In the dynamic landscape of modern business, making informed decisions is absolutely essential for growth and stability. They drive the company forward, pave the way for new approaches and can ensure that you’re at the forefront of any trends. However, many companies can struggle to get the additional contextual information they need to ensure that their decisions will work in reality, rather than just in the boardroom. Enter decision Intelligence (DI): a multifaceted approach that combines data science with managerial decision-making.
Lucy Montgomery, a freelance writer at Quantexa, advises how to dissect four compelling benefits of incorporating DI into your business processes, showing how it can be the compass that guides you through the complexities of data-driven decision-making.
What exactly is Decision intelligence?
By now, most of us are familiar with the concept of artificial intelligence (AI). AI programs can gather and analyse vast amounts of data, but they often lack context. Therefore, results provided by AI aren’t as valuable as they could be, or aren’t suited to the problem you’re trying to solve. In order to tackle this, a DI program or framework can be combined with AI and other tools to generate data that is actually helpful and applicable to your business.
In summary: DI brings together the disciplines of data science, social science and managerial skills to allow you to either make quicker decisions with human input, or automate some of them entirely.
1. Decision Intelligence helps you make the most of your data
When you ask AI to run analysis on a dataset, you often naturally restrict the findings to your direct team. Especially in larger companies, teams work as close units under one specialism – so sharing your research findings on large charity events, for example, might feel irrelevant to a team that only organises small meetings.
However, despite the difference in context, there are often wider learnings that may be applicable to other areas of the business. For example, you might discover that attendees at the charity events respond best to email marketing, and the same could be true for smaller meetings too. Without DI, you might not realise this, as it wouldn’t occur to you to run datasets from other teams through your tools.
DI allows you to create a single repository to store your data, maximising the learning potential and opening doors for other teams to benefit from your research. Plus, from a technical perspective, having single storage means a reduction in duplication and missing data.
2. Make informed decisions
When we make business decisions, we do so based on the information we have. It’s not practical to consider every possible outcome for every decision – no one would get anything done, and it’s impossible to always have this kind of foresight. However, there’s no denying the benefit of having a holistic view of the business.
DI can allow you to seek out hidden connections and make the most informed decisions possible, reducing risk. Additionally, technology has none of the biases of humans. It simply looks at data as a set of information, pulling out connections based on facts alone, rather than choosing what fits with a specific aim.
In summary, computer technology has the ability to analyse and identify far more connections than a human, in a fairer way, at a faster speed – this is an area where DI really adds value to a business.
3. Reduce workloads and increase customer satisfaction
Thanks to the modern business model, customers are getting increasingly used to being able to access what they want, when they want, and they expect it to be correct at all times. For example, a banking customer may want to be able to log on to mobile banking and get a mortgage in principle or open a new account without even speaking to a bank clerk. In days gone by, they may well have been able to apply online, but their paperwork would still have to be reviewed by a human before it went through. Now, they expect to be able to complete their business at the click of a button.
Unfortunately, this can be tricky. Banks, for example, have to have the right information about the credit score and history of that customer before they make a decision, in order to reduce their own level of risk. Whilst this can be done manually, it won’t meet the needs of the customer, so this is where DI can step in. Using a framework and large data repositories, it can run those same checks at speed, giving the customer the answers they need without having to wait in a phone queue or visit a branch.
As well as increasing customer satisfaction, this can reduce employee workloads, leaving them free to tackle more complex tasks that require human interaction. This may even boost employee morale, as repetitive tasks are removed from their to-do list and they can focus on making a real difference in other areas.
4. Maximise your potential with the help of Decision Intelligence
Introducing a new technology to your company can feel daunting. However, the potential that DI has for boosting business insights and maximising potential is worth it. Before you begin, make sure you fully understand data protection laws and partner with a trusted DI supplier to ensure your customer information is as secure as possible.
About Lucy Montgomery
As a business manager, Lucy is always looking for new ways to bring inspiration and value to the company she works for. She is fascinated by new technologies and is always willing to try a different approach.
