Four Ways to Leverage Business Intelligence Across Your Enterprise
In this blog post, we discuss four ways manufacturing companies can use business intelligence and analytics to improve the interplay across production efficiency, product quality, customer demand, and service excellence.
1. Improve production, performance, and products
People who intimately understand data create the best dashboards. These dashboards typically reside in Excel files and are tapestries woven from disparate data sources.
Today, it is possible to run user-generated, real-time dashboards on top of cloud-based data management infrastructure. This approach saves hours of time and increases the level of insight gleaned from data.
Here’s an example: In the dashboards below, users can browse through filled orders and see how well the production ran by bringing together several data sets on a single dashboard. The scatter graph depicts the major metrics that affect production (setup, downtime, run speed). Note how the differences in variance trend between the two machines. Not only does it beg the question, “why is Machine 123 running better than Machine 456?” but it also shows the impact of the discrepancy in production cost, labor inefficiencies, and customer satisfaction.
2. Mobilize supply chains
Manufacturing data is constantly changing but immediately relevant. Using data at the right time is vital to a more profitable operation.
Mobile business intelligence provides information when and where it’s needed to make fast, business-critical decisions.
Here’s an example: The Coca-Cola Bottling Co. Consolidated (CCBCC), the largest independent Coca-Cola bottling firm in the US, has workers on the ground interacting and collaborating with visual dashboards from anywhere—even truck drivers in different cities.
3. React to customer feedback better and faster
In order to succeed in any industry, businesses must understand, and act on, the desires and needs of the customer. Manufacturers need to collect customer data by listening to many different channels such as social media, call centers, and customer surveys.
When finding insights from customer information, time to action is vital.
Here’s an example: Trane, a global leader in air conditioning systems and equipment, migrated from exclusively using spreadsheets to track customer service data to using integrated self-service data analytics and visualization. This change significantly reduced the time taken to transform data into insights and, more importantly, customer happiness.
4. Sales force optimization
The ability to efficiently staff sales support teams is paramount in today’s competitive environment. Creating an enterprise view of data assets fosters a culture of data-driven decision making that reduces the cost of sales and increases sales productivity.
Furthermore, an enterprise view of data allows sales teams to clearly see potential revenue by customer, product, and territory. Such clarity facilitates data-driven decision making that results in more efficient quotas, territory assignment, sales alignment and service demand.
If you want to learn more and take advantage of Search Discovery’s expertise, get in touch today!