The Hark data science squad are held in high regard around these parts, and for very good reason. Their insights into data analysis allow a much more refined and efficient way to process energy/asset information. Sure, actually getting hold of the data is considered the “hardest part” of any digital transformation – but doing the right things with that data… Well, that part is invaluable.
I recently got in touch with data scientists, Angus Doherty and Victoria Mawson, to pick their brains on remote monitoring best practices. Happy to oblige, the pair have curated a list of 7 brilliant tips for maximising the efficiency of your data collection and analysis strategy. So with no further ado, check out the list below:
1. Define your objectives to help you understand what you’re looking for
Knowing why you’re monitoring data is, as you might imagine, the most important factor for positively impacting your operations. Trying to reduce your carbon footprint? Want to maximise your factory’s yield? Perhaps a shorter energy bill is what you’re looking for? Well, whatever you’re trying to achieve, define your objectives first, retrieve/analyse your data and then start implementing processes to support the objectives you’ve set.
2. Ensure accurate and reliable data collection
Your data is no good if it isn’t accurate, make sure your data is collected in a way that is always precise and correct. In other words, don’t send Jeremy The Engineer around the estate with a clipboard and a spanner – instead, consider using sensors. Sensors will reliably collect your data, without the risk of human error.
3. Develop a model of expected outcomes
You’ve defined objectives, but what are you expecting the results to look like? What changes would you like to see happen as a result of remote monitoring? Figuring this out will get you one step closer to achieving it.
4. Analyse by comparing the expected outcomes against the actual outcomes
Were your expected outcomes way off? Compare the actual results against what you thought would happen to help define your future remote monitoring strategy.
5. Automate analysis where possible to increase time spent implementing changes
While analysis is key, actually making changes is what will ultimately save you money and reduce your carbon footprint. More time making changes = more efficient ops. In order to free up this extra time, you can automate analysis by setting triggers and alerts. When using a data analytics platform (like The Hark Platform), once a threshold is breached, you can alert the relevant people, prompting them to take action swiftly.
6. Frequent and consistent data collection
Depending on the situation, data collection will need to occur at certain intervals and should ALWAYS be consistent. When data is collected once every 30 minutes, for example, there’s essentially a 29-minute blind period in which valuable data could be lost. In these instances, data must be collected much more frequently: 60-second data collection means nothing will be missed and your data will be of much higher quality.
7. Simplify the output
Feed your data into easy-to-understand graphs and alerts. Using software like the Hark Platform, you can create a custom dashboard that delivers your information in the best way for you. Rather than presenting a thousand datapoints to the user, you can easily see where the issue is and what the issue is.
By taking these recommendations into your organisation you can expect to maximise your data and, as a result, reduce costs, maximise yield and increase efficiency/sustainability in all areas you monitor. For more information on how to connect to assets, visualise data and use that data to operate more intelligently – just get in touch.