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Monday, November 23, 2009

Business, Information and Technology

Are you in management? Do you have annual/quarterly goals? Will you be held accountable for achieving those goals? Is the accountability expressed in bonus dollars? Is there any possibility of a zero bonus?

Are you still with me?

How will the achievement of your goal(s) be measured? Please note here that "how" has two dimensions: one is related to process and the other to a unit of measure. In all of my vast personal experience, all of the attention has been focused on the unit of measure part (when there has been any attention at all), and the process part has never even been part of the conversation.

Please understand that what follows is not intended to sling mud at any individual or organization. My purpose is to clear the air so that we can talk about how we're really going to achieve our goal(s).

I am going to generalize based on extensive, though anecdotal, experience. In other words, I have not conducted a survey, scientific or otherwise, and cannot produce data to back up anything I'm about to say here, so I'm leaving it up to you, the reader to determine whether it feels like truth or not. Should you feel that this does not ring true, or should you wish to fault me for not being more objective, I would ask that you produce a study or at least a body of experience in support of your position.

Awards of bonus dollars tied to achievement are based solely on whether the holder of the dollars wishes to give them away or not. There is rarely, if ever, any protocol defined for defining metrics, units of measure or measurement process. You will go into an "annual assessment" meeting with your boss and he or she may discuss your level of achievement in very general terms before announcing the amount of your bonus or a recommendation for an increased level of compensation.

Why is this important, you ask? Well, it is important because it's the the way things are done. Despite vigorous protests to the contrary, the business world is set up to run on subjective assessment supporting subjective decisions. What, you say that your decisions are "data-driven" (objective)? I would love to hear the story behind the data that was used to arrive at your most recent decision.

All of this is background for understanding why "data" initiatives so frequently become mired in a swamp of politics and personality. Let's walk back from a data-driven decision.
  1. You are able to make the decision because you trust the data.
  2. You trust the data because you are familiar with and trust its source.
  3. You trust the source because you know that it is reliable.
  4. You know that it is reliable because it consistently produces information that can be relied upon.
  5. The source has been consistent because it always uses a tried and true methodology (set of processes) to produce its product.
  6. The consistency is possible because the methodology includes steps designed to validate the source's inputs.
  7. The validation decision returns us to #1.

How do you feel about standards (e.g., standard operating procedure or SOP)? If you don't currently support the creation, implementation auditable use of standards or, at any time in the past have not done so, you have no right to and almost certainly do not have access to reliable information and therefore no claim to data-driven decisions. Just to drive the point home, when your boss decides that you won't be getting that bonus or increase you were counting on, your only acceptable response is to smile and say thank you.

By the way, if you notice that your bank account (or budget) is suddenly much bigger (or smaller) than it was yesterday, what is your responsibility? Who are you accountable to? How much trust can you afford? Now you have some insight into compliance.

The use of technology introduces an additional huge portion of uncertainty into the trust equation. Take another look at the decision walk-back above and note the points where the use of technology means adding additional paths and complexity to the validation process. This is what your data governance people are trying to get their arms around.

To summarize:

  • data-driven or intelligence-driven decisions demand trust
  • trust demands reliability
  • reliability demands consistency
  • consistency demands compliance
  • compliance demands governance

OK, you can go back to work now.

Tuesday, November 17, 2009

What Is "Data" Anyway?

If you have any experience with phone support (on either end) you will recognize how easy it is to get deep into a process before realizing that the other person is on a completely different path than you are. RTFM (Read The F---ing Manual) often pops up as the answer to our communication difficulties, but it clearly is not the answer or it would have been universally embraced by now.

I happen to be a proponent of the theory that the answers aren't nearly as important as the questions. As a teacher, I know that learning is happening when the pupil is asking questions--particularly a series of related questions. This has become very important as I have attempted to make headway on [data] governance and [data] quality.

My early attempts assumed that everyone knows what data is--and they do, in the same way that a picture is worth 10,000 words. Each and every person you talk to knows what "data" is and each has a different idea in mind. For most, it's a picture of the last set of values they looked at. This might have been a spreadsheet, a graph, a collection of measurements... The key is that data is a set of values. For some, "data" is a commodity. It is files, stripes on a disk, a percent of capacity, a quantity of bytes measured in "mega-", "tera-" or "peta-". For still others, "data" is represented by a schema, model, definition, or some other abstraction.

Given those varying perceptions or perspectives, is it any wonder that at some point in the quest for "data" anything we find ourselves stuck in the quicksand of confusion. Even when all parties have been saying the same things and have been agreeing on goals, there comes a point when someone will say, "We're not going to do that." or "I don't see why that is necessary." or "But that will change my work flow." This is frequently the point at which everything starts to unravel.

So what I have learned, and what I offer to you now, is that the initial phase of any data initiative must be a carefully constructed education process to insure that the quicksand moment never happens. This must be thought of as risk management. Remember, too, that the really important questions (and answers) initially are not the ones you're hearing. All of the different constituencies are going to be much more comfortable exchanging information (or misinformation) within the tribal group than with "outsiders."

The best way to head off this risk is to carefully choose allies from each constituent tribe and use informal conversation about their pain points and the ways that data figures in the relief of that pain. You will be setting these people up to be the "experts" within their respective tribes. Part of this will be coaching them in how to respond to questions and discussion in which they don't feel themselves to be on firm ground. They need ways to postpone a response until they've had a chance to confer with other experts. This is easy to do by setting up a collaborative model.

Rule one of this model is that I never answer for someone else. Everyone can understand that a situation involves yet another perspective and that it is necessary to involve someone from that tribe in order to get a complete answer. The most common danger here is "We don't have time for that." Everyone must understand that this is an absolute red flag event. It signals that we still have not achieved a universal understanding of objective.

When a red flag event happens, it isn't the same as finding ourselves up to our necks in quicksand. It just means that we need to engage in some risk mitigation. It's a sign saying "Quicksand ahead." We will need to bring this person into the fold--usually through informal and non-threatening discussion with at least one peer or trusted expert.

Your role, should you choose to accept it, is to be a non-judgmental, constant, committed, and helpful presence that can be relied upon to be a neutral mediator and facilitator who feels like a friend in any need. Your motives must be above reproach. You cannot count on and should not hope for recognition. All around you will be better off for your presence.

If you are senior in the organization to this person, you should make sure that you are appreciating their contribution but they will appreciate non-public affirmation since putting them in a spotlight may negatively impact their ability to continue to function in the same way.

"What is data anyway?" is a question that requires many answers initially and one answer eventually. Remember, though, that many people are really only interested in what they have to do differently. "Data" may have no meaning whatsoever in their day-to-day responsibilities even though they may be monitoring real-time run charts with instructions to take a specified action when the line goes above or below a certain point. You can't possibly know where to start or where to stop in defining data for them. That's why you need the tribal expert.

Don't seek "important." "Helpful" will take you much farther more quickly.