wizards that are using a combination of Excel, Access and the old BI system to run the company. Needless to say that in these scenarios the savings never materialized and the company who was trying to save money, ended-up spending even more for a not so cheap and even less Self Service BI solution.

The Peace Keepers
The people in charge of the BI strategy strongly believe that they are implementing Self Service BI for all the good reasons: they want the business users in each of the local markets to be able to produce their own reporting that better allows each market to respond to unique local challenges. They are also aware of the pressures that the local markets are putting into corporate for defining a centralized view of the world, which does not enable local reporting. These BI managers blindly trust that if everyone is given the capabilities to customize their own view of the world they will not challenge the corporate definitions as they can use the Self Service capabilities to define unique reporting hierarchies and structures for their particular market’s use. In the long run, what ends-up happening in these situations is that each market creates a parallel structure to the official, corporate one and gradually the local reporting needs keeps growing more and more apart from corporate. A few years pass and the “guy” who knew how the local reporting systems were set-up leaves the company and IT is asked to take over these “applications”. However, given that the corporate structures and view of the data is now radically different, IT has no clue on how to support these local reports. Then people suddenly realize that letting each of the markets implement their local reporting needs on their own is not a good idea, and they should centralize the generation of reports. A business case is built with the potential of millions of dollars in savings, but only if the markets are willing to relinquish control back to a centralized entity. At this point the same battle that they were trying to prevent in the beginning is about to break loose with no clear winner in sight.

The Next Gen
No, these are not the companies of the future, but they could as well be. These are the companies that see the implementation of BI Self Service as the next generation of Business Intelligence, not because the previous generation failed, but because their predecessors established a solid foundation with the right metric definitions, excellent data quality and a solid technical platform. The Self Service BI culture is driven by an enthusiastic business sponsor who is pushing the use of information to take decisions directly from the top. These organizations continuously organize trainings and information sessions to share best practices and let the users from different business areas connect among themselves building communities around the reporting applications. A company in this position has probably failed implementing BI before and they have realized that the problem was not on the tools but rather on key foundation blocks (Metric definitions, data quality and proper infrastructure) that were not present or were incomplete.

Never underestimate the commitment that BI Self Service requires. Most of companies that have implemented Self Service BI successfully experienced drawbacks early in their journeys that provided critical insights and learnings to course correct. Let us take the example of a retailer that started this journey in the early 2000’s. This particular retailer already had a solid BI program enabled by an in-house developed tool, and had established solid metric definition and data quality principles. Business users had limited Self Service exposure as they could choose any combination of attributes from a limited product, location and time selectors. While the capabilities enabled some degree of self service, most of the users had predefined reports which they looked at every day/week/month and seldom ventured in ad-hoc capabilities like “adding new stores” or “categories” to their reports.
Given the changing competitive landscape, this retailer decided to revamp their business intelligence infrastructure and bring market leader tools, the investment was in the millions of dollars and many stakeholders in the organization saw it a as a waste. “We have all the reports that we need” they used to say. The first release was not successful, in a high profile meeting the new set of tools performed slower than the in-house developed application and the information provided was incorrect. That meeting almost killed the program before someone realized that the problem was in a piece of equipment that had been wired incorrectly. This setback instead of demoralizing the BI team, pushed it try even harder. The BI organization was divided into two teams, one that would focus on the technical issues and one that would focus on how to get alignment and buy-in from the business users. This strong teaming, coupled with a new approach on Self Service BI helped the BI organization to generate enough buzz with the business stakeholders to give it another try.
After only six months, the business users were impressed with the capabilities of the new tool, not only could they select any product, location or time period they wanted but they had access to new metrics, and functionality that never before any of them had seen. For example, the new platform provided Market Basket reports On-demand, where the users could specify a driver product and the system would identify all the items that had some affinity. The business users now had the capability to run full ad-hoc reports, selecting the KPIs they wanted to see in real time while they were negotiating with vendors and suppliers. The business users could compare the performance of a particular product against a competing product, or look at its performance during different time period when the item used to be on sale, promotion or temporary price reduction.
The level of excitement grew daily as the BI business team had highly talented individuals walking the halls of the merchandising, pricing, marketing and supply chain organizations daily, helping the business users to leverage the new Self Service capabilities. A key element for success was the establishment of a monthly breakfast where one of the business users presented the results that they had achieved leveraging Self Service BI to their colleagues and got recognized by one of the Senior Vice-presidents of the company for their contributions.
In just a few months, a project which very few people believed-in, had suddenly jumped to the spot light, providing the company with a tremendous competitive advantage. Years went by and the popularity of the system kept growing, store users started asking for having access to the Self Service capabilities and they were willing and able to take all the necessary training to properly use the system. The company enjoyed a period of incredible growth fueled by business innovation initiatives that would not have been possible without the implementation of Self Service BI.

Wednesday, June 2, 2010

How many metrics do you need to tame a wild Enterprise?

