Home BUSINESS How To Use Data To Break Down Silos And Unify Your Teams

How To Use Data To Break Down Silos And Unify Your Teams

In this age of big data, many companies are laser-focused on using data within their companies. However, improper management of data is hampering your organisation.

Referral data is spread across tools, leads get saved in an Excel file or CRM, and other sales analytics data points such as quotes, opportunities, and forecasts live in another system. This approach creates silos within departments. Data is trapped behind walls and never gets shared with the rest of your company.

To begin to address this, you need to figure out a way to break down each of your data silos to make data analysis more holistic and, ultimately, your data-driven decisions more able to maximize your team’s real potential.

1. Take Inventory Of Your Data

In a siloed environment, data is not shared, and teams work in isolation. By contrast, a unified team shares data across departments and respects one another’s ownership. A unified organization can build a more actionable, data-driven culture by taking an inventory of their data.

Take note of the data in your company across different departments/ silos, who has or doesn’t have access to what, and who has ownership over certain things. This will give you a better place to start in breaking down your silos.

In most companies, there is an inherent strain in relations between the marketing and finance department and resultantly a dissonance in collaboration. If you discover that this is an area of critical concern in your organization, you will need to gather additional data to bridge this dissonance. Discover more active steps you can take to save the relationship between the two and thereby break any silo-ed information between the departments.

2. Draft Questions

You don’t necessarily have to wait until you finish your data inventory. While doing so, you can start creating questions that your teams might be interested in or are already asking from your data.

If you know the most pressing questions, you are more aware of what to target. You can create a system that extracts the right data from your tools and convert them into more widely accessible formats.

Sample questions might look like this:

  • How fast is the company growing so far?
  • Which tools are propelling your growth the most?
  • Of your services, which ones do the audience seem to respond to the most?
  • How much does process X cost your company each month?
  • Are there specific triggers that usually result in a spike in your Organisation’s website traffic?

Suppose you notice that your questions are leaning more towards one area—for example, operational costs or return on investments—while you don’t have direct or any access to financial data. In that case, you need to make sure you address that.

3. Map Your Stack

At this point, things begin to get technical and practical at the same time.

You need to have your data in the correct format that you need it in and when you need it.

Map out your stack in your data management plan. Outline all the tools you need if you’re to control your raw data from every department across your organisation, as well as reports that’ll help your teams make more data-driven decisions— ultimately mapping up all the steps in between.

To figure this out, you might consider the following:

  • Data collection should be standardized and consolidated.
  • Create a data storage solution that is long-lasting, scalable, and secure.
  • Allow users to conduct self-reporting and analysis.

Once you’ve extracted relevant data points, then it’s time to clean your data. This will likely include deleting any weird characters from your data as well as performing some mathematical transformations before you can load your data into any data warehouse. The entire process is referred to as Extract, Transform, Load (ETL).

4. Ensure Your Data Storage Solution Is Scalable And Secure

This entire process from start to finish isn’t something you want to be doing every few years. It would help if you approached it with a long-term view. Therefore, your data warehouse needs to be secure and arranged to be scaled up when the need arises without any problems and in ways that make it easy for someone to ‘walk’ through its aisles and find data both quickly and easily.

Conclusion

In many ways, your organisation cannot begin to hit most of its milestones, at least not quickly, while most of its teams operate in silos. Breaking down those silos will mark a critical point in your organisation’s growth curve, and data will be a vital tool in how you centralize your processes.

Tech Cults
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