How to be Data-Driven, and Not Just Data-Busy

Like almost every other, your organisation is probably on a journey to drive more value from its data in the form of better insights, increased automation, digitised business models, artificial intelligence, or even entirely new data products. 

The phrase ‘data-driven’ has become synonymous with this push for greater data value. But whilst striving to be data-driven, many businesses unwillingly end up being just ‘data-busy’. 

What does that mean? Quite simply, a data-driven business is one where data value is higher than data effort, because data is cost-effectively driving the business towards achieving its goals. Data-busy is of course the opposite. It’s where data effort is high but data value is low, because despite a lot of hard work and data investment, data isn’t really helping the business to achieve its goals. 

Naturally, no business wants to be data-busy. But it’s an easy trap to fall into. So how can you tell the difference? And how can you avoid it? 

Signs That Your Business Is Data-Busy

Do any of the following situations sound familiar? 

  • You have a centralised data team, BUT they spend a lot of their time firefighting data issues. Often the same ones, over and over. 
  • There’s an abundance of reports and dashboards, BUT most of them are seldom used. They’re often used just to export the data, and people don’t really understand or agree on what they are for.
  • There’s an established data operation in IT, BUT that operation is mainly focused on aspects such as technology licensing, data integration, and database maintenance. 

These are just three of several situations commonly found in businesses trying to mobilise their data as a high-value business asset, yet have become stuck on a treadmill of daily data management overheads that seldom seem to deliver data’s true potential. 

How To Not End Up Data-Busy

If this sounds familiar to you, you’re not alone. But rest assured, there are simple and reliable ways to reach the promised land of automated data insights, self-serve analytics, high data literacy, and robust data quality, and ultimately transform your data into a high value business asset. 

Here’s four essential methods for becoming data-driven, and not just data-busy. Read to the end for ways that you can get free information, tools, and templates for putting these methods into action! 

Get a Genuinely Good Data Strategy

No, not one of those strategies which takes months to devise, costs a fortune, no-one reads because it’s three inches thick, and never changes a darn thing! And yes, I know you’re tired of hearing that you need a data strategy. But you really do, because you need a way of getting people in your business to agree on what high data value looks like, and the steps required to achieve it. Maybe you can’t put a data strategy in place because you don’t have the time, budget, or leadership appetite? If you’re struggling to get data strategy on the agenda, then at least document robust terms-of-reference instead and use that as the basis of a common and agreed understanding among stakeholders. But don’t do neither of these things because the fact is, it’s impossible to transform data into a valuable asset without a clear strategy. Trying to do so will lead to you spend too much time and money on the wrong things, and you’ll just continue being (or become even more) data-busy. 

Pinpoint the Jobs Your Data Needs To Do

Don’t give your data a free-ride. It’s not there just so a bunch of people can work on managing it in databases and securing access to it. Your data must earn its keep. Your data operation must evolve beyond a simple cost-centre, by innovating the data outcomes which measurably empower your business to achieve its goals. 

This is about much more than just gathering reporting requirements. You must turn the dial all the way up on exploring and pinpointing ways that data could deliver business benefit. 

There’s only three ways that any business benefits from data. By learning from it, working better through it, or selling it. In other words – data science and analytics, digitalisation and AI, or data commercialisation. Use this as your starting point for building a backlog of well-documented data use cases which are concise enough to reveal which ones go first, because they’re in the sweet spot of high feasibility, low cost, and high value. 

Build Cost-Effective Data Capabilities

Data capabilities are the real-world keys to unlocking data value. They’re where the rubber meets the road. Plainly, if your business is incapable of doing what’s necessary to deliver those data use cases, then you’ll spin your wheels forever and epitomise the term ‘data-busy’. 

Examples of data capabilities are data compliance, data security, data storage, data governance, data visualisation, data analysis, data self-serve, data literacy, and so on… The list of data capabilities is long, and the spectrum of data capabilities that’s right for your business, depends of course on your specific data goals your current situation. 

Ask yourself these questions: 

  • Does our data strategy tell us what data capabilities we need and why?
  • Do we know what strength of data capabilities we’re aiming for?
  • Do we know how strong our data capabilities are today? 

If your answer to any of those questions is “No”, then you need to be concentrating more on data capabilities. Because trying to become data-driven without understanding your data capabilities, is like trying to tune a car without touching the engine. You can put as many go-faster stripes on it as you like, but the real performance isn’t going to change a bit. 

Focus on People, Not Data

The factor which determines the strength of your data capabilities more than any other, is your business’s people. So much of what your business must do to be truly data-driven relies not on technology, but on people’s knowledge, skills, and engagement. 

And when you think about ‘data-busy’, what exactly is it that is busy? Mostly of course, it’s people. Spending time and energy on avoidable, low-value tasks such as searching for data, working around data quality issues, toiling over spreadsheets, and debating conflicting reports. 

So, to put people-power fully behind your data, you first need a data operating model which arranges your data operations into streamlined data production lines, giving you a clear and accountable understanding of what people need to do, when, and where, to minimise data effort and maximise data value. Then you need to overlay that operating model with an organisation structure which defines the roles that people must occupy, as well as the skills, training, and support that they will need. 

This pairing of a data operating model and data organisation structure, is what will enable you to disentangle the melee of manual processes, rogue software, legacy fixes, and data siloes which are a plague on data productivity. 

It’s also important to think about how the people in your business ‘feel’ about working with data. Do they generally feel like it’s a pain in the butt? Or do they find it easy to get the results they’re looking for? By applying this customer-experience lens to the interface between your people and your data, you can see and take control of factors which are weakening people’s engagement with data and undermining data value. 

To find out how we can help transform your business from data-busy to data-driven, get in touch today. 


We should be talking.
It will be worth it.

    Cookie Consent with Real Cookie Banner