Your Data Resolution

An annual look at improving data driven decision making in your organization.

Well, another year is behind us and we got through January, that cold, exhausting month when new year promises are broken. As humans, we put special meaning on data each time we mark one trip around the sun. We organize our trends, our profits, our losses, and our progress based on an annual cycle. Many retailers literally take stock of the year in January. With much of the sweat work of closing out a year behind us, February is the perfect time to take stock of your data, data practices, and data strategy. Let’s look at the three most important topics when reflecting on your data.

What data do you have?

If you have recently pulled together any annual report, I bet you have some thoughts on how it could be better. Maybe you would like more data — or more accurate data. Or maybe your reports are in too many places and reconciling them is why you hate January (that and the seasonal cold the in-laws gave you in late December)

Having the right data is crucial to decision making in your organization. It is the responsibility of all data consumers in your organization to be on the lookout for data gaps, fidelity, accuracy, and access. An analyst or data steward may be able to see gaps or find opportunities for data improvements at a high level, but the people on the data front lines that use the data to make decisions are usually the first to know when there is an issue. Your organization should take this opportunity to seek out recommendations from data stakeholders and consumers on what their data needs are and what data you have to support them.

How do you manage your data?

I have worked with many organizations, from large international enterprises to small startups and NGOs. What do they all have in common? They have messy data lying around. And it doesn’t matter how many times they clean and organize their data, it gets messy right away again. It’s like my kids’ bedrooms, an ever loosing battle. I can only hope that years after I have provided them with sage wisdom and guidance, that they are now keeping things cleaner (both my grown kids and my clients).

You can still gain insights into decision making however even with messy data habits, but it can be much more expensive and limited in scale and scope. Some questions to consider are:

• How are you managing your data?
• Do you have a data steward?
• Do you review data practices and make changes?

Data management is a lot like plumbing, you have to figure out where the flow is going and how best to support the needs of those who are using the water for different purposes.

There are a lot of things you can do to improve your data management. After you assess the data that you have, find a way to organize this data so that it is accessible and relatable. A centralized data platform is one way to wrangle data together, but there are other options as well. You may hear terms like data lakes, data warehouses, data lakehouses — all of these are simply part of data management. The important thing is that you look at your data as an important asset that needs management then find out where you need improvement.

What is your data strategy

Many times, data feels like a by-product of the work that we do. However, your data is much more valuable than that. It can be the seed for making informed decisions. Many organizations do not have a formal data strategy. Data is either happenstance, an afterthought, or simply content for end of year reporting.

Creating a data strategy is key to maturing beyond reactionary and stagnant data practices. It takes time and discipline but can yield amazing results. It is not simply about identifying new data sources, creating pipelines and warehouses, and having data visualization. It begins with a shift in people and culture. How do you value your data? How do you plan and budget for data management and operations? How do you start creating data-first initiatives?

Now what?

Now it is time to take stock and actually see how you are doing. Here are a few questions I use as discussion points when talking with clients.

Get to the heart of the matter

• What does success look like for you?
• What are the crucial decisions that you need to make for your organization?
• If you could have any knowledge to help you make that decision, what would that be?
• How can you gain that knowledge, what data would you need?
• Who are the ones in your organization that care about the data?

Assessment

• What data do you have?
• Where is it?
• What data don’t you have?
• How can you get it?

Management

• Who is looking after your data?
• Does someone have a clear and up to date view on the entire data ecosystem?
• Can decision makers get to the data they need when they need it?
• How do people request data or data insights?
• What tools are you using to make data available?
• Who has access to the data and is that access traceable?
• Could your current data governance be too relaxed and create data risk? Or is it too tight?
• Is your data in a manner that makes it queryable and allows for data exploration (as opposed to PDF reports on a file server)?
• What is the lifecycle of your data?
• Does your data and data management need to be audited regularly? What are your audit plans and responsibilities?

Strategy

• Based on the information above, think more about “What does success look like for you?”
• What are your primary data goals?
• What steps can you take to accomplish these goals?
• What hurdles are in your way?
• What steps can you take to remove or leap over those hurdles?

This is not a complete list of questions but rather discussion points to get started on creating a better data environment for decision making.

The final advice here is similar to any resolution: Be prepared to make bold moves and commitments. Also understand that change can take time and require multiple steps. Set yourself up for success with goals that are achievable, but that also cause you to grow.

JT Mudge is a data, innovation, and foresight consultant at productOps and works with organizations to improve their data and technology strategies and have better insights into their futures.