Do you spend too much time and resources preparing data?

Bilde av Jarle Soland
by Jarle Soland

01. Jun 2021, 4 minutes reading time

Do you spend too much time and resources preparing data?

We define data preparation as the process of collecting, organizing and submitting data in ways that make them actionable. As this is crucial for making informed, data-driven decisions, you want to make this part right. But do you spend too much time and resources on this process? The answer is probably yes, and here is why.

Almost as certain as death and taxes, is the fact that organizations have their inefficiencies. This is true of companies across the entire spectrum of digital maturity. Luckily, most time-wasters can be eliminated – you just have to find them.

 

What is holding us back?

There are many reasons why manual processes persist, sometimes despite new technology that could automate them. One major reason is job protection: People keep doing things the way they always have. As long as they stick with their tried and tested technologies, their jobs are as safe as they are predictable. 

However, few actually find these repetitive tasks rewarding. But what if, instead of spending 6 hours putting out fires and 2 hours developing the business, you could flip that ratio? Not only would it not mean the death of your job, but your workday would also be vastly more interesting, enjoyable – and valuable.

 

Fallibility of man

The drawbacks of spending human capital on work that could be automated, like reporting data, are many. One is that the employees tasked with generating the reports you require, probably have their hands full already. How often have you not had to send a reminder to your overworked IT department? 

This ties into the problem of key person risk, which ultimately may cripple your organization’s productivity if not properly managed. Also, with manual extraction of data, quality is almost inevitably lower. Many mistakes that we fallible humans do, computers simply do not. The more manual processes, the greater the risk of error.

The last point we will make here, is that if you spend too much time getting the reports you need, it might already be too late when you get them. Data is incredibly powerful as real-time decision support, which means that speed is crucial. 

 

Inefficiency – a case study

But how do you actually know if you are spending too much time and resources reporting data? Well, a while back we ran a project with a prospective client that owns oil and gas licenses in the north sea. Because they are in the business of extracting as much value as possible from their licenses, they are monitoring production closely – and are dependent on a vast amount of data from the field operators. Some of it internal, some external.

So we ran a self-assessment. Who actually has which information – and where do they get it? What we found was a significant overlap in work done across employees. Put bluntly: People were reinventing the wheel, in some cases even 4 or 5 times. This alone added up to more than a man-year of labour in a fairly small organization.

 

Find your weaknesses

This leads us back to the question: How do you identify if or how you are wasting resources?

Your very first step should be to map out the entire flow of information – and make an assessment of whether or not this is optimal. Ask yourself: When a new analytic need arises, how long time does it take to acquire the information you need? And how does this connect to the data flowchart? 

This should give you a picture of pain points and inefficiencies, and most importantly jumpstart the crucial work of developing data governance. With proper routines and guidelines for who owns what data – and how they should move between silos and people – you are significantly better positioned to make reporting more efficient. 

And with proper data governance in place, you have a framework wherein you have access to higher quality data more quickly – creating a more dynamic and agile work culture.

How to make more strategic corporate decisions based on data

Jarle Soland

Jarle Soland

Chief Executive Officer

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