Article - Greenbyte

November 4, 2020 — Industry Trends

How data-backed dividends help your investors

Are you having problems with your dividends? Perhaps they’re often coming out too high or too low, and damaging relationships with investors and shareholders. Sounds familiar? Then you might have a data problem.

Matthew Lush
Sales Manager, Greenbyte

Data professionals all know the idea ‘garbage in, garbage out’ – and its more X-rated cousins. This is the principle that your analysis can only be as good as the quality of data you put in. Bad data can lead to bad results throughout your company.

Anyone who’s ever been faced with an upturned trash can knows the pain. Garbage spreads everywhere, takes far longer to clean up than you thought possible, and can cause serious injury if someone slips up on it. Mess isn’t even the half of it.

The same principle applies for investors and operators in the wind and solar sectors.

Strong data is not only the stable basis to run your wind and solar farms at optimum efficiency, but is also the foundation on which you base your financial reports about these projects. These are the reports you share with shareholders, and provide you with the figures to work out those all-important shareholder dividends.

But it’s easy to nod along and say that high-quality data is important. The challenge for companies in renewables is that the people tasked with cleaning up the problems caused by low-quality data – including those on the financial side – aren’t necessarily those who are choosing the data systems that are put in place.

It’s a disconnect that can lead to slip-ups in relationships with your investors.

Data and dividends

This is a topic that came up in a discussion I had recently with a fund manager.

They said that they had found themselves in a precarious position with shareholders on more than one occasion because of the poor-quality data on which they work out their dividends. If those dividend calculations are wrong too often then it can destroy reputations than have taken many years to build, and may never return.

The problem is the same whether dividends are too low or too high.

Now I’m sure we can all appreciate the problem for an operator if the dividends they pay shareholders are lower than expected. It’s rare for someone to be happy to get less money than they thought. The reputational risk here is clear. But paying out too much can also call into question your reputation as a competent financial partner.

The other risk of paying out too-high dividends is that then it becomes money you can’t use for your own operations. You are doing direct damage to your own margins, and your ability to re-invest. It’s not a good position in an ever-evolving industry.

We looked at the role of data in building investor confidence in this case study too.

Therefore, if you work with shareholders who demand rigorous financial data then it makes sense to ensure that the data you get from your assets is rigorous too. It may be the difference between them trusting you or going with your rival.

And, of course, it will keep your own management team happy as well.

Getting quality data

But how can those in financial teams have an impact?

The first thing you can do is recognise that companies are complex organisms. The decisions made by operational teams impact on financial teams, and vice versa. You should feel confident to have a conversation on whether your data is good enough.

We’ve recently produced this buyer’s guide to help you ask the right questions.

The second is making sure you work with a system that tracks data in a rigorous and robust way, and produces the insights you need. It is easy to gain a wealth of data about how your turbines are performing, but you need to be focused on the correct key performance indicators. You can learn about the six vital KPIs in this ebook.

And third, you should look for a system that enables you to improve your data quality by drawing on external sources; helps you access data specialists with engineering knowledge; and uses artificial intelligence that can identify in your anomalies in wind and solar farms before your team or your original equipment manufacturer would.

For example, we bolster our own capabilities by working with highly trusted partners such as Solargis, who we interviewed in this Marketplace Q&A article. And we look to keep evolving as technology changes, including with a looming storage boom.

In short, a system that weeds out bad operational data before the garbage reports start spewing out.

This can save a lot in time, money and shareholder happiness.

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