EDITOR ’ S QUESTION

HOW CAN IT LEADERS EFFECTIVELY OVERCOME THE CHALLENGES OF DATA COMPLEXITY TO DRIVE SIGNIFICANT BUSINESS VALUE ?

A new report from Appsbroker & CTS revealed businesses use less than two-thirds of their ‘ data brain ’, showing that lack of timely and accurate data is leading to missed reporting deadlines , customer complaints and bad decisions . We get insights from Chris Gorton , EMEA Managing Director and Senior Vice President , Syniti ; Jason Beckett , Head of Technical Sales EMEA and CTO , Hitachi Vantara ; and Rajesh Ganesan , President , ManageEngine .

The data maturity report , Making the Most of Your Data Brain , revealed most ( 91 %) of the 150 UK IT leaders surveyed said they have a specific mandate from their board or executive team to make their organisation more data-driven and data-centric . However , almost three quarters ( 73 %) still struggle to transform data into delivering significant business value . Key findings include :

• Not firing on all cylinders : Businesses are using less than two-fifths ( 39 %) of their data brain – with 69 % admitting to hoarding data in data lakes and using just a fraction of it .

• Data friction persists : 88 % of organisations said they face hurdles to becoming data-driven , with the top-ranking issues being IT and data complexity , legacy systems and a lack of skills and resources .

• Data citizens left out in the cold : 87 % of respondents think empowering citizen developers will help businesses overcome the data skills gap , but 81 % lack the skills and know-how to enable data citizens .

This lack of access to timely and accurate data has serious ramifications for businesses , as 39 % confirm they have overspent or underspent on projects . And as far as they are aware , 37 % of respondents have made decisions based on inaccurate data , and 36 % have made inaccurate forecasts – although the true amount could be even higher .

Furthermore , 31 % have suffered customer complaints , 31 % have delayed product or service launches , 27 % have missed reporting deadlines ( including businesses from heavily regulated sectors such as financial services ) and 25 % have missed revenue opportunities .

“ Leaders are using data for big business-defining decisions , so they ’ d better be confident that information is right ,” said Matt Penton , Head of Data and Analytics at Appsbroker & CTS . “ Reporting bad numbers can have very serious and public repercussions , and customer complaints can quickly lead to churn . Unless you ’ re selling grated unicorn horns , customers can and will go elsewhere . These are the tangible costs that can sink a company when data is used ineffectively .”

IT leaders reported using over 30 different data sources on average . As the volume and complexity of data architecture increases , many businesses are struggling to keep pace :

• Less than half ( 46 %) of IT projects that rely on data run on time , within budget and to the intended scope – a source of frustration , stress and cost for internal teams .

• Despite the move to more open technology stacks and APIs , 81 % of IT leaders say integration issues still plague the IT industry – with 79 % lamenting that ‘ it ’ s near impossible to get a single organisational view ’.

• Three-quarters ( 76 %) say the complexity of their data architecture is increasing exponentially . As a result , 85 % say associated costs are increasing every year , and 69 % say it is becoming increasingly difficult to manage .

While complexity will inevitably continue to grow , Penton argues this doesn ’ t have to result in ballooning costs and confusion – simplification is the key : “ Don ’ t try to boil the ocean – start with a smaller data set and then expand to ensure you are getting things right , and doing it in a timely manner . Complexity isn ’ t going away , but automation , common tooling , low-code and no-code can make it easier to manage data .

“ By taking a structured and realistic approach , speaking with experts and deploying the right tools , every business can unlock the power of their data brain .”

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