Active & Passive Data Governance: How a Collaborative Approach is More Effective for Business?
No data governance, in which the responsibility for data management lies with the user alone and there is no centralised or overarching control. Everyone is trusted to enter the data properly and accurately.
The Centre of Excellence model, in which a central body is tasked with handling all data requests and entries, as well as handling verification.
Passive data governance, in which the user inputs data into the ERP system, and the MDO analytics with the help of business rules, creates exceptions and workflows to ensure data quality.
Active data governance, in which all data is assessed and verified before being inputted to the ERP system to ensure the quality and veracity of all data is directly available to the business.
In most cases, data management solutions will involve one of either stage three or four of this traditional structure. However, adopting such a rigid approach may not be the most efficient means of managing the vast amounts of data which are critical to your business. Instead, a collaborative relationship between passive and active data governance is something you and your team should be aware of.
With this model, all incoming data is screened via the active governance component of the master data management solution, providing an effective first line of defence against erroneous or misleading data. After data has been inputted into the system, passive governance mechanisms automatically screen and assess this information, providing automatic reports on any unreliable data and enabling this data to be removed.
These two functions provide an effective double safeguard against flawed or corrupted data, but the advantages and effects of this approach go further than this. Passive and active governance, when deployed together, work with one another to ensure their mutual efficacy. For example, the passive component of automatic checks ensures that the active component is working efficiently. If the automatic reports are still turning up large amounts of error-strewn data, even with the active checks in place, then active governance policies can be tweaked and honed to make them more effective.
So what does this mean for businesses in practical terms?
Let’s consider manufacturing as an example. A manufacturing firm relies heavily upon its machinery and infrastructure, much of which is state of the art and expensive. If even one of these pieces of machinery is put out of action due to a fault or the failure of a part, the cost to your business can be astronomical.
And how does your organisation keep track of repairs and replacement parts for these machines to make sure they remain in working order? Through the implementation and management of data. If this data is not up to scratch, disaster can strike on your production line.
Of course, the ramifications of bad data are not limited to manufacturing. Any business which relies upon data to inform its future strategies and initiatives – which is all businesses, or at least it should be – can be critically affected by substandard information in its systems. Once the damage is done by harmful data, it can be very difficult to contain. In fact, the negative effects of poor quality data have a habit of growing in magnitude; in only a short time, a small data mishap can build into something disastrous.
Collaboration between passive and active data governance is a huge leap towards eliminating this danger.
Prospecta are pioneering this collaborative approach between passive and active data governance with our Master Data Online (MDO) solution. This feature of the MDO solution is unprecedented in the market, thanks to its flexible and ultra-reliable model for data governance.
To learn more about Master Data Online get in touch with our team today and discover how this solution can be deployed within your organisation.