Dear Readers,
It is summer and as you can see by the title on this blog I am in Dallas today, daring to compare business intelligence to a rodeo, where the cattle are the different company divisions and the lariats the metrics that are used to report on performance.
In one of my previous postings I discussed the feasibility of having a single metric - the silver bullet - to identify the right candidates to be staffed in business intelligence projects, however can we find another golden bullet to manage performance in the Enterprise?
This quest has given birth to numerous discussions within the Enterprise Performance Management experts, leading to the construction of frameworks such as the "Balanced Scorecard" and the "Performance Prism" among others. However after talking to numerous CPOs (Chief Performance Officers) in top Fortune 500 organizations they are still struggling to "tame their Enterprise” so to speak. Measuring performance in a large organization becomes a real challenge, as different leaders define achieving success in different ways, thus seeing performance through a different lenses (or prism) and making it difficult to agree on what to pursue, forget about how to measure.
Life goes on, the stocks markets open and close and some companies win and some other loose. So this encourages the debate, can we define performance as a company stock going up in the market? As always the answer is not as clear as we would it like to be, the stock price can indeed be a short term performance metric that is visible and well understood to the organization. However it is like trying to laze a calve with a very wide lariat, yes you might succeed in getting the lariat on the calve, but can you make the calve follow you? Most likely the calve will get through and you will end up empty handed.
So, if stock price is not THE metric, what then? Is there any hope to find the silver metric that I can report to my CFO to make all my problems go away?
Imagine that you are a cowboy or cowgirl and you are about to compete in the steer wrestling event. In this event you have to jump from your horse onto a running “Corriente steer” and wrestle it to the ground. Could you succeed? As dangerous and difficult as this challenge sounds, many “vaqueros/as” are able to successfully accomplish this task continuously in every rodeo. The secret lies in knowing how to handle your cattle, and working together with your horse to jump on the steer at the right time, avoiding the horns.
So I pose the question back to you, do you know your cattle well and can you work together with the right horse to tame your wild Enterprise?
Have a great summer,

Saturday, May 29, 2010

Is experience years the silver bullet metric in Business Intelligence?

Dear readers,
In this holiday weekend, in the middle of trying to catch-up with some backlog work, I stumbled into a random LinkedIn page. What really caught my eye was the summary, where it was stated that the person had over 20 years of experience. Something immediately tingled in my mind telling me that there was something odd about this statement. Immediately my conscious mind tried to calculate how old was this person based on the profile’s picture. My estimate was no more than 30, which would put the start of the professional experience even before the teenager years. Sure enough, when I read the profile in more detail, it was clearly disclosed that this person started a professional career helping on the family business from childhood.
My current job requires me to interview at least a dozen people every week; many of them, like this profile in LinkedIn, write in their resumes that they have long years of experience in a particular domain or using particular tools, but they cannot provide a solution to basic problems that Business Intelligence professionals face when implementing projects. So, I pose the question: what makes experience years a valuable metric in Business Intelligence? Does it even make sense? Well, according to Wall Street it does, you cannot imagine how many annual reports quantify the experience of management in experience years. In fact, many organizations use experience years as the core way of defining the pay grades across all levels – the silver bullet metric that can be applied equally across all departments.
However, before you start getting the dust of your boy/girl scouts patches to add them to your LinkedIn profile, ask yourself if this “personal” experience is indeed relevant experience that will help you increase your productivity in your current role, or better yet, enable you to move to a higher role. After all, isn’t this the expected outcome of being "Intelligent in Business"?
Have a great memorial holiday weekend,

Monday, May 24, 2010

How I made it from Newark to Dallas in 13.5 hours and why should BI matter to American Airlines

