The 4 Functions of Data in Decision-making

What is decision-making?

Decision-making is the process of choosing between different actions based on knowledge, experience, and intuition. Data is often the foundation for this. The decision method is usually self-evident, but it is wise to also critically evaluate the decision method used.

Role of data in making choices

Intuition, data-informed, data-driven, and data-inspired decision-making are different approaches to decision-making, each with its own characteristics and degree of dependence on data. Here's a quick comparison of these functions of data:

None

Intuition is the ability to feel something without thinking about it. Many decision-makers make decisions this way; data plays no role in these situations.

Inform

Data-informed decision-making focuses on the context of goals and looks more critically at the underlying data and analyses. The data is taken into account in decisions, but unlike data-driven decision-making, there is room for acquired knowledge, experience, and common sense, making out-of-the-box actions possible.

Direction

With data-driven decision-making, data and goals directly lead to specific actions. The selection process is fully automated, and there is no room for the knowledge, experience, and intuition of employees and management. This requires high data quality. A downside of a data-driven decision can be that (historical) data and models influence the direction of the organisation too much.

Inspire

Data-inspired decisions differ from the previous two in that there is no clear end goal. Instead, data that the organisation has access to is viewed as strategic capital. The emphasis is on how to get more value for the organisation from this capital. There is room for creativity in this process, in addition to knowledge, experience and intuition. Goal setting is therefore abandoned to prevent blindness due to (wrong) goals. A first step is often to inventory and organise data in a data catalogue.

Is data-driven decision-making always best?

No, in practice, the choice between these 4 approaches depends on the specific circumstances, the availability and quality of data, the complexity of the decision, and the culture and values of the organisation. While data-driven decisions are often seen as the gold standard for objective choices, there are situations where intuition, data-informed, or data-inspired approaches can lead to breakthrough insights and creative solutions. The key is to find the right balance between data and other factors, depending on the context and goals.

Apply example 4 functions of data

Imagine you run a small e-commerce business that sells handmade jewellery, and you want to determine the price for a new necklace design. Here's what each role of data could look like:

• None: You decide to determine the price of the new chain based on your gut feelings and creative intuition. You believe that the necklace is a work of art and should be priced higher than similar products on the market, hoping that customers will recognise its uniqueness.
• Inquire: After researching the market, you discover that comparable handmade necklaces in your niche cost between €40 and €60. You also collect data on customer preferences through surveys, which show that most customers are willing to pay up to €55 for a handmade necklace. In line with this information, you decide to set the price of your necklace at €55.
• Steering: You use advanced analytics tools to analyse market data, production costs, and competitor prices. The data-driven analysis shows that a price of $48 is likely to maximise both revenue and profit margins, taking into account factors such as demand elasticity and cost structures. Therefore, you decide to price the chain at €48.
• Inspire: You research customer reviews and feedback on your previous jewellery products and discover that many customers describe the emotional connection they feel with your creations. Inspired by this emotional data, you decide to price the new chain at €58, slightly higher than the market average. You believe that customers are willing to pay more for jewellery that has personal and emotional meaning, matching the emotional aspect of the data.

Symbio6 & data-driven decision-making

Symbio6 focuses on automating data-driven decision-making. The fastest and easiest way to make real-time decisions, 24 hours a day, seven days a week.