One of the key benefits of an enterprise cloud platform for back-end functions is the potential it offers to integrate the data that informs those vital, but non-mission-critical, tasks.
In this way, organisations can gain a much more granular view of their structures, financial health, talent, performance, productivity, efficiency, and other key metrics - one that can be sliced, diced, and interrogated to extract maximum value from the underlying data.
But how many such systems are integrated at present?
A mixed bag
An exclusive Computing research survey of over 150 data and IT decision-makers in enterprises across most professional sectors of the economy found a very mixed picture.
Asked which of a range of descriptions most closely matched their HR, Payroll, Finance, and Accounting systems, 17 percent of respondents reported minimal automation across what are still largely standalone operations.
Just over one-quarter of respondents reported limited integration and data sharing between some, but not all, of those applications, while one-third of the professionals surveyed described moderate integration and data-sharing between most of the systems.
This left just one-quarter of data and IT leaders reporting that those back-office functions are "completely integrated". As a result, Human Resources Management System (HRMS) users are able to access any Finance or Payroll data in real time when they need it, and this same principle applies across all of the applications.
So long, silos
That one-quarter of organisations have this level of enquiry and analysis within their systems in the cloud is inspiring and good news for UK productivity and efficiency. As a result of that integration, managers can not only see how the organisation is performing, but also ways in which their resources could be put to better, smarter use.
However, the survey does reveal that in a majority of organisations - three-quarters of them, in fact - applications and data are still at least partially ‘siloed'.
While decision-making has become more data-guided in an impressive 83 percent of enterprises - those reporting some level of back-office automation and integration - for many this still falls short of them being able to extract maximum value from their data.
However, siloing is only part of the problem, suggests the survey. Another is the separation of data analytics from the data itself. According to Computing Research, just 12 percent of respondents report having full embedded analytics, with transactional and analytical data available within the same system.
The remainder are struggling with extra modules that offer limited analytics (40 percent of respondents), or report strong analytics being available only as an extra module (36 percent). Twelve percent use a completely separate analytics platform.
Adding value at last
It is often said that back-office functions are essential to the smooth and efficient running of the enterprise, but add little extra value to them. This is why many organisations have outsourced them in the past, regarding them as commodities that can be stripped out of the enterprise and passed to the lowest bidder.
But that is no longer the case: having access to a cloud platform that integrates formerly discrete functions and data allows in-house professionals to have a much more nuanced and informed view of the enterprise - one to which they can begin to add value.
However, back-office Accounting or HR staff do not necessarily have deep, specialist skills in data analysis and data science, though it is likely that such hybrid skill sets will soon be in demand. Either way, cloud platforms need to be easy to work with and present data in an accessible and comprehensible way.
Nearly half of the leaders surveyed (48 percent) reported a "reasonably" easy toolset to work with. However, nearly one-third (31 percent) of all respondents said that this is not the case and they often have to bring in their data teams - specialists who would be better deployed working on more strategic tasks.
Put simply, today's data analytics tools are failing to deliver if they do not make it easy for non-data-scientists to do their jobs properly.
Almost half of survey respondents have specialised teams located throughout the business, 40 percent have a dedicated central data science/analyst team, and 44 percent have a limited data democratisation programme in place.
Only 25 percent of the survey's respondents enjoy full data democratisation, where non-analyst users can access all the relevant data, visualisation, and analysis tools. This means that three-quarters of the professionals Computing surveyed lack vital insights into their business.
It doesn't have to be that way.