More than 80% of organisations polled by Seequent say data management is critical to their organisation. Yet less than a third have a proper framework in place to do it. Why the disconnect?

In our recent Seequent Evo Webinar, three industry experts – Liv Carroll (MD Applied Intelligence Mining Lead, Accenture), Jody Conrad (Founder and CEO, Krux Analytics Inc), and Vicky Corcoran (Principal Engineering Geologist, Atkins) – discussed why data management in the Cloud is still moving so slowly, in an industry that should be racing to embrace its benefits.

Every journey starts with a first step. But when that journey involves moving your data to the Cloud, is the first step just too daunting for many geoscience-based businesses?

There’s certainly a willingness to look at data management differently and to leverage the Cloud. We saw that in our survey. But in truth, people are struggling to know where to begin, and there’s a (misplaced) belief that it has to happen in one enormous stride if the effort is going to be worthwhile.

“And that’s just not true,” says Jody Conrad. “You don’t have to move everything at once.”

“In fact having as variable or dynamic a model as possible is going to provide you with better results. So start with small chunks.”

The days when every transformational project had to be massive (and likely cost millions) have passed. It’s now much simpler to take an iterative approach, agreed all three panellists. Look at what the business needs are, and move at a pace that suits; that is comfortable; and which can be supported by a prudent budget that allows for prioritising at every step.

Accept that the real world may want you to go slowly

The advantages of the Cloud have been well rehearsed: accessibility to your data on the go, more processing horsepower that brings Machine Learning and Artificial Intelligence (AI) within reach, the potential for reduced costs, and the benefit of a single source of truth where collaboration can thrive.

However, for many organisations reliant on geoscience data, the reality may be different. For scattered stakeholders with poor connectivity, communicating via the Cloud can be a challenge. Team members in the field may not want to risk a wasted day so instead fall back on the comfort of everything already downloaded on their laptop. That’s important, because unless everyone feels certain their data will always be there for them, it can be tough to get cloud-based data management to ‘stick’ within a business.

“Being able to flex how you use the Cloud and having a hybrid approach can therefore be super valuable to organisations taking these first steps,” says Liv Carroll

A combination of the Cloud and on-premises servers that plays to the best of each world will deliver a smoother transition, with less chance of rejection across the business.

It’s also important to remember that digital transformation is not – or at least is no longer – about technology. It’s about purpose.

“There was a time when everybody was excited about digital technology, and they were all looking for nails to hit with their digital hammer” recalls Liv. “Unfortunately, it wasn’t a very useful approach… Hard to scale, definitely hard to maintain, and not actually effective at extracting value from data.”

Find your purpose and your route will come
Digital for digital’s sake isn’t the answer. There has to be a purpose, and that is to extract the maximum possible value from the data you have; not just by getting it into the hands of the people who need it, but doing so in a form they can easily use. Consequently, the Cloud has to be about more than connectivity. It needs to offer solutions around interoperability and the creation of insights through advanced analytics and AI.

“Have a plan for your data, and how you’re going to manage it,” says Vicky Corcoran.

“Some organisations are very data focused, but they don’t necessarily plan how they’re going to manage that data throughout its lifetime – the journey it’s going to go through, and what they want to come out of it.

“Because if you’re managing data poorly, moving it from one software package to another, working in multiple databases that all have to be aligned, then you’re really wasting a lot of time.” Plus, there’ll be errors and inconsistencies that will take even more time to correct.

“Even within each data set, you still have to ask yourself how you are normalising or standardising that data,” adds Jody Conrad. “If you don’t; if you’re not comparing apples with apples, then you can’t draw any real insights from it.”

Scale is about more than storage

The issue of scale vs cost is also one not always fully appreciated. The most commonly quoted example is the ability to raise or lower your Cloud storage dependent on the amount of data you have, and therefore only pay for what you need as you need it. For some that’s a boon. But many organisations dealing with geoscience data will only ever be adding to it, so the opportunity to scale storage back down again may simply not materialise.

However, scale is also about processing power – the capacity to handle heavyweight calculations when the job demands it. Boosting the storage of your on-premises servers with an extra memory card is relatively easy, but upgrading their processing power is a significant capital cost. This is one area where the savings of Cloud scale can be more substantial, while the liberation of being able to crunch the big numbers whenever required can help drive the business.

“Whatever you do,” concludes Liv Carroll, “do something.”

“Because there’s a huge amount of value to be added, and that’s not just monetary value. It can be health and safety, ESG metrics, workforce satisfaction, attracting digitally agile talent, and so on. The Cloud can open all that up for you.”

To hear more of what our experts had to say about Cloud security, common data management problems and their fixes, working with legacy data and more, you can watch our full webinar in the link below.