It 'Meta' Lot to Me: How To Use Metadata for Digital Transformation

To start making sense of all the data we have been gathering so far in our digital transformation journey, we need to start aggregating and classifying it. Otherwise, we will never make any sense of the data we have been tracking.

This is Part 7 in a series all about the digital transformation journey. In our last post, we discussed how to improve data entry in regards to your timekeeping method. And now we will continue perfecting that method by adding taxonomy organization.

The first step is to begin cleaning our data, otherwise we risk corrupting our analysis. In short, we need two things to start mining our time-keeping data:

• Taxonomy for our data, which is a classification scheme
• A Data Map showing the hierarchy of our classification

And both of those adjustments involve creating Metadata.

What is Metadata?

Metadata is data about data. While that may sound simple, it is a critical step in helping move out of the weeds and into visualization of your data for analysis.   Once we start aggregating, we can also start to see patterns, making predictions, and find relationships that lead to better predictions and better investment decisions. 

Implementing Taxonomy for Your Data

First, we need to classify our data. But how do we do that? A beginner taxonomy classification system can be based on answering more of the "Fives Ws" (Who, What, Where, When, and Why). Luckily, we already have the ‘When’ for each entry. The ‘Why’ will be useful after we have done more analysis, so we hold off on that for now.

The remaining 5 Ws (Who, What, Where) should provide us a good starter taxonomy system. We will continue to use the Excel spreadsheet strategy to address these questions and classify our data. 

Answering the "Who?"

Who or what benefitted from my activity - myself, a customer, a project, a department?

Your time is an investment, and while it could be argued that you are the ultimate beneficiary for your time, focus on tracking anyone else who benefited immediately from your time investment (colleague, group, department, family member, friends, customer, school, etc).

Internally, at Data Networks, my activities tend to impact several different teams. This is my first draft for the “Who” taxonomy along with a hierarchical Data Map:

• Customer
  • Internal Teams
    • Commercial
    • State and Local Government
    • K-12 Education
    • Higher Education
    • Engineering
    • Marketing
    • Management
  • Customers
    • Customer Name

Answering "the What?"

What type of activity was I doing?

I must repeat a previous recommendation to you here: “Do not get too granular." For that reason, I am limiting the field length and disabling text wrapping on the ‘Description’ Column Name in my Excel spreadsheet. The goal is to develop a high-level overview of your time investments.

Top Tip: If you need help building this out, look at what your management has you track on any activity report.

For now, here are the activities that consume most of my time:

• What Project?
  • Project Name
• Activity/What?
  • General Administration
  • Research
  • Discovery
  • Design
  • Building the Bill of Materials (Products and Services)
  • Building the SOW
  • Presenting
  • Commuting

Answering "the Where?"

This is all about location, so let’s keep it very simple. Remember, we do not want to make anything difficult to track. Location provides an easy Data Categorization map:

• Where/Location:
  •  Home
  • Office
  • Customer Site
  • Staging Center

Looking at "the Why" in the Future

Although we should definitely be tracking "the Why" in regards to our data, we need to first look at the data we gather. Then, we can start successfully defining a Data Map for this category.

Armed with our new classification system, we can continue to build out a sturdier, more organized Digital Transformation Timekeeper in Excel.

In the next post, we will dive in deeper to see how we can perfect this system and continue along the journey of Digital Transformation. But for now, focus on implementing this new taxonomy strategy and see how that impacts your data analysis.

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