Organizations of all types and sizes have access to huge amounts of data which can be analyzed for insights that will guide their decision making. But some organizations don’t know where to begin, or just what the benefits will be.
Actionable insights provide the ultimate value from data analysis because they allow an organization to take concrete actions, and make bold decisions which improve efficiency, break open new markets, create new revenue streams, increase profits, and reduce costs.
This article contains eight examples of actionable insights from data analysis, and shows the benefits achieved from each.
Supply Chain – Keeping Shelves Stocked
At the start of the pandemic, Pepsi Co, whose brands include Pepsi, Lays, Doritos, 7UP, Tropicana, and Quaker Oats, found that some of their products were flying off of shelves to help clients manage inventory to meet demand. They asked their clients for warehouse inventory and point-of-sale data. Pepsi used a machine learning algorithm to analyze the data to predict when clients would be out of stock, and to send reorder alerts, and shipment notifications.
- Pepsi helped its customers have the right products, in the right volumes, and at the right time.
- Pepsi paused marketing campaigns for products that were in high demand, saving advertising dollars.
Healthcare – Improving Practitioner Skills
One health system analyzed data on patient experience with medical practitioners.
Data analysis showed that some practitioners prioritized scientific facts over patient experience leaving the patients feeling that the doctors weren’t empathetic.
Doctors received empathy training to help with patient communication.
- Patients felt heard and communication in both directions improved resulting in improved patient safety.
- Practitioners who took empathy training have fewer malpractice claims.
Healthcare – Detecting Anomalies
In 2018, researchers at MIT created an algorithm that detects differences in MRI scans and other 3d images 1,000 times faster than humans.
- Patients got an accurate diagnosis faster and started treatment earlier, in some cases leading to better outcomes.
The Centers for Disease Control uses outbreak analytics and forecasting to anticipate spikes in cases of COVID-19.
- Hospitals can anticipate staffing and supply needs, and be better prepared to meet them.
- Helps inform decisions made by authorities to combat spikes in cases.
- Helps individuals plan travel and interaction according to their needs.
Manufacturing – Product Quality Improvement
To improve product quality, a plastics manufacturer analyzed 612 unique production parameters across 12 machines to identify parameters impacting product quality.
- Modifications resulted in a 22% reduction in scrapped parts.
- The reduction in scrapped parts resulted in a 15% increase in throughput.
Manufacturing – Predictive Maintenance
A semiconductor manufacturer monitored machine, operational, and system data for the pumps used in the manufacturing process.
It compared data collected to known normal baseline operational data to determine when machines and components needed maintenance.
- Reduced maintenance costs because machine data goes beyond predicted mean-time-to-failure and periodic maintenance schedules allowing maintenance to be performed only when needed for components required.
- Costly unplanned downtime due to unexpected failures were reduced due to timely maintenance based on the machine’s component health.
- Cost savings and faster equipment ROI as costly machine parts, which previously might have been replaced before the mean-time-to-failure period, can continue to be used while they are operating within acceptable parameters.
Process Optimization – Cost Reduction
Vodafone discovered that they have low automated transactions and used data analysis to implement new robotic process automation (RPA) with improvements to it’s process.
- Implemented robotic process automation (RPA) to improve its order process resulting in an 11.5% reduction in processing costs.
Process Optimization – Identify and Eliminate Bottlenecks
BridgeLoan has integrated a process mining tool into its ERP system to identify the bottlenecks in their loan application processes and used the data to reimagine and recreate their process.
- Improved loan processing time by 40%, and increased capacity of loans processed per month.
Analyzing the data about your business, processes, products, and customers pays dividends in the long run, and may provide actionable insights that can help you customers, improve the quality of the products and services you deliver, and reduce costs.