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Month: January 2022

Beware the Data Ditch!

Market research of global data maturity reveals the negative commercial impact of ill-planned investments in data projects and why companies get stuck in the “Data Ditch”

More businesses have started to invest in their Data Maturity and have begun their journey to make smarter, wider use of their data. However, more than half of those businesses are in the “Data Ditch”. Measured by more than 10 metrics of business performance, they are worse off than if they had not bothered.

Meanwhile, a third of businesses have come out the other side and have seen dramatic upticks to their performance.

Stats from the Calligo's Data Maturity Report

and more…

These are the findings of our Data Maturity Impact Report.

The report is unique market research into the progress made by mid-tier organizations and enterprises in their use of data. The report also shows the commercial impacts seen at the various stages of development.

500 NA & EMEA respondents

Data Maturity Impact Report Map shows UK, Europe and North America

…spread from SME to Enterprise

*All respondents were confirmed to be part of the data leadership, predominantly Director and C-level

A shift to the right

One of the principle high-level findings was that since we performed a similar investigation in 2019, there has been a noticeable surge in the number of organizations pursuing greater data maturity.

This is perhaps unsurprising. Business commentary has been dominated by discussions of the untapped potential of data for organizations of all sizes, so naturally, the business world has responded.

The struggles of 2020 and 2021 only put this into sharper context. Oganizations that had invested in better data infrastructure were not only able to adapt to remote working more immediately, but were also in a stronger position to adapt to the new market dynamics. Those that couldn’t struggled to survive.

Data Maturity Impact Report - A shift to the right

Misplaced confidence

This highlights more than just an overconfidence. More importantly, it also shows a lack of appreciation of two things: what is actually required to be truly data mature and particularly to structure data so it can be fully exploited and interacted with safely. 

If so many people consider themselves to be fully mature, but so few truly are, clearly there is a disconnect in businesses’ understanding of what it means to use their data fully.

This supports the main finding of the report: the appearance of the Data Ditch.

The Data Ditch

Does it matter that so many organizations are overconfident in their data maturity and so underappreciative of how far they really have to go?

Isn’t it just a misalignment and a sign of naivety that is quickly solved with greater education?

Yes, in part. But in the meantime, businesses are suffering. More than half of businesses are in the “Data Ditch”. They are creating their own substantial and wide-ranging downturns in almost every performance metric.

Data Maturity Impact Report - Graph

By every metric of business performance, businesses that have only reached mid-maturity are worse off than those that have not even started on their data journey. This includes financials, ability to bring new ideas to market, NPS scores and customer retention, technical performance, employee retention and even measures of human relationships. And more.

But when organizations “skip the data ditch” and reach the latter stages of maturity, every performance metric soars.

Assess your own data maturity

Use the interactive visualization to benchmark yourself against your peers and learn how to avoid the Data Ditch

What are the best performers doing that those in the Data Ditch are not?

Simply put, they are taking a more strategic approach.

Further analysis of those in Stages 5 and 6 shows that they perform extraordinarily well in four key areas – the same four key areas that those in the Data Ditch underperform in:

  • Data Goverance
    The foundation stone for any advanced use of data, and arguably one of the least understood and most overlooked. Built on a clear vision for how data should be used; followed by a strategy for how data should be structured, stored, architected, treated and protected.
  • Data Ethics
    A detailed understanding of every source and type of data, its workflows and purposes, and the data privacy regulations and ethical considerations that apply.
  • IT Security
    Proactively combatting the wider threats that come with greater data use, both internal and external – and in a way that does not obstruct or restrict data interactions.
  • IT Architecture
    The proactive planning and provision of technology resources that support the ambitious use of data, securely and cost-effectively.

There is a common thread that runs through all four of these: they can only succeed if closely aligned with the strategy of the business overall.

Data governance has to create a structure for data that supports the overall and specific ambitions of the business. It provides the foundations to meet its regulatory and legal obligations, and supports IT security. Data ethics ensures that every data interaction complies with the organisation’s legal and moral obligations. And excellence in IT architecture depends on proactively aligning resource demand, tools and cost with the organization’s objectives. Strategic alignment underpins them all.

And this is the key lesson for any business embarking on their data journe. Including those who are already in the Data Ditch. Skipping across it, or escaping it, depends on putting these four foundation stones in place first, and thoughtfully. It is demonstrably the most valuable time spent.

After all, if they are underserved or if shortcuts are taken, then this research confirms that the outcome is painfully certain. Read the report and interactive visualization here.

 

Data Strategy Assessment

A step-by-step path to avoiding the Data Ditch

Let Calligo’s expert data strategists assess data’s role, use and application in your organization, and design a custom, practical roadmap to mitigate every risk and realise every suitable opportunity

The Data Maturity Impact Assessment

Revealed for the first time:

The commercial impact of organizations’ investment into the intelligent use of data – and the consequences of doing so unadvisedly

Beware the ‘Data Ditch’!

Almost all NA and EMEA mid-tier organizations and enterprises are actively investing in their Data Maturity and aiming to maximise the value of their data.

But insufficient resource, investment and skills in critical areas such as data governance, engineering or safety means more than 50% are actually performing worse than the “data laggards” they have “outrun”, and certainly worse than those who excel in the strategic and intelligent use of data.

These organizations with data initiatives built on unstructured and unsafe foundations suffer from:

  • Inaccurate and inefficient data analytics and data science, impacting productivity
  • …and speed to market
  • …and customer satisfaction and retention.
  • All of which creates employee dissatisfaction
  • …and harms the internal perception of the data leadership.
  • While the wasted investment negatively impacts profitability.

This is the ‘Data Ditch’ – and the chances are, you are about to slip into it.

How the research was built

500+ NA and EMEA mid-tier organizations and enterprises were assessed in each of the 8 key pillars of Data Maturity, and self-rated their business performance across 10 metrics.

The 8 Pillars of Data Maturity

Data Ethics

Data Governance

IT Architecture

IT Security

Privacy by Design

Collaboration

IT Cost Management

Data Insights

The 10 Business Performance Metrics

Gross Profitability

Productivity

Security Confidence

Compliance Adherence

Speed to Market

Ability to Innovate

Customer Satisfaction

Customer Retention

Employee Retention

Internal View of Data Leaders

Data Warehouse vs Data Lake – Which Is Best?

While both data warehouses and lakes are big data storage solutions, they are useful in distinctly different situations. Data warehouses store structured data that can be accessed and interpreted by anyone with permission to do so, whereas a data lake is an unstructured storage space for large quantities of raw data.

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