Managing Data, Information and Knowledge

Effective management of data, information and knowledge is critical for businesses to thrive and grow.

Let’s start with some quick of the basic elements being discussed:

  • Data: Individual points of raw data. For example, a client purchasing something from your site offers a series of data points – the item purchased, the date and time it was purchased, the amount paid, etc. Think of an individual data point as being a single piece in a jigsaw puzzle.
  • Information: Using the relationship between individual data points to extract something more meaningful. For example, looking at the total number of sales over a month might indicate days where sales are higher or lower than other days which might then inform decision making around resources allocated to those days. Think of information as the picture that is revealed when the puzzle pieces are all assembled.
  • Knowledge: Placing the insights from the information into the context of the real world. It combines the information with aspirations, prior experience, and understandings of the context in which the organisation operates. For example, viewing the sales peaks and troughs in the context of public holidays, political / climate context etc, to then develop a sales strategy. Think of knowledge as understanding what the final jigsaw picture represents and the context it sits within.

With these elements in mind, we can now consider how each of these are managed.

  • Management in this context refers to the collection, storage, organisation and use of the data, information or knowledge. While the focus on quality remains, the way in which quality is assured is different for each of these element.
  • Data management focuses on the way in which raw data are captured, stored, and retrieved. Data is not necessarily collected only in a computer database, but can be recorded in any format: pieces of paper, in a spreadsheet or document, or even in someone’s head. Each of these differ in their ability to be accurately recalled, their proneness to error, and their ability to be shared with others. Data management emphasises gathering, securing and organising these individual data points.
  • Information management looks at the processes to organise, analyse, and present the raw data so that it becomes useful for decision-making and problem-solving. It includes the ideas of reliability and replicability. Reliability means that the information is an accurate representation of the underlying data. Replicability means that same information will be produced whenever working with the same underlying data points.
  • Knowledge management involves capturing, organising, and sharing this knowledge within an organisation as a means to sustain operations, facilitate learning, and foster innovation. It focuses on capturing insights, useful practices, lessons learned, and tacit knowledge from individuals and making it accessible to others.

Key takeaway: Good quality data leads to good quality information which leads to better decision making and knowledge management.

The relationship between data, information and knowledge can be summarised as:

AspectData ManagementInformation ManagementKnowledge Management
Purpose of ManagingEnsures data integrity, security and organisationFacilitates decision-making and problem-solvingPromotes learning, innovation, and collaboration
Human ElementPrimarily technicalIncorporates human expertise and experienceCaptures and shares tacit knowledge
ValueEnsures data availability and accuracyTransforms data into actionable insightsLeverages collective knowledge and expertise

For a new business, limited time, money and resources mean that initial priorities are often – understandably – on ensuring daily business operation. However, if a early focus on data and information management is not in place, this can have several impacts:

  1. The early data are irretrievable lost, meaning that critical evidence of things that worked well – or less well – are also lost and cannot inform future decision.
  2. New businesses often evolve rapidly, Having evidence of that evolution, and the reasons driving it, form an essential part of the company’s history. Loss of this information means that a formative part of the company’s origin story is lost.
  3. A new company is often unsure of what information may be needed in the future. A early focus on collecting as much data as possible leads to much greater options in the future of how this might be transformed into useful information and knowledge to inform decision making. Collecting early data, even while its ultimate use remains unclear, is a key part of being future aware.


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