Data can paint a picture of what happened, but data analysis can be needed to explain why it happened. It’s often the “why” (vs. the “What”) that makes an insight actionable insight. Actionable insights are conclusions drawn from data that can be turned directly into a response. This article explains why data collection is so important and how businesses can use it to support their operations.
Benefits of data collection
The data collection method gathers information from different sources to find answers to specific problems and questions. Today, an organization can gain a competitive edge by adopting a digital approach to capture or collect shop floor or production data and having the benefits which include but are not limited to:
Manufacturers can get quick and timely insights on asset performance, workforce utilization, product quality, inventory levels and equipment efficiency. In addition, it helps to mitigate unplanned machine downtime and production bottlenecks and boost factory floor efficiency and productivity.
Improved Decision Making
Different teams maintain different data records, and that too in other formats. With cumulative data collection, organizations can eliminate assumptions, guesswork and communication gap between various teams. It saves other teams time and effort to look for the correct information. By having a single source of reliable, accurate and accessible production data at their fingertips, employees can collaborate, make critical decisions and respond to changes quickly.
Accurate data captured at various stages on the shop floor, like raw inventory, current production capacity, and estimated delivery, helps to align planning, production, and sales.
Optimize cost savings
With a spectacular rise in labour, transportation and materials costs, manufacturers are always on the sprawl to embrace ways to save money. Implementing data collection can translate to evaluating production processes, bringing process improvements, increasing output and reduction in scrap; while bringing down the overall costs.
Turning Data into Actionable Insights
Data is meaningless unless it helps make decisions that have a measurable impact. Too many Big Data projects are formulated without input from front-line operators or consume so much time that the insight goes stale before it can be used. This is why the term “Actionable data” is critical.
Actionable data is “information that can be acted upon or gives enough insight into the future that the actions that should be taken become clear for decision makers.” Actionable data is information that has gone through analytics and data processing and is presented in a clear, understandable, and often visual way that is useful.
Picture a manufacturing industry. Data is the raw material from which the products are necessary to make a product, Actionable Data. These types of data are the ones that address the need and use the gathered information.
The “Actionable Data” approach enables organizations to sift through massive amounts of data quickly, run the right analytics, and provide relevant insights so people can take meaningful action.
Examples of actionable insights
- By analyzing your supply chain process, it can be identified where costs are being incurred. The adjustment of the cost structure via actionable insight that results from supply chain process optimization to improve margins.
- Identify equipment error patterns by analyzing insights from operations data and take action to prevent times.
- Identify preferred operational targets that should be engaged to reduce costs.
- Measure employees’ engagement and act based on analytics analysis to improve employee productivity, attendance, etc.
Benefits of actionable insights
Actionable data enables organizations to draw actionable insights from business information to make data-driven decisions. This provides a clear and comprehensive picture that helps businesses connect the dots and take the necessary steps to grow.
Data should reflect reality in as close to real-time as possible. To drive insights and help users make accurate decisions, data needs to be up to date. Outdated data is ineffective for solving problems since the situation implied by the data needs to reflect the status as it’s actually happening accurately.
With dashboarding and other data visualization tools, data can be presented in a format that’s easy for non-data professionals to understand. Asking the right questions and transforming requisite data offers a new way to identify potential opportunities and make strategic changes. It allows organizations to go beyond the spreadsheet to data visualization, helping them show cross-functional data and determine what business leaders may not have seen otherwise.
This approach is highly graphical, interactive, and visual. It starts with a sketch—sometimes called a wireframe—that maps out what an ideal information dashboard might look like if it were designed to answer all the critical questions the organization has identified. Once this design has been agreed upon, it’s formalized as a finished dashboard.
Organizations at the top of their industries engage in digital transformation strategies far beyond a drive toward efficiency and traditional practices. Instead, these organizations are entirely changing the way they operate. For example, manufacturers are improving profitability by forecasting errors and enabling proactive maintenance scheduling.
They focus on driving action within their organizations based on insights and collecting insights from audience data to ensure the earned insights are actionable. Organizations that have become data-driven are seeing real results. Actionable analytics and the accessible app will drive this third wave of BI. These highly interactive, action-oriented data experiences co-exist seamlessly with existing applications and workflows.