As COVID-19 continues to have a wide-reaching effect on the business operations of organizations all over the world, we must begin to plan and prepare for an effective post-crisis recovery phase.

This year has provided a series of wake up calls for everyone.

The coronavirus pandemic has devastated lives—quarantine, economic shutdown and a huge reduction in social movement have all compounded the agony, and the knock-on effect is plain to see in business quarters. 

The economic machine has come to a shuddering, grinding halt. 

Understandably, many companies have struggled to comprehend the full impact of the crisis, finding themselves blindsided and with little else to do but stretch their runways as far as possible and wait it out.

Now, as we reach a tipping point in this global saga, redefining business priorities is essential in the recovery process, and data plays a vital part.

How does data hold the key?

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In tandem with a sound fiscal policy to support revenue recovery, organizations with or planning for a data-driven resurgence will certainly have a headstart post-crisis. Data as an asset is priceless. It holds the answers to the questions businesses are asking. 

However, for many organizations, a data-driven strategy may have been previously unimaginable. The route forward may be mystifying and full of uncertainties. Do businesses really need any more uncertainty at this point?

Time, resources and talent all contribute to this uncertainty; embedding a data-driven culture isn’t instantaneous, the resources businesses need to implement data practice can be pricey, and tapping into a pipeline of proven talent doesn’t come for free, but more on that in just a moment. 

Businesses broaching the subject and beginning to explore data strategy might look at these barriers and view a roadmap littered with obstacles. However, data is easier to access than some businesses think.

Technical workers

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There is a belief that technical roles are resilient, a necessity in any modern business generating vast amounts of data, but this doesn’t necessarily hold true anymore as we lurch towards the “new normal”. 

Data departments, and technical workers to a wider extent have been downsized amidst this COVID-19 uncertainty.

Whether it be for worker reallocation, cost-cutting, restructuring or consolidation, the fact is that when businesses anticipate a seismic shift is on the horizon, or find themselves suddenly in one, these workers may be considered not as essential as they were pre-crisis.

Technical knowledge workers, good ones, are expensive, too. For a number of years now, data science has been a mainstay at the top of job rankings. With great pay, job satisfaction, and plenty of demand, it’s no surprise. 

But even before the pandemic, demand tailed off and pay shrunk year on year. Businesses just can’t afford them. Now, in the midst of a global pandemic, this rings even truer. 

So how do businesses react? With smaller data teams or no forthcoming recruitment due to the restructuring and preserving of capital, businesses might wish to consider no-code.

Is no-code a viable alternative?

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No-code, although a relatively modern movement, has been gathering pace for the last few years. However, it’s not a new invention. No-code has been around in some form or another for a long time. We just might not be aware of it.

Every day we perform many codeless tasks, but it’s all “under the hood”, so we rarely pay it any attention. We are able to perform complex computing processes in just a few clicks. 

Take for example a word processor. To change the style of a typeface requires no coding,  just a GUI and some buttons. Everything happens elsewhere and is of little concern for the user. All they want is to reach their end goal.

As previously mentioned, traditional data analysis isn’t easy, it can often be time-consuming, a drain on resources, and costly. The platforms and tools are sometimes convoluted, packed full of unused features, and also require extensive training, often at yet more cost. 

So, when presented with the opportunity to mitigate these costs and these risks with no-code data analysis platforms, organisations can adopt smarter analytics easily, almost instantaneously. No-code data analytics immediately motivates better decision making. Businesses can easily complement that valuable insight with their domain knowledge and human talent—thinkers and strategists—before looking cross-functionally to implement those across the wider business.

No-code tools demystify data, unveiling new approaches to data analytics; ones which don’t depend on worker reallocation, financial outlay, or time invested in new personnel and training. 

It’s time for businesses to get the jump on the “new normal” by adopting no-code data analytics. Beginning to explore solutions and strategies now, to understand the benefits businesses can have with data by their side, will pay off in this uncertain future we all face.

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