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– yet research shows slow progress up the data maturity scale


More than three-quarters (77%) of businesses now rely on data for planning and forecasting, according to an MHR Analytics survey.


Yet progress along the data maturity scale is slow, with initial findings from the Data Maturity Quiz indicating that most businesses are still stuck in the early stages.


The quiz is a diagnostic tool that assesses the extent to which organisations are optimising their data to achieve goals. It provides guidance on overcoming barriers to climbing the data maturity scale and has so far been completed by over 150 medium-to-large organisations.


Findings from those completing the quiz to-date show 68% are now fully committed to harnessing analytics to make evidence-based business decisions.  But nearly half (43%) of respondents are struggling to determine what big data initiatives to measure, and 60 percent don’t have a strategy to improve the level of insight from their data.


Two thirds (66%) remain in stages one and two (the operational and descriptive stages) of the five-stage scale:


STAGE 1 – Operational. Reporting is limited to tasks that are critical for business operations, with no formal BI (Business Intelligence) and analytics tools or standard in place to support this, and spreadsheets used as a primary means of reporting.


STAGE 2 – Descriptive. BI and analytics are in their early stages of implementation and are used to report on activity.


STAGE 3 – Planning. Using tools like scenario planning, BI and analytics are used not just to report on what’s happening, but to plan for the future.


STAGE 4 – Predictive. Data analytics is used to predict what will happen five, ten, even twenty years from now and to pinpoint the key drivers of trends.


STAGE 5 – Prescriptive. Users no longer have to input variables into the system to predict future outcomes. Instead, Machine Learning and AI make it possible to detect issues before they’re even considered.


“Many surveys show organisations are well aware of the benefits of the planning and predictive capabilities they couldbe using, particularly within finance and accounting functions, but most are not adopting them yet, despite evidence that those who progress further along the journey soon reap the rewards,” said data maturity expert Laura Timms, product strategy manager at MHR Analytics.


“It is often data quality issues that prevent businesses from climbing the data scale as quickly as they would like, and that is where investment should typically be focused – in collating and coordinating existing data sets to enable much more valuable systems to be implemented. A recent PwC survey showed the main *challenges to implementation for 62 percent of businesses were data silos or organisational silos.”


“The results mirror what we see when working with our 750 customers around the UK as well as overseas. Spreadsheets and the manual work that comes with managing them are still blighting data quality and business processes, making it difficult for organisations to break down silos and obtain a clear picture across their business and progress to the further stages of data maturity they need to compete.”


The MHR Analytics Data Maturity Quiz produces practical steps to improving data maturity and aims to demystify some of the jargon about data and provide a no-nonsense diagnosis.



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