Today, companies of all sizes collect increasingly large volumes of data, from customers, vendors sales, inventory and production. However, many of these companies do not understand how to fully leverage this asset or utilize data to truly enhance multiple facets of the business. Implementing a comprehensive data strategy can provide significant advantage to organizations that do this properly.
Data Collection Considerations
There are many ways to collect both internal and external data, but in order to know what to look for in your data, it is critical to first establish a purpose for using data analytics. For example, what are your organization’s long-term plans and goals? What insights would you like to gain from this data? Do you want to learn more about your customers? Do you want to improve your data security?
Some of the most common reasons businesses are leveraging data analytics include:
- Improving e-commerce sales and operations;
- Creating efficient marketing strategies;
- Increasing security;
- Improving fraud prevention;
- Enhancing user experience;
- Increasing profits; and
- Providing exceptional customer service, support, and experience.
An ongoing training program that is regularly updated to keep up with the evolving threat landscape and incorporates new security protocols is key. Most people learn best with a more hands-on approach, so backing up the theoretical training with simulations which allow employees to practice safe online behavior will help to reinforce the training and improve its effectiveness.
To successfully use your business data for insights, expert data analysis is necessary. Whether you hire an in-house team or work with external consultants, it is important to understand that this team will be responsible for delving into every aspect of data collected by your organization. Additionally, your analytics experts must work closely with your IT infrastructure group to ensure smooth operations.
Once the data analytics specialists gathers and organizes the critical data, visualization tools are necessary to help interpret the information by presenting it in easy-to-understand formats that put insights front-and-centre.
Putting Your Data to Work
Uncovering the value in your data is easier said than done. While in certain cases obvious opportunities can be actioned quickly, more often deeper dives are needed to develop a keener understanding of the “why” behind your data. The deeper dives are necessary to inform a plan of attack to address key challenges or enable great opportunities.
For example, using these insights to improve a marketing plan could mean including consumer insights in each step of the decision-making process.
Depending on your goals and plans, using data analytics can help you discover opportunities to reduce costs, improve efficiencies and drive productivity in various areas of your business operations.
Insights from data analytics can help your business:
- Meet consumer demands;
- Improve service level performance;
- Improve order fulfillment;
- Drop poor-performing suppliers;
- Re-align the organization to improved processes;
- Use customer feedback (e.g. complaints and refund requests) to improve products and services;
- Identify, cater to, and retain loyal customers/clients to optimize your marketing investment;
- Maximize advertising;
- manage operational costs; and
- Understand popular products/services by season, region, etc. to market the right products at the right times and increase sales.
Companies Using Data Analytics to Better Drive Business Insights
Delta has used big data to help with one of the most uncomfortable travel situations that exists—lost baggage. With over 130 million bags checked per year, the company held a lot of tracking data about bags and became the first major airline to allow customers to track their bags from mobile devices. To date, the app has been downloaded over 11 million times and gives customers much greater peace of mind while traveling while also differentiating Delta as a customer-centric company.
On a daily basis, UPS makes 16.9 million package and document deliveries every day and over 4 billion items shipped per year through almost 100,000 vehicles. With this volume, there are numerous ways UPS uses big data including forfleet optimization. On-truck telematics and advanced algorithms help with routes, engine idle time, and predictive maintenance. Since starting the program, the company has saved over 39 million gallons of fuel and avoided driving 364 million miles. The next steps include completion of the roll-out and applying the operational efficiency to their airplanes.
American International Group (AIG) uses big data and data visualization to help fight fraud. The system uses structured and unstructured data from claims databases and handwritten adjuster notes to identify potential fraud. Besides listing priority claims to investigate, charts and visualizations, like heat maps, inform teams of other insights and help them make improvements to machine learning algorithms.
Tesla is the world leader in instrumenting vehicles with sensors and sending every piece of data to the company’s Apache Hadoop cluster to collect the data. The data is used to improve the company’s R&D, car performance, car maintenance, and customer satisfaction. For example, the company is notified if a car is not functioning properly, and consumers can be advised that service is required. These capabilities have helped Tesla create market share in a difficult environment where charging stations are not widely deployed.
Is Your Organization Ready?
Companies today collect data in ways not envisioned even a couple of few years ago. However, to gain a competitive advantage, your organization must implement strategies to aggregate that data, analyze it in real-time, and turn it into a true asset. When setup properly, data analytics programs can deliver insights that provide an avenue to better understand your customers and operations, discover key trends, and support more effective and informed decision-making.