Dear readers,
On the morning of Friday, May 14 I was boarding American Airlines 1971 unaware that a 3 hour flight would become on the longest domestic trips in my consulting career. Everything was going well, I had avoided the early morning flight so I could enjoy a few more hours of sleep, I had completed my morning work calls and the plane had internet connectivity. Everything was set to enjoy a good, comfortable and productive trip in time to make it to my client meetings at 1:00pm CST.
I was aware that there was some potential bad weather coming to Dallas, both everything looked clear in the radars and nobody expected any problems to get to Dallas. We should have known better.
According to my fellow passengers in first class, the pilot of the plane had determined a minor malfunction with some of the control lights but a mechanic signed-off on it and we were on our way to Dallas.
About 10 minutes prior to landing, the pilot was notified that the airport had been closed because of bad weather, given that we had only 1 hour of fuel left and air traffic control could not guarantee that the airport would open before then the pilot directed the aircraft to Shreveport, Louisiana. While annoyed, I have been in this situation many times before; it was always a matter a refueling and wait for the airport to reopen for us to be on our way to DFW. However, this time things would play a little different for me and my fellow passengers. When we landed in Shreveport, there were six other planes ahead of us waiting to be refueled, which meant at least 1 hour wait to be serviced. Further, on the ground the great GOGO wireless does not work and the Shreveport airport does not have 3G coverage from T-mobile. I knew that I was going to miss my 1:00pm CST meeting so I called to cancel, however little I knew I was going to miss all my appointments for the day, including reading to my kids before they go to bed...
Back on the ground on Shreveport the pilot announced that they would let anyone who requested off the plane, being optimistic about the situation I declined this offer and kept working on my laptop. About 30 minutes later, the pilot announced that they could not take off again until a mechanic signed-off on the light problem (same issue that the plane had in Newark). However there was no mechanic available in Shreveport and someone had to fly in from Dallas. All the Dallas-Shreveport-Dallas flights were grounded; because of bad weather (service in this route is through old propeller planes). So, citing the new bill regulations the pilot made the decision to have everyone off the plane. Because the Shreveport airport was not equipped to handle MD80s, deplaning would be through the back engine door rather than using a Jetbridge. This maneuver had given the priority of deplaning first to people who were sited in the very last rows of the plan, while passengers in first class were the last ones to deplane. After 30 minutes, I finally made it to the terminal where long lines of people waited everywhere. American Airlines had 4 employees staffing the counters at the airport, clearly insufficient to handle the additional 120+ passengers who just had deplaned and were looking for options to get to their final destinations. After making a line for 45 minutes to buy sandwich, I came back to the America airlines counter where there were still 20 people ahead of me. After another 45 minutes, they announced that they would get buses to get us to Dallas, given that it was not safe to return to the plane. 15 minutes after making this announce the plane takes-off back to Dallas with half of the bags. Nobody knew what hit us, but for the next three hours we patiently waited for the buses to come. People who had been lucky were given a seat on the last flight from Shreveport to Dallas that Friday; I was one of the lucky ones. Until they announced that flight was going to be cancelled and we had the option of staying the night in Shreveport or running downstairs to catch the buses. People who were able chose to run to catch the bus and then start our 4 hour drive back to DFW. American airlines clearly did care for the welfare of their passengers as they ordered the bus to stop half way there at a Burger King so people could buy then own dinner, how thoughtful of them.
After a high cholesterol dinner, we got back on the way and we had some close encounters on the road because of the winds on the ground, I got three inches away from an 18 wheeler which carried healthy food. Not the kind of gastronomic experience I could have wished for.
Finally at 11:00pm, 13.5 hours after leaving Newark we arrived into Dallas. The driver did not even ask where people had park, if anyone, they took us straight to Terminal A, so I spend another 20 minutes commuting to my car in terminal C. By the time I got home, everybody was slept and it was clear that I had not only missed my business appointments but also playing with my kids.
So, why should Business Intelligence matter to American Airlines?
If you have people who spent an average of 50k per year on airfares, I think it would be worth it to go the extra mile for them when something like this happens. If American Airlines had had better forecasting capabilities they could have loaded the plane with more fuel and make sure the maintenance light was fixed in Newark rather than just signing off on the problem to the Dallas crew. Further you want to make the experience as pleasant as possible; I am sure few of us who were in that flight will ever forget the experience. However American Airlines quickly forgot about it, when I called last week to complain about this travel disruption and request an upgrade on my flight to Dallas from Raleigh , the lady at the executive desk told me very politely that she was sorry for the bad experience but there was nothing she could do, that these were after all unrelated events (never forget that the flight from Raleigh to Dallas was an hour and a half late) and I needed to send a letter independently about each flight to customer service. So, while American Airlines was first with the customer loyalty program, they definitively could use a better Business Intelligence system to truly get to know their customers before someone else will…

Monday, April 19, 2010

The role of the business intelligence analyst and Datamodeling

Dear Readers,

What is the role of a business intelligence analyst?

Many of you will say, he/she is responsible for making sure the solution meets the user expectations, but isn't the role of the entire Business Intelligence team?

Ok, so let's say that the Business Analysts is then responsible for documenting the business requirements. If the role is only documentation, why do we need a business analyst, developers can do documentation right?

But you will say, developers might not understand the domain and we need someone who
understands the domain to accurately document the business requirements.

But if the previous statement is true, that means the users can document the requirements better than anyone, after all they are the experts of the domain.

Before we give up, let us explore something else. What if the business analyst could also do data modeling, so we have established that a good business analysts needs to have good domain knowledge, needs to know a little of development and needs to be very good with documentation. These are all qualities that define a good a data modeler.

You might be asking yourselves, Data modeler ha? The two roles cannot be more different, in one you deal with report and dashboard mock-ups and in the other one there are some abstract objects called entities that contain attributes. However, aren't all elements in a report attributes? Also, isn't a dashboard just a nice graphical representation of a report? So, following this logic, isn't the data modeler part of the business requirements?

And so, my dear readers isn't this the role of a business intelligence analyst, help business users articulate and document the requirements?

Until next time,