Big data. Information technology. Business intelligence. You’ve heard all of the big data and analytics buzzwords. But it’s not all buzz. It’s the new reality.
Business intelligence (BI) tools are on the rise with 76% of C-level technology executives expecting to increase their BI and analytics budgets. Why? Data management solutions enable better decision making, improve operational efficiencies, and increase competitive advantages.
However, when investing in data management, predictive analytics, or business intelligence solutions, most firms make a critical error: They don’t know which pieces of knowledge they need. It isn’t until after they’ve invested in an intelligence solution that they realise the tool is useless without better data.
There’s a difference between data, information, and intelligence. And if you want to make more sophisticated decision-making and differentiate your organisation, you need to know how they differ and how they work together.
Data vs. Information vs. Intelligence
Data, information, and intelligence have major implications for your business. And, yes, you need all three in order to enable better decision-making and strategy.
Data in its rawest form is a recorded truth from a point in time. It’s a snapshot of an event. That event might be a conversation, a transaction, or an interaction with your company’s website. Data is the collection of outcomes from those events that is then recorded in a quantifiable way so businesses can easily review them. They’re statements of fact and cannot be contested.
Information is a simplistic way of bringing data together. You will have information, not data, when you take data from an event and put it into a narrative. It’s the context of data helping you answer questions such as:
- How many clients operate in EMEA?
- What is our churn rate?
- How long is our sales cycle?
The answers to those questions are what create information. It’s all about turning data points into something that informs you about your business.
Intelligence takes it a step further and uses information to drive decisions. Instead of telling a story (like information does), intelligence paints a picture. For example, if you’re selling to more people in EMEA, intelligence answers why that might be. Intelligence will look at the number of events, ad spend, or marketing campaigns EMEA clients receive and compare them to other clients in other regions and markets. Through this analysis, you might see that there are a greater number of client interactions (events, emails, or meetings) in the EMEA region and deduce that you need to do the same in North America to bring sales up.
How Data, Information, and Intelligence Work Together
Data, information, and intelligence are all a part of the same continuum. Yes, they’re different in definition and function, but equal in importance for accurate decision-making. When constructing a solution to a business problem, you need to have all three elements guiding your strategy. Miss one, and you’re using incomplete data or information to form strategic decisions, which could have catastrophic effects on your bottom line.
The Starting Point
If intelligence is your end goal (which it should be), you need to have clean, accurate data first and foremost. Therefore, you need to collect data from your operational environments across your organisation, both internally and externally. You never know what insights will transpire, and without data, the continuum falls apart.
For example, Tesco, a popular retail company here in the UK, created a loyalty card back in 1995 with the sole intent of gaining more data on their customers from their transactions. It was only once the data was collected that information and intelligence started taking shape as a potential output.
Filling in the Gaps
Without the context information provides, data is meaningless. As such, you need to ask critical questions of the data you’ve gathered to identify the “who, what, where, when, how” of your business.
In Tesco’s case, they used the data from their Clubcard to see how often their customers shopped at their stores versus their competitors, what types of purchases they were making, when they preferred to shop, and more.
Completing the Continuum
To complete the knowledge continuum, you need to analyse your data and information to uncover why results are happening to make more informed business decisions. For Tesco, they saw that customers in populous communities preferred “express” stores that housed essential products as they provide a faster and more convenient shopping experience. Using this intelligence, Tesco revamped many of their stores to the “express” model to cater to the communities they served.
A loyalty card isn’t the only way to complete the knowledge continuum, though. Tools like Introhive’s relationship intelligence automation platform passively collect relationship data in the background so you don’t have to. It identifies and records your firm’s network of contacts, emails, calls, meetings, social media activity, transactions, and more so you have a full understanding of your firm’s relationships and how strong they are.
With the data collected, the platform analyses that data to turn it into information and intelligence that can be accessed through reporting dashboards and Pre-Meeting Intelligence Briefings. Automation tools also remove human error from the data entry process and flag duplicate data points to ensure that your CRM data and insights are accurate, complete, and up to date.
Intelligence Is Easier to Obtain Than You Think
Business intelligence isn’t just for the Tescos of the world. Organisations often get scared of big data, how it operates, and the associated costs. However, SaaS technology has made it far cheaper and accessible to collect data, create information, and extract intelligence since there’s no labor or server costs associated with them.
Start your knowledge continuum with the right technology. See how Introhive can help by requesting a demo of our relationship intelligence automation platform.