Archive | October 2013

My Dog Ate the Requirements, Part 2

DogAteRequirements2

There’s nothing more frustrating than not being able to rely upon a business partner.  There’s lots of business books about information technology that espouses the importance of Business/IT alignment and the importance of establishing business users as IT stakeholders. The whole idea of delivering business value with data and analytics is to provide business users with tools and data that can support business decision making.  It’s incredibly hard to deliver business value when half of the partnership isn’t stepping up to their responsibilities.

There’s never a shortage of rationale as to why requirements haven’t been collected or recorded.  In order for a relationship to be successful, both parties have to participate and cooperate.  Gathering and recording requirements isn’t possible if the technologist doesn’t meet with the users to discuss their needs, pains, and priorities.  Conversely, the requirements process won’t succeed if the users won’t participate. My last blog reviewed the excuses that technologists offered for explaining the lack of documented requirements; this week’s blog focuses on remarks I’ve heard from business stakeholders.

  • “I’m too busy.  I don’t have time to talk to developers”
  • “I meet with IT every month, they should know my requirements”
  • “IT isn’t asking me for requirements, they want me to approve SQL”
  • “We sent an email with a list of questions. What else do they need?”
  • “They have copies of reports we create. That should be enough.”
  • “The IT staff has worked here longer than I have.  There’s nothing I can tell them that they don’t already know”
  • “I’ve discussed my reporting needs in 3 separate meetings; I seem to be educating someone else with each successive discussion”
  • “I seem to answer a lot of questions.  I don’t ever see anyone writing anything down”
  • “I’ll meet with them again when they deliver the requirements I identified in our last discussion.
  • “I’m not going to sign off on the requirements because my business priorities might change – and I’ll need to change the requirements.

Requirements gathering is really a beginning stage for negotiating a contract for the creation and delivery of new software.  The contract is closed (or agreed to) when the business stakeholders agree to (or sign-off on) the requirements document.  While many believe that requirements are an IT-only artifact, they’re really a tool to establish responsibilities of both parties in the relationship.

A requirements document defines the data, functions, and capabilities that the technologist needs to build to deliver business value.  The requirements document also establishes the “product” that will be deployed and used by the business stakeholders to support their business decision making activities. The requirements process holds both parties accountable: technologists to build and business stakeholders to use. When two organizations can’t work together to develop requirements, it’s often a reflection of a bigger problem.

It’s not fair for business stakeholders to expect development teams to build commercial grade software if there’s no participation in the requirements process.  By the same token, it’s not right for technologists to build software without business stakeholder participation. If one stakeholder doesn’t want to participate in the requirements process, they shouldn’t be allowed to offer an opinion about the resulting deliverable.  If multiple stakeholders don’t want to participate in a requirements activity, the development process should be cancelled.  Lack of business stakeholder participation means they have other priorities; the technologists should take a hint and work on their other priorities.

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My Dog Ate the Requirements

20131016DogAteMyHomework

I received a funny email the other day about excuses that school children use to explain why they haven’t done their homework.  The examples were pretty creative:  “my mother took it to be framed”, “I got soap in my eyes and was blinded all night”, and (an oldie and a goody) –“my dog ate my homework”.  It’s a shame that such a creative approach yielded such a high rate of failure. Most of us learn at an early age that you can’t talk your way out of failure; success requires that you do the work.  You’d also think that as people got older and more evolved, they’d realize that there’s very few shortcuts in life.

I’m frequently asked to conduct best practice reviews of business intelligence and data warehouse (BI/DW) projects. These activities usually come about because either users or IT management is concerned with development productivity or delivery quality. The review activity is pretty straight forward; interviews are scheduled and artifacts are analyzed to review the various phases, from requirements through construction to deployment. It’s always interesting to look at how different organizations handle architecture, code design, development, and testing.  One of the keys to conducting a review effort is to focus on the actual results (or artifacts) that are generated during each stage. It’s foolish to discuss someone’s development method or style prior to reviewing the completeness of the artifacts. It’s not necessary to challenge someone approach if their artifacts reflect the details required for the other phases.

And one of the most common problems that I’ve seen with BI/DW development is the lack of documented requirements. Zip – zero –zilch – nothing.  While discussions about requirements gathering, interview styles, and even document details occur occasionally, it’s the lack of any documented requirements that’s the norm.   I can’t imagine how any company allows development to begin without ensuring that requirements are documented and approved by the stakeholders.  Believe it or not, it happens a lot.

