The good news: The data your organization is (hopefully) collecting contains the answers you need for most, if not all, of your strategic and operational questions. You know those issues that keep you up at night? Those unanswered questions about what drives your organization toward successful outcomes? These questions can be addressed and possibly resolved by harnessing the power of the data you’re collecting.

The bad news: Creating an environment for self-service analytics, and deriving meaning from your data is much easier said than done.

That being said, there are specific steps to help your organization (whether it’s an entire enterprise or a department) become one that is data-centered and data-driven—and here’s how. 

Determine what data you need (Hint: What drives your business?)

You can collect everything, but you’re much more likely to garner wisdom from raw data if instead, your org first identifies the data that drives business outcomes. Plainly speaking, what matters most to your org? Once you identify what matters at a high level, your company is then able to point to the data that matters. This isn’t always easy since sometimes it’s unclear what may affect an outcome. And in those cases, err on the side of saving data. Of course, the costs of data storage, governance and curation must be weighed; however, there are various ways to mitigate those costs (cloud storage, for example).

If we’re thinking from the perspective of a technology-centric business, where financials are measured and determined based primarily on online activity or app engagement, then there are specific kinds of data that deserve a high level of focus and scrutiny. Some of those specifics would include the identification of your org’s user base. Who are these people? What are their attributes? For example, email addresses, browser info, IP address, locale, Operating System (OS), device type, phone #, demographics, etc. Basically, your org wants to be able to identify who uses your product and how they’re doing so.

Some other pieces of data – and the questions to ask – that are valuable to your business are:

• Search data (How are people finding you?)
• Activity on your site or platform (Where are people going in your product? How are they getting around once they are with you?)
• Usage patterns (How long do people stay logged in? How often do they visit?)

How to put good data to use: The easy(ier) part

Once your business determines the kind of data it wants and needs, the next objective is to put that data to use—good use. As above, this is still part of the process that is not technically difficult. Here, it’s important to identify specific metrics your business wants to track and expose to your stakeholders. To make it more simple: What do your external stakeholders (e.g., investors) need to see, and what do your internal stakeholders (e.g., board of directors, employees) need to see?

Internal & external metrics to use

Some external metrics your business will want to create are sales measures, number of users (or customers) and number of subscriptions (or accounts/items sold). A few examples of internal metrics may be:

• Analysis of your hiring practices
• Profit ratio
• Trend analyses
• Seasonality
• Daily active users

Another excellent use of your data would be a cluster analysis of your customer measures (i.e. sales, subscriptions/units sold, geolocation). Cluster analysis helps determine customer segmentation, which in turn, helps drive marketing and sales initiatives, as well as the determination of resource allocation.

How to put good data to use: The hard part

Now that your org has identified the data you need and how you might use it, here comes the hard part. The analytics and algorithms that drive a data-centered organization need to be created, deployed and maintained by skilled and focused individuals. To put it simply, there are no shortcuts to becoming a data-centered org—you absolutely need people in your company that not only understand all facets of data and have the bandwidth not only to maintain it, but communicate it effectively throughout the organization. When shortcuts are taken, there are several negative outcomes that can occur, and can be really detrimental to the health and operations of a company.

Conclusion: Have the data team lead the charge 

If your goal is to make your organization truly data-driven, you must have a skilled set of data scientists, engineers, analytics engineers and so on to truly own and distribute the right data to the rest of the business. Start with the “easier” part and determine what drives your business, identify specific metrics your org wants to track and then leave the rest up to the experts. And once you’ve got your data ducks in a row, be sure you’ve got someone on the data team that can help the rest of the organization make sense of the data and teach them how to make strategic, informed decisions based off of that data. Data is a company-wide effort, but having a knowledgable data team leading the charge will ensure your entire org develops a data-driven culture that is aligned and ready to achieve business objectives.   

Have your team skill up with our data courses.