Trusting the Data

Virtually all organizations in this digital age depend on information, on data. They use it to know where the business is going and how to manage it. They receive and provide it to their customers and business partners.

Frequently, however, we see a report or a web page and wonder if we can trust what we are seeing. Is it accurate, is it complete, is it the latest most up-to-date version, where did it come from, and what exactly does it include? Often, our mistrust is well-founded, and as we know, it’s very easy to lose trust and extremely difficult to rebuild it once it’s lost.

So what can we do? How can we build and maintain trust?

Let’s start with an analogy. In our everyday lives, we all have to trust things that we receive in a ready form. We haven’t been part of designing, sourcing, or producing them, and yet we trust them. Take a can of tomato soup, for example.

We buy it, we open it, and we use it. But why? Why do we trust what’s inside?

Let’s break this down:

• We know what’s in it – It has a label saying it is tomato juice, and if we turn the can, we can see a list of ingredients. So it has a good description, a good definition.
• We know where it came from – We know what country it was produced in, sometimes we know precisely the state, province, or city it came from. We also know who imported it if it came from abroad. So we know its source and sometimes the path it took to get to us – its lineage.
• We know how fresh it is – There is a “best before date” or “expiry date” on the can. So we know how fresh it is, how current or up-to-date it is.
• We know who produced it – There is a company name and address on the can indicating the producer. We know who to contact if there are problems with the contents: we know who is responsible for the content, who takes ownership and accountability.
• We know its quality is tested – Even if we don’t see it on the can, we know that there are a large number of quality controls and testing happening before the product is packaged. We can find out about them if we go on the producer’s website. So we know its quality is measured and assured.
• We know there is oversight – In addition to all of the above, each country has an oversight body performing independent testing and providing warnings and recall notices. So we know oversight exists, in some form.
• So, a lot goes into the trust we have in a simple can of tomato juice. We should expect nothing less from our data. Here is an outline of what steps can we take to establish data trust:
• Ownership and accountability – Have an accountable individual within the organization who “owns” the data, whether it’s in a report, a database, an application, a department, etc. Typically, there are multiple individuals accountable for different data assets. They may be organized around data domains, business processes, or systems. A data governance organization usually sets the stage for data accountability.
• Metadata – Data definitions and data lineage help develop and maintain understanding and organizational alignment around what the data means, what it is supposed to contain, where it comes from, and what it is used for. A metadata management methodology and practice define how to do this.
• Data Quality – Data quality management includes the definition of quality standards, the consistent measurement, and reporting of data quality, as well as all automated and exception-based measures to improve and assure data quality. A data quality management framework, processes, and solutions help address this.

We can and should do what is needed to establish and maintain trust in the data.

In subsequent posts, we will be providing more detail on how to achieve each of these steps, in line with your organization’s strategic goals.

Krasen Paskalev

SVP Practice and Solution Delivery