Over the last few decades, several acronyms have sprung up naming essential systems for storing and processing business data, such as CRM (customer relationship management), ERP (enterprise resource planning) and MRP (material requirements planning).
Companies invest a lot of time and money in these tools, as executives know that collecting data to report on what’s happening in the business is vital. But invariably more can be done with the data to help manage the business.
Considering the huge expense and effort that goes into collating data, it’s surprising how many organisations fail to reap the full benefits. A lot of businesses have become data junkies, addicted to collecting and storing information but not putting it to good use.
The purpose of collecting and analysing data should be to inform decision-making and to guide the business so it can meet the needs of its customers better and become more profitable.
Business intelligence vs business analytics
So, let’s break it down. What is business intelligence (BI) and business analytics (BA)? How do they differ? And why do we need them?
Business intelligence (BI) is an umbrella term used to encompass the processes, methods, measurements and systems businesses use to analyse raw data. These might include reporting, automated monitoring and alerts, dashboards, scorecards and ad hoc queries. Using business intelligence is a good way to check how well a business is doing and benchmark it against past performance.
Today, artificial Intelligence (AI) is powering up BI’s contribution to businesses, expanding its functionality by simplifying data processing and developing critical insights with predictive analytics, machine learning and natural language processing.
Many of us go for routine medical check-ups just to check whether we’re in good health and to pick up any issues that need to be addressed. Monitoring your BI is similar, in that it allows you to see how healthy your processes, methods and systems are and to check whether things are improving or deteriorating.
Business analytics takes things a step further. Put simply, we can use BI to manage our day-to-day business. We can then take that same information and use BA to change the business.
It’s through BA that we can leverage the value of the data we have collected. So, BI is the first step for companies to take when they need the ability to make data-driven decisions, and BA is the analysis of the answers provided by BI to drive the business forward.
Mining value from data
BA includes statistical and quantitative analysis. It also encompasses data mining, which we can use to find out what has happened (descriptive analysis) and why it happened (diagnostic analysis), as well as techniques to discover whether it’s likely to happen again (predictive analytics) and optimisation and simulation to help with deciding on the best course of action (prescriptive analysis).
So, business analytics enables leaders to make decisions based on deep learning rather than instinct.
As an example, during weekly sales meetings, you might review your sales KPIs and use a dashboard to see where you stand against targets, then discuss what happened, when and how. This is business intelligence. If you finish your review there, you will need to cross your fingers that you will reach the target next week.
On the other hand, business analytics applies statistical modelling to extrapolate from past results what future results can be expected. Using a BA tool will help you predict, if you go on as you are, whether you will reach your monthly target or not. Clearly, this is a useful feature to support business planning.
The insights gained from BA enable companies to automate and optimise their business processes in four distinct categories:
• Operations analytics
• Financial analytics
• Customer analytics
• Employee analytics
Don’t collect data for data’s sake
Business intelligence and business analytics should, in theory, make everything visible, transparent and easy to manage. In reality, while having all this deep insight is great, actually applying it to making decisions on a day-to-day basis is not always easy.
Despite acknowledging the importance of BI and BA, and investing good money in them, many businesses fail to unlock the potential gains available. This may be due to several factors:
Inadequate systems or structure to capture data
Not only does the organisation need the right tools to capture data but they need to ensure that the organisation structure is optimised to leverage analytics. For example, does data flow freely across the organisation? Or is it siloed and locked up in paper form, making it difficult to access?
No strategy driving the collection and organisation of data
Some problems with data include unreliable or bad interpretations of data, wrong or too many KPIs. To prevent this, there needs to be a strategic plan for collecting, organising the right data and using it in a way that will add value to the organisation.
No buy-in
Leadership needs to define and communicate the vision of what it means to be a data-driven organisation and how analytics will contribute to a business’s health. Only then can there be buy-in from employees.
Missing skillsets and capabilities
It may be appropriate to set up a dedicated team equipped with the right tools and skillsets to enable the organisation to interpret and develop data-driven insights.
Becoming a data-driven organisation
Data is your best friend to survive tomorrow.
Effective use of business analytics will help you quickly identify key opportunities to boost efficiency, drive profitability, improve customer satisfaction and motivate employees.
However, for an organisation to transform into a data-driven one, it needs to be equipped with the right skillsets and capabilities, strategy, systems and structure. Only then can they reap full value from BA and keep pace with a fast-moving, ever-evolving marketplace.