So, as a tribute to the creative school children of yesterday and today, I thought I would devote this blog to some of the most creative excuses I’ve heard from development teams to justify their beginning work without having requirements documentation.

  •  “The project’s schedule was published. We have to deliver something with or without requirements”
  • “We use the agile methodology, it’s doesn’t require written requirements”
  • “The users don’t know what they want.”
  • “The users are always too busy to meet with us”
  • “My bonus is based on the number of new reports I create.  We don’t measure our code against requirements”
  • “We know what the users want, we just haven’t written it down”
  • “We’ll document the requirements once our code is complete and testing finished”
  • “We can spend our time writing requirements, or we can spend our time coding”
  • “It’s not our responsibility to document requirements; the users need to handle that”
  • “I’ve been told not to communicate with the business users”

Many of the above items clearly reflect a broken set of management or communication methods. Expecting a development team to adhere to a project schedule when they don’t have requirements is ridiculous.  Forcing a team to commit to deliverables without requirements challenges conventional development methods and financial common sense. It also reflects leadership that focuses on schedules, utilization and not business value.

A development team that is asked to build software without a set of requirements is being set up to fail. I’m always astonished that anyone would think they can argue and justify that the lack of documented requirements is acceptable.  I guess there are still some folks that believe they can talk their way out of failure.

 

 

Data Quality, Data Maintenance

20121009 DataMaintenance

I read an interesting tidbit about data the other day:  the United States Postal Service processed more than 47 million changes of addresses in the last year.  That’s nearly 1 in 6 people. In the world of data, that factoid is a simple example of the challenge of addressing stale data and data quality.  The idea of stale data is that as data ages, its accuracy and associated business rules can change.

There’s lots of examples of how data in your data warehouse can age and degrade in accuracy and quality:  people move, area codes change, postal/zip codes change, product descriptions change, and even product SKUs can change.  Data isn’t clean and accurate forever; it requires constant review and maintenance. This shouldn’t be much of a surprise for folks that view data as a corporate asset; any asset requires ongoing maintenance in order to retain and ensure its value.  The challenge with maintaining any asset is establishing a reasonable maintenance plan.

Unfortunately, while IT teams are exceptionally strong in planning and carrying out application maintenance, it’s quite rare that data maintenance gets any attention.  In the data warehousing world, data maintenance is typically handled in a reactive, project-centric manner.  Nearly every data warehouse (or reporting) team has to deal with data maintenance issues whenever a company changes major business processes or modifies customer or product groupings (e.g. new sales territories, new product categories, etc.)  This happens so often, most data warehouse folks have even given it a name:  Recasting History.   Regardless of what you call it, it’s a common occurrence and there are steps that can be taken to simplify the ongoing effort of data maintenance.

  • Establish a regularly scheduled data maintenance window.  Just like the application maintenance world, identify a window of time when data maintenance can be applied without impacting application processing or end user access
  • Collect and publish data quality details.  Profile and track the content of the major subject area tables within your data warehouse environment. Any significant shift in domain values, relationship details, or data demographics can be discovered prior to a user calling to report an undetected data problem
  • Keep the original data.  Most data quality processing overwrites original content with new details.  Instead, keep the cleansed data and place the original values at the end of your table records. While this may require a bit more storage, it will dramatically simplify maintenance when rule changes occur in the future
  • Add source system identification and creation date/time details to every record.  While this may seem tedious and unnecessary, these two fields can dramatically simplify maintenance and trouble shooting in the future
  • Schedule a regular data change control meeting.  This too is similar in concept to the change control meeting associated with IT operations teams.  This is a forum for discussing data content issues and changes

Unfortunately, I often find that data maintenance is completely ignored. The problem is that fixing broken or inaccurate data isn’t sexy; developing a data maintenance plan isn’t always fun.   Most data warehouse development teams are buried with building new reports, loading new data, or supporting the ongoing ETL jobs; they haven’t given any attention to the quality or accuracy of the actual content they’re moving and reporting.   They simply don’t have the resources or time to address data maintenance as a proactive activity.

Business users clamor for new data and new reports; new funding is always tied to new business capabilities.  Support costs are budgeted, but they’re focused on software and hardware maintenance activities.  No one ever considers data maintenance; it’s simply ignored and forgotten.

Interesting that we view data as a corporate asset – a strategic corporate asset – and there’s universal agreement that hardware and software are simply tools to support enablement.  And where are we investing in maintenance?  The commodity tools, not the strategic corporate asset.

Photo courtesy of DesignzillasFlickr via Flickr (Creative Commons license).

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