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.