A common problem for the majority of housing providers is that due to the plethora of business applications that each of them typically has, even a simple query such as ‘how many properties do we own or manage’ may result in different answers depending on which application is being used.
The phrase ‘a single version of the truth’ is commonly used to describe this problem, most frequently caused on the one hand by the same data-fields and data being duplicated across different applications, and on the other hand by data being manually processed, manipulated and analysed using ‘offline’, standalone spreadsheets on individual PCs and laptops.
In the case of duplicated data fields, how can a housing provider know which application has the correct figure for, say, ‘number of occupants’ or ‘number of completed repairs’? And if the figures are different, why are they different?
And for ‘offline’ spreadsheets, consider the example of a financial analyst at a housing provider being tasked with calculating depreciation schedules for its housing stock, taking into account the changing ages and demographics of its tenant population. In order to do this, the analyst might have to source data from multiple systems and then consolidate those data-sets into a spreadsheet on his desktop. Aside from the complications of actually combining the data in the first place, that spreadsheet is then prone to errors due to becoming immediately out of sync with its parent applications’ data.
The quest for ‘a single version of the truth’ isn’t necessarily about best-of-breed applications vs. a single ERP-style application, it’s more about streamlined data engineering so that the same information is captured as infrequently as possible, along the lines of ‘enter once, use many times’.
