Big data is becoming a fundamental part of modern businesses. However, the true benefits of big data go far beyond simply creating dashboards and reports. The real difference it makes is in your business operations.
Business data can be collected in many ways such as web pages, mobile apps, transactions, internal systems, IoT, marketing and more. Understanding, organising and analysing this data can give your business valuable insight. This can help to identify patterns, reduce inefficiencies and make better business decisions.
However, having lots of data isn't necessarily going to make your business more efficient. The real benefits come from how you can use the data.
1. Improve Decision Making Speed
Traditionally many business operations will be based around reports and data from years ago. For example looking at monthly sales figures, operating costs, employee performance and customer feedback.
Whilst this can provide some valuable insight, it can slow down the decision making process. By the time you find out there is an issue, you may have already had an impact.
Using big data analysis can help you analyse data from many sources more frequently.
For example, your e-commerce company can track activity on their website, product searches, purchases and abandoned carts. This means they can see how customers are behaving in real-time. This can help them identify any changes in demand and react accordingly.
This helps to turn your business from being reactive to more proactive.
2. Personalise Customer Service
Customers now expect businesses to know their preferences and make recommendations. Big data can help you gain more insight into your customers.
You can use data from:
- Previous purchases and browsing
- Viewed products
- Customer support
- Feedback and reviews
- Preferred contact method
- Purchase frequency and seasonal interest
This can help your customer service team to give more relevant answers and marketing team to create targeted campaigns.
Customers who purchase certain categories of products regularly, can receive relevant recommendations.
This can make a real difference in how your team operates. They will spend less time guessing what your customers want and more time focusing on what they actually need.
3. Predict Inventory Needs
Inventory can be one of the most challenging parts of any retail, manufacturing and distribution business.
Having too much stock can cause increased storage costs. Having too little can cause lost sales, delayed orders and unhappy customers.
Using big data can help you plan your inventory needs. You can look at past sales, current demand, seasonal trends, supplier performance and market trends.
For example, if you're an online electronics retailer and about to have a big sale during the festive period.
You can look at past sales, current product searches, customer queries and stock movements to help predict which products may have increased demand.
Your operations team can then plan their purchase schedule, work with suppliers and optimise stock in the warehouse.
This helps to make your inventory decisions more proactive.
4. Improve Visibility Within Your Supply Chain
A supply chain can be quite complex. It can involve purchasing, manufacturing, warehousing, delivery and more.
If each of these are using separate systems, it can be difficult to identify any delays, supplier issues or inefficiencies.
Using big data analysis can help you bring data together. For example:
- Vehicle locations and delivery routes
- Fuel usage
- Shipment status
- Traffic
- Processing times in the warehouse
- Supplier delivery performance
If there is a delay with a shipment, using this data can help your operations team understand why and what they can do.
Rather than finding out about delivery issues when customers complain, you can find out potential issues quicker.
5. Reduce Breakdowns With Predictive Maintenance
Equipment breakdowns can cause disruption to your production, delayed deliveries and increased maintenance costs.
Traditionally maintenance can be done on a set schedule.
With big data you can use predictive maintenance.
Sensors and monitoring can be used to collect data from your equipment. This can give you insight into temperature, vibrations, pressure, speed and performance.
By analysing this data along with previous maintenance data, you can identify any anomalies. For example,
A manufacturing company may notice that a certain machine has regular abnormal vibrations.
The maintenance team can investigate this issue and schedule an inspection.
This means your maintenance is no longer reactive.
6. Understand Employee Productivity
Your business productivity is not just about how long your employees are working. It's about how efficiently they are completing tasks, how resources are used and where there are unnecessary delays.
Big data can help you understand how your business is performing. For example:
- Average ticket resolution times
- Common issues
- Customer satisfaction
- Workload distribution
- Repeated manual tasks
- Service response times This can help identify if your employees are spending too much time on repetitive queries. Management can then implement automation, improve internal documentation or redistribute.
The aim isn't to keep a close eye on employees. But to understand where there are issues and create an environment where your teams can be more productive.
7. Create More Data Driven Financial Planning
Many areas of your business operations will be affected by financial decisions.
