Your organization is drenched in data. If you’re a leader in a defense or security agency, it’s becoming more and more common that those at your level have access to all kinds of data about your organization – personnel data, budget data and competitor data, just to mention a few.
The challenge lies in the data’s usefulness: How do you as a leader put all of that data to work for your organization? How do you make useful decisions with the data? How do you correlate the data appropriately so that it actually drives your organization forward?
The answer is to adopt a process improvement approach. You already know the basics of process improvement and data analysis tools, so it’s time to move beyond the basics and approach your data analysis at an advanced process improvement level.
Assess Data Quality
Before you’re able to dive into data-driven decision-making, you need to assess your data quality. Data quality means you’re sure that you have the right data for the decision, that the data is organized properly and that your data contains quality information. Without quality data, it’s impossible to have any confidence in your resulting decisions.
Frame The Issue
In order to follow a process improvement approach, you need to frame the issue, question or decision point before you dive into your data analysis. Usually, the best way to frame an issue for further data analysis is to adopt a hypothesis-driven approach.
Creating a clear hypothesis ensures that your data analysis is focused, reliable and time-efficient. Once you begin, you must only focus on collecting and analyzing data that is directly related to proving or disproving your hypothesis. The focused path of a hypothesis-driven approach reduces wasted time on unrelated data and ensures that your data is more reliable by being directly related to your given hypothesis.
Align Data And Strategy
Advanced data analysis doesn’t happen in a vacuum. Instead, you need to structure your data analysis tools so that they’re applicable to the overall strategy of your organization. In other words, your data strategy has to tie into your overarching business strategy.
For example, imagine that your defense agency wants to tighten its budget in anticipation of new legislation. Like most defense and security agencies, you probably collect a significant amount of data regarding your budget, but are you leveraging that data to help you achieve your goal? Once you do, your data analysis is much more effective.
Use Data Analysis Tools That Harness Scenario Modeling
Not all data analysis tools are created equal. When looking for the right decision-making tools for your defense or security agency, keep in mind that your data analysis tools should be:
- Simple and straightforward to use
- Appropriate for data visualization (particularly for executive leadership)
- Aligned for swift and simple scenario modeling
While ease of use and simple visualization have been covered elsewhere, don’t forget the last criteria: scenario modeling. Robust data analysis tools allow you to create different scenarios and model the various results, letting you experiment with the “what-ifs” of your organization or industry. Scenario modeling gives you the data analysis you need ahead of time when you ask questions like, “What if insider threat legislation tightens up security compliance?” Conducting the data analysis on these types of questions before circumstances change allows your organization to be more flexible – and responsive.
These are just a few more advanced approaches to keep in mind when conducting data analysis at your security or defense agency, but when you put these techniques into practice, you fuel the kind of process improvements that drive your organization confidently into the future.
You don’t just need data analysis to distill your information into charts and graphs – you need in-depth analysis that drives success. Click below to download a free tip sheet from Big Sky Associates and discover how to harness better data-driven decision making for your organization today.