What happens when people who should be accountable for producing quality data as part of their job make it clear that they want nothing to do with producing data? What happens when these people say, “It’s not my job” and they act accordingly?
What happens when the data they should produce is important in improving operations, marketing and sales, or engineering (a quick sample of impacts this could have)?
Does the organization allow them to get away with refusing to produce the data?
What is the best way to deal with these people who literally say that it is not their job to produce the data?
So many questions…and so little space to answer.
I am known to say that “everybody is a data steward” and that the organization must “get over this fact” (as I wrote back in in 2018). The truth is, to cover the entire organization with governance and stewardship of data, everybody who has a relationship to data, as a definer, producer and user of the data, must be held formally accountable for that relationship. It’s all in the data.
If an organization wants to improve the understanding and value people get from the data, that means that people who define data must be held accountable for how they define the data. This includes, when possible, not defining the data in an umpteenth way and using existing data whenever possible. This includes the responsibility for providing strong business definitions rather than the basic “cheeseburger” variety (a cheeseburger is defined as “a burger with cheese”). Data definition will not improve by itself and by providing standards for how the data is defined.
People who use data must be held formally accountable for how they use data. You will not force only a percentage of a population of people who use sensitive data to protect that data. Everybody who uses sensitive data must protect that data. That is what the law says–and this is to what the government will hold your organization to account. Many a data governance or information governance program, or many a data security program, is put in place to assure that all sensitive data is protected.
So, if people who define data must be held accountable for how they define data, and the people who use data must be held accountable for how they use data, where does that leave the people who produce the data? I would wager that you didn’t answer that question by thinking, “we let them only produce the data they want to produce.” People who are on the front-line of producing data that is important to the organization must be held formally accountable for the data they produce. This should make a lot of sense. It’s all in the data.
In many organizations, the salespeople are not particularly skilled (or interested, for that matter) in entering data into systems. In many organizations, the same can be said for the technical engineers are not particularly skilled (or interested) in entering data into systems. The salespeople say they are responsible for closing sales. The engineers say that they are responsible for designing and creating the specifications for products. In fact, I have recently experienced, with two of my clients, that people in these roles have outright said that this is not their job. There are potential problems that can arise from allowing these people to reject the notion that they are responsible for entering data.
It is important to recognize that the ability to close sales often depend on data about the prospect, products and/or services the prospects are buying, and the contacts and transactions that take place every step of the way toward closing the sale. It is also important to recognize that the delivery of well-engineered products that are well understood and required by customers often depend on the data about specifications, materials, availability and so much more. If we cannot expect the salespeople and engineers to produce the data, then there has to be an alternative way to get the appropriate data produced in a quality and timely manner.
I see that there are two options to resolve this problem:
The first option in these situations is to require the salespeople and engineers to produce the data. Requiring them to produce the data may be rejected out of hand if these people are given the ability to say that the data is not their job. Perhaps if these people could become enlightened and truly understand how the production of the data will improve not only their performance, but also the performance of the company or organization, they will see the light as to why they are being requested to take on a little bit more data-associated responsibility. Oftentimes, the amount of time required to produce the data is minimal but would require a change to the “way they have always done things.” And we all know how willing people are to change their mode of operation.
The second option is to provide a resource to work with the salespeople and engineers, someone who takes on the responsibility of producing the data in a timely manner. This is a non-invasive way to satisfy the same requirement. This does not require an additional resource per salesperson or engineer, but rather, the addition of a data production steward (“person who is responsible for producing the data for the organization”), who assists and works with all of, or a percentage of, the salespeople and engineers. Granted all of these people require this type of coverage, so the number of data production steward resources will depend on the number of people who sit in these positions within your organization.
Either of these options, 1) telling the staff that they must produce the data (more invasive) or 2) making certain that a resource is available to work with the staff to produce the data (less invasive), are viable approaches. The option that cannot be selected is that the data is not produced. This is especially true when the data in question is critical to improving operations of the organization. We all know that the data will not produce itself. If the data is deemed necessary for operational improvement, and leadership is not ready or willing to force people to produce the data, it may become necessary to provide resources who take on data production responsibilities.
Data is everybody’s job. The quicker an organization gravitates toward that statement, the quicker the organization will produce the data that is required to improve their bottom line.
Again, data is everybody’s job. Practitioners of data governance, data stewardship and data management need to deliver options that are acceptable to the organization. Sometimes this requires us to think outside the box and look at alternative approaches to solving data problems. It is all in the data.
