Data maturity
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Over two-thirds of firms who have a data strategy, admit that it is not widely understood across the organisation, according to a Mango Solutions study

● 68% of organisations have established data science teams
● 62% of data leaders cite skills gaps or recruitment as core challenges
● 72% of companies say their data quality and integrity requires improvement
● 92% of businesses plan to rely on data to drive predictive decision-making by 2023

14th October 2021 – Mango Solutions, an award winning data science analytic consultancy has announced the results of a study which reveals that while 95% of companies questioned have a data strategy, less than a third of those (29%), claim their data strategy is clear and widely understood.

The data maturity survey, which polled the opinions of 100+ data professionals at the September 2021 Big Data LDN event, shows that the companies questioned are investing heavily in data capabilities, resulting in maturing data functions – for example, 41% have established data science functions in the last two years. 93% of data managers surveyed claim their company has a well-structured data estate and 92% claim to have well established data management processes.

However, the study also revealed that companies are not yet reaping the benefits from their data capabilities. Only 26% of respondents say that the quality and integrity of their data is high and suitable for analysis, and only 43% already rely on data to drive predictive decision-making.

Establishing a data-driven culture is just as important as providing people with data capabilities if companies are to realise the potential value from their data. The Mango survey shows good progress here, since 88% of respondents already have an established internal data community that works across the business and enjoys good stakeholder relationships. However, 56% of those surveyed still feel there is room for improving their data community.

Data science also seems to be delivering on its potential too. Reassuringly, 68% of organisations boast established data science teams that already work effectively with collaborative tools and platforms, with 85% of respondents claiming their business sees value in the function. 29% of respondents say there is room for improvement when it comes to establishing an effective data science function. Effective data governance is an essential part of improving the effectiveness of data analytics and data science functions, and this statistic aligns with Gartner’s prediction that, by 2024, 30% of organisations will invest in data and analytics governance platforms, increasing the stability, scale, trust and impact of insight and analysis.

Predictive decision-making is also a key focus area for data managers, with 92% of businesses claiming they will rely on data to drive predictive decision-making by 2023, more than double the 43% of organisations who claim their business already relies on data to drive predictive decision-making. 59% of companies report that they already successfully derive, share and action insight delivered through dashboards and reports and a further 26% will be following suit over the next 18 months.

Rich Pugh, Chief Data Scientist at Mango solutions, said: “While the majority of organisations surveyed say they have an established data capability, a large proportion admit that they need to improve the way they use it, to help derive data-driven value. These improvements are obviously best done strategically, but whilst 95% have a data strategy, only 29% of those have one that’s clear and widely understood. This is a real concern – creating a clear and understood narrative around the role of data is essential to the success of a data strategy. Without this, data leaders are at risk of not bringing the organisation with them on their journey, and missing out on the potential value of their data opportunity.”

– Ends –


data literacy
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The pandemic has emphasised the importance of a data-led approach and raised the bar for data literacy. Emerging from the crisis, the businesses that succeed will be those that put value at the heart of analytics initiatives.

By Rich Pugh, 24th May 2021, posted in Training Journal

To a large extent, the data that we gather, examine and use to help us make decisions has been kept in the hands of a few data experts with the appropriate skills and understanding to interpret and use to benefit their organisation. This is not surprising; the enormous growth of data has meant that most employees haven’t had the right training or skills to work effectively with data in order to extract the best value from it.

The goal with data democratisation is to enable the development of informed decision-making to a broader set of people. 

This is changing, however, thanks to the advent of technologies that have the capability to support the sharing and interpretation of data for non-data experts. Advancements like these have made it possible to disseminate data throughout the organisation, and that’s a good thing. If implemented the right way, this democratisation of data has the potential to propel businesses to new levels of success.

Dissolving the bottleneck that often characterises the point of entry to a company’s data means that everyone should be able to use it to make informed decisions, faster. Fundamentally, devolving good data visualisation capabilities across an organisation allows decision makers to make more informed decisions, or to identify evolving trends and patterns that may constitute an opportunity or threat.

While data democratisation is certainly the key to transforming how organisations operate, there are challenges to be addressed, specifically around literacy. If you give a lot of data to someone who isn’t skilled at interpreting data, how would you expect that person to discover things?

I believe that’s where data literacy is becoming really important, and by this, I mean teaching the broader business what data is about, how you interact with it, how you analyse it, how you identify a trend, and what to do if you think you’ve found something.

The impact of the pandemic on data literacy

Interestingly, the pandemic has shone a spotlight on data and inadvertently played a role in elevating the data literacy of the population at large. Faced with the Covid-19 crisis that took hold over a year ago, many of us tuned into daily briefings to understand the spread of the virus through data and statistics. During these briefings, ‘descriptive analytic’ approaches have been used to present points and trends, regularly exposing the public to the world of data visualisation (charts showing Covid-19 numbers), summary statistics (such as an R number), predictions (forward-looking projections) and simulations (understanding the projected impact of approaches to ‘flatten the curve’).

This has certainly raised the bar in terms of data literacy, or at least expectations around the richness of information that could be presented to underpin a topic – the public has viewed the pandemic through the lens of data and statistics, gaining familiarity with the use of common analytic tools (charts, statistics, predictions) to better understand what is a complex topic.

Throughout the past year, we’ve seen the link between data and action, with phrases such as ‘we’ll follow the data’ being used to explain to the public the rationale behind the road map out of the pandemic. Indeed, both Boris Johnson and Nicola Sturgeon used the same phrase to say that they would be ‘led by data, not dates’ when it came to making decisions with regard to easing lockdown rules and re-opening the economy.

This has emphasised to the public the importance of a data-led approach when it comes to making informed decisions that are meaningful and valuable.

What data democratisation means for your business

As already mentioned, it is not merely sufficient to foster data literacy across the organisation for the purposes of interpreting data. The goal with data democratisation is to enable the development of informed decision-making to a broader set of people. In a crowded market place, this is what creates smarter, leaner organisations with a competitive edge.

Take the ‘left or right Twix’ ad campaign as an example. The campaign envisaged a world where two companies create the exact same product, using the same processes while selling to the same consumers. It’s a good metaphor for disruptive influences in markets being able to create companies that are very similar to established players, which then have to find some way to compete.

Find out more about upskilling your data science teams here.