Cleansing and building the right information governance for success

Executive summary

Organisations are building massive information stores, and new technologies such as artificial intelligence (AI) are poised to convert these troves of data into usable data outcomes that can guide actions at a more rapid pace. But today, most organisations acknowledge that they have too much information; most of which is unorganised and uncategorised, which is limiting the effectiveness of tools such as AI, thereby putting these organisations at risk. To truly take hold of their data and drive a more efficient operation, organisations need to begin by addressing their current information governance practices and data, putting strategies in place that can help streamline and automate, enabling long-term compliance and efficiency for their operations.

The data problem

It is said that information is knowledge and that knowledge is power. But conversely, information is a liability, and information is a risk. Organisations need to understand this complex balance to effectively run and protect their operations.

Between the standard transactional information that is generated through ongoing operations, such as the data contained in forms and applications, and the ancillary information that is contained in non-structured repositories such as SharePoint, OneDrive, file shares, emails, memos or even text messages, a lot of work must be done to identify and categorise this information if there is any hope of reigning in the current situation.

The risks associated with the generation and retention of information are vast. Whilst many risks are highly visible, still more lurk below the surface, potentially not making their presence known until it is too late. Both reputational and financial risks abound as data grows at its maddening pace. Unfortunately, risks scale faster than the information itself, meaning that as data stores grow, the exposure increases at a much faster rate, often outpacing the organisation’s ability to deal with it.

Whilst various organisations want to utilise all their internal information to power tools such as AI in the hopes of accelerating decision-making, if the data is not adequately cleaned up, structured, and organised, the value of the AI outputs is greatly diminished.

Ultimately, the goal for any organisation will be automating the collection, categorisation, and usage of their internal data. However, these actions demand information that exhibits consistency and repeatability to maximise their utility. Without clean, structured data, automation cannot be applied, leaving the old time- consuming manual processes in place.