Big data can help your finance team understand where your money is going. They can look at:
- Departmental costs vs productivity
- Project costs
- Sales
- Customer acquisition costs
This can help you identify unnecessary costs. You can also understand what is contributing to your business.
Using predictive analytics can help organisations predict future cash flow needs, identify any anomalies and prepare for changes.
This means your financial planning is more aligned to your operations.
8. Identify Potential Risks
All organisations have risk. Whether it be cyber threats, financial discrepancies, disruptions, and unexpected changes in customer demand.
Big data analysis can help you identify any anomalies in large volumes of data.
For example, financial institutions can look at transaction behaviour to identify any potentially suspicious activity.
IT teams can also analyse network activity, logins and system logs to identify any unusual activity.
However, just because there is an anomaly doesn't mean there is a risk. You will need to ensure the data is validated, you have appropriate security measures in place and keep a human element.
The benefit of using analytics is that you can investigate potential risks quicker.
9. Ensure All Departments Are Using The Same Data
A common issue with business operations is having data split across departments.
Sales may be using one platform, marketing another, customer support a third and finance a completely separate reporting tool.
If data is not shared between these, your employees may not have the full picture.
Big data initiatives can help businesses to bring data together from different sources. This can help create more consistent reporting.
For example, sales, marketing and customer support data can be brought together. This can help your teams understand the full customer journey.
Marketing can see which campaigns are bringing in valuable queries, sales can understand where potential customers are coming from and customer support can see what issues are consistently affecting customer satisfaction.
This can create a more cohesive environment between departments and reduce the need for manual data collection.
10. Implement More Automation
Big data can be used to automate processes and reduce repetitive tasks.
Once you have accurate data you can use this within your automation. This can trigger certain actions depending on rules or analytics.
For example:
- Automated stock alerts when stock hits a certain level.
- Customer alerts when order status changes.
- Invoices that need further verification.
- Support tickets assigned based on the issue.
- Operational reports from integrated systems.
Using Artificial Intelligence and Machine Learning can help to take this even further. This can help to identify patterns and allow more complex decisions.
However, you need to be careful with automation. Ensure you know what can be automated and which decisions need human approval.
The aim is to reduce any unnecessary manual tasks.
Challenges To Consider
Big data can provide many opportunities for your business operations. However, there are a few challenges to overcome.
Data Quality – If your data is incomplete, duplicated or incorrect it can cause unreliable insights. Ensure you have consistent data capture and validation.
Data Integration – Often data will be stored in many different applications and legacy systems. Ensure you have a good plan in place to bring everything together.
Security – Ensure you have appropriate security in place to protect customer data, finances and business data.
Storage – Ensure you have the correct storage solution to hold large amounts of data.
Understanding – Ensure your employees understand how to use the insights.
Define A Goal – Before investing in complex solutions, identify what issue you want to overcome.
If these aren't in place your big data initiatives could become a costly tech initiative. Whilst you may have amazing dashboards, it won't make much difference to your operations.
How To Get Started With Big Data
You don't need to change all departments straight away. A practical approach would be to start with one issue.
Identify An Issue – Identify an area that could benefit from better information. For example, predicting stock, customer support or deliveries.
Identify Relevant Data – Determine which systems have the data you need.
Ensure Data Quality – Ensure data is standardised, validated and organised.
Select The Right Technology – Choose the right analytics platforms, databases, cloud and integrations.
Create Useful Analytics – Create reports, dashboards, predictive models or automation to help with decision making.
Measure Results – Measure any meaningful metrics. For example, processing time, costs, errors, customer satisfaction and productivity.
Scale Up – Once you've seen improvements from your initial implementation, think about other departments.
This will help you to focus on making real improvements to your operations.
The Future Of Business Operations
Big data is transforming how business operations are run. This is helping organisations understand issues, resources, customers and make decisions.
The real benefit of using big data is helping people to do their job more efficiently. Rather than simply collecting more data and creating complex dashboards.
As cloud computing, Artificial Intelligence, Machine Learning and integrated applications are developing, organisations will have more opportunities to bring data together.
Those focusing on accurate data, practical use cases and measurable improvements will be best placed to make the change.
The real change isn't what you see in a presentation. It's how your work changes.
Want To Know More? Find out how Big Data In Business Operations is helping organisations change their processes and make more informed decisions.
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