Transforming data from pointless to practical
What could you be doing with your data?
Many companies invest in collecting data, but to what end? Today, data is being amassed at ever-increasing rates by governments, multinational corporations, not-for profit organisations and even small business.
Data comes in different forms, including numerical or text-based. Numerical data might come from things like measurements or points scored, whereas text-based data might come from demographic information like age, gender, location or interests.
Organisations are always trying to figure out how to use what they collect in a practical and meaningful way. And many are only scratching the surface.
The most important thing to remember is that data on its own is often useless. It’s when you add context, by comparing it with other data sets or benchmarks, that you get insights. And once you have those insights, you can take-action. Data is a catalyst!
What data do you have at your fingertips
It’s possible you have a variety of data available to you without even knowing it. From internet usage to the number of steps taken in a day, there are hundreds of data sets organising and controlling the information around you.
If you work in a school, you may have access to:
- Student demographic information
- Power usage data
- Academic or sporting achievement data
- State or national benchmark data
- Qualitative data from interviews or surveys.
Of course, it’s important to understand the restrictions around accessing or sharing certain types of data, particularly personally identifiable information such as student names, addresses or sibling names. Depending on your internal policies (which should be guided by relevant legislation), you may be able to view or use basic demographic data.
Interesting ways data has been used
Google brought together cloud computing, geo-mapping and machine learning to tackle a global problem. By using AI and satellite data, they took on illegal fishing. They started with maps containing 22 million data points showing where ships are in the world’s waterways. Engineers from Google then applied machine learning to the data, allowing them to identify why a vessel was at sea. They ultimately created a tool called the Global Fishing Watch. It shows where fishing is happening and allows authorities to identify illegal fishing activity.
France is leveraging big data to improve staffing in hospitals. The pilot program uses 10 years’ worth of hospital admissions records, which data scientists processed using “time series analysis” techniques. This allowed the researchers to see relevant patterns in admission rates. Then, they use machine learning to create algorithms that predict future admissions trends as accurately as possible.
Australia’s state and federal governments share significant amounts of anonymous data publicly as open data. Businesses and individuals can easily access this data at no cost. The data can be used to create economic and social benefits, and events like hackathons and Startup Weekends regularly shine a spotlight on these opportunities.
How can you turn your data into actionable insights?
Data is only half the story. A list of values or answers presented in isolation doesn’t tell anybody anything. But when you use it to answer a question, identify a problem, or solve a problem, data becomes much more helpful.
Start with a hypothesis
One way to approach a set of numbers is to begin with a hypothesis. For example, you might surmise that your school’s poor solar power generation is because you’ve had a lot of cloudy days recently. From there, you can examine weather data alongside solar generation. It could also be helpful to look at other schools in your area to see if their solar generation is performing similarly.
Once you’ve collated the relevant data, you can examine it to see what the reality is. In this example, you might notice that there actually weren’t many cloudy days. Or perhaps there was some, but other schools didn’t experience similar drops in solar generation.
After you’ve examined the data, you can draw a conclusion. The conclusion in this scenario may be that weather isn’t causing your poor solar generation.
The final step is your action. If weather can’t explain the occurrence, you’ll need to do some digging. Whether it’s dirty panels, damaged wiring from a storm or something else, the data shows that further investigation needs to happen.
Identify or solve a problem
Another way to apply your data in a practical setting is to identify a problem. If you have a pain point, you can often use your data to understand the problem more thoroughly or even identify a solution.
For example, you might notice that while children are enthusiastic about the school’s sustainability program, parents are more difficult to get on board. The problem statement might be ‘parents aren’t engaging with or supporting school sustainability initiatives’.
You can use demographic data to infer why they might be reluctant to be more involved. In suburbs where both parents are likely to be full-time workers, it might be a simple case of being time-poor. In other suburbs, topics like sustainability might be a lower priority for parents struggling to make ends meet.
In this case, data might also be the solution! If you can understand what the barriers to engagement are, then you can come up with ideas to reduce the obstacles standing in the way of their involvement. To allow time-poor parents to get on board, you can trial initiatives that actually make their day easier, or at least require little extra time from their day.
Data is an incredible asset to your school
Whether you’re using it to educate or looking for ways to use data to improve your school’s environmental footprint, there’s no denying the opportunities data presents.
With an inspiration and experimentation, data can be applied in many different situations to bring about real impact and change.
