Data Management? It’s a Supply Chain.

In the business world today we think of data as something that is really complicated, that you need to be highly qualified to understand. Consequently, companies that want to be data-driven are working hard on data training programmes to give their people the skills to work with data. 

This wasn’t the case in the past. Historically, business teams naturally understood data. They were the people who created data and worked with it to generate insights.

How did we become uncomfortable with data today?

Well, it’s for two reasons:

1. Systems and tech teams do things to data, and we don’t understand what they do. 

2. There is so much data today it’s too overwhelming to understand it all.

What mysterious stuff does the tech team do with data?

Before we get into the role of the tech team, let’s start with a note on technology. Technology, fundamentally, is created to automate activities that people used to do. 

So what did we do to data before tech? Well, we’d:

  • Collect/Record Data
  • Copy/Move Data into new views
  • Assemble data to help us understand things (by building reports)
  • One final addition that people do naturally at every step of the process is to look for anything that seems incorrect (and amend incorrect values)

So, in a nutshell, technology and systems primarily do the above activities, automatically at scale. Technical people are usually involved simply to use technical language to tell the systems what to do.

Context Makes Data Approachable

On the second point, many business teams find data as a topic intimidating. However, it’s easy to understand data, by looking at it logically, by remembering three key points:

  1. Data is still most commonly generated by the people in an organisation.
  2. All we typically need to understand data is a little context. Basic information like a description of the data, where it came from, how it was created, and how it was quality assured.
  3. Once you have context, it’s easy to understand

This information is much like the labelling we have on food packaging that specifies the manufacturer, ingredients, country of origin and best before date. When the information is available, it’s easy to understand whether the food is safe to eat. However, if it’s difficult to find, you’re unlikely to feel comfortable consuming it. So, to make business teams more comfortable with data, we need to create a labelling process that’s uniform and easy to understand in the business.

It’s kind of like a supply chain.

An easy way to understand this work is to compare it to the supply chain. A file of data is effectively a component part of any ‘data product’ in an organisation, whether that product is a sales report or a procurement dashboard. Much like the ‘nuts and bolts’ that we rely on to build products in the physical world.

The process for sourcing, moving and assembling component parts in the physical supply chain is very similar to the activities that we do in the data world.

  • To create ‘data products’, modern businesses rely on multiple different teams, systems and geographies to ‘supply’ data.
  • There are specific requirements around what a data component should look like.
  • There are often specific delivery dates when we expect data to be received.
  • There’s a process for moving data securely and at scale.
  • There’s a process for checking that received data is correct
  • There’s a need to communicate with suppliers if requirements change or quality issues are identified.

So how does this apply to data management?

When there are several components in a supply chain, this can be a complex process to manage, even using technology. That’s because it depends on two teams with very different perspectives to collaborate and communicate throughout the process. So, it makes sense to manage the process in a similar way. To do this, it’s important to consider how easy it is to communicate at key points along the journey, and create an interface that both suppliers and requesting teams can both work on to collaborate throughout the process.

This approach is very similar to what supply chain software does in the logistics industry. It creates an interface to help teams measure and understand every step along the journey and automate the parts of communication where technology can support.


What’s Next?

Want more information on gather360 or how to work with data? Our expert team can help, speak to a member of our team today for more information. Check out our other blogs and resources where we explain more data concepts and strategies.