Data-driven decision making is exactly what it sounds like; a process by which stakeholders use data to inform their decisions. This sentiment is what the entire insights industry is based on, as we are the miners of insightful golden nuggets of data on which businesses guide their entire brand.
I know that sounded lofty, but it’s not wrong. We are in the business of gathering the data, turning it into insight, and handing it to stakeholders on a golden platter to make sure their business makes the right decisions at the right time. Now, if those businesses actually take the data and insights into account in those decisions is a different matter entirely, and I aim in this blog to lay out how data-driven decision-making works.
|Data-driven decision making is exactly what it sounds like - but how exactly does it work? Is it as simple as it first seems?|
Choosing the Right Data
Now, to make the best decisions, you need to make sure you have the best data to make a truly informed choice. A lot of stakeholders, and people in general, make decisions based on limited, situational data; making use of what they can see at the time - but that only works for decisions that affect the short-term, not the long-term.
The fact of the matter is, the only data you need is data that is accurate and relevant to your decision at hand. The way you get this data is up to you, but make sure that the method will provide you with the in-depth, rich insights you need to make the right decision.
There are a variety of factors that go into the production of accurate, relevant, and reliable insights, such as: the sample used, participant engagement, the methodology(s) used, the analytics techniques used, the amount of time it took to gather and analyse the data, all at the very least. For example, if you combine quantitative and qualitative methodologies then you’re more likely to get an in-depth response from participants, rather than just using either a quantitative or qualitative methodology. But then again, using social media analytics might be a better way of getting in-the-moment feedback from one of the world biggest online communities, but you don’t know exactly how dedicated they are to your brand.
As long as the research you conduct is thoroughly planned beforehand, you’ve consulted with insight professionals on your options and agreed on the best way to gather your data to make sure it the most accurate and relevant it can be, then you can use it in your decision-making processes with confidence.
Making the Decisions with Data
Now that you have your accurate and relevant data, it’s time to choose the right way to action it. In every decision-making model, there are a few commonalities in the framework used to evaluate the data and proceed with an outcome, which include:
- Understanding the purpose of the decision, both in its individual state and how it fits into the wider business objectives/goals.
- Identify the right insights to take into account from those you’ve managed to gather.
- Make sure you’re taking into account professional opinion and know how your decision would impact the business in the projected future.
- Make the decision and evaluate the outcome so you can learn for next time.
There are a few Knowledge Management techniques that allow for the compiling, storing, and distribution of data and insights, so that they’re accessible directly at the time their most needed. Creating this central depository of data and insights can help immensely when data is needed to make a decision right at that very moment, but this central depository is built up over time, and the data that might be contained within the depository needs to be reviewed regularly to make sure it’s still relevant.
There are a variety of data-based decision-making models for us to choose from, but there are two specifically that I think might help start your data-driven decision-making journey off to the right start.
The first I want to mention is Cognitive Mapping, which is an organised set of ideas to help guide your thoughts, identify areas of uncertainty, and clarify assumptions made throughout the process. This is a great place to start to get a proper handle on any situation, and it lends itself to an interactive approach when new information or data is added into the mix. This is used a lot by professionals in all industries, whether they know it or not, and is the most straightforward, logical process to start with.
However, the second one I want to mention is not a business or market research-based model at all, rather it’s a policing model that works to help establish the right actions to take based on the evidence presented. The National Decision Model can be applied to spontaneous events or planned operations, used by an individual or a team of officers, in both operational and non-operational circumstances, and has a lot of applicability to this situation. The model has six key elements based on the code of ethics, to evaluate situations, evidence, and suitable outcomes.
Getting Data to Stakeholders
Having the right tools to actually make the decision is all well and good, but all decisions depend on insight professionals getting the right data to the right people at the right time, and present it in a way that captures their attention so our clients have no choice but to listen to the data and insights we present to them. Luckily, that’s what we do best.
Maria Twigge not too long ago explored how we can electrify data to help capture stakeholder attention so they actually listen to the data we present. In this article, Maria explored the use of data visualisation techniques, video delivery, embracing tension and inspiring discussions in interactive engagement to ensure that stakeholders engage with research results.
|From making sure you've got the right data, to finding the right decision-making model for you, data-driven decision making might be a bit more complex than the definition makes it out to be.|
Don’t be afraid to experiment with data delivery formats to find the right presentation technique for each stakeholder you come across so you can maximise the potential of your insights. Experimentation in this form can come in a number of ways, including blending the data formats to make it more comprehensive, cohesive, and exciting.
This might have all made data-driven decision-making sound a bit more complex than first thought, and while the premise is fairly simple, once you take a look under the surface you can see that there are different stages to making a data-driven decision: generating the right data, presenting it in an engaging way, using it in decision models to maximise potential, and evaluating at the end to make sure you’ve done the right thing.