Data-driven decision support

Challenges

The idea of data-driven decision making is that decisions should be extrapolated from key data sets that show their projected efficacy and how they might work out. The Sunstone RTLS (real-time location system) can get this data, and present it in ways that back up decisions. This is in stark contrast to the way that decision-making had been done throughout the history of commercial enterprise, where before the presence of new complex technologies, individuals often made decisions based on observation or informed guesswork.

Fundamentally, data-driven decision making means working towards key business goals by leveraging verified, analyzed data rather than merely shooting in the dark.

However, to extract real value from your data, it must be accurate as well as relevant to your aims. Collecting, extracting, formatting, and analyzing insights for enhanced data-driven decision making in business was once an all-encompassing task, which naturally delayed the entire data decision making the process.

Data-driven business decisions make or break companies. This is a testament to the importance of online data visualization in decision making.

Data collection with Sunstone platform

Sunstone RTLS is a platform for collecting data (position, motion, tracking- and sensors data) based on UWB (ultra-wideband) technology and making online interfaces for manufacturing reporting and controlling. You can see your Andon system online and real-time without any modification in your machines and with product tracking you can get a real picture from your production status in any time and also get an alarm if the system recognizes any anomaly during the process.

The online monitoring system for the logistics and manufacturing area is also included in the system which can help identify the problem during the processes. The system is easy to integrate the ERP and MES systems and all of your enterprise databases for better data collecting and connecting.

The 5 steps of data-driven project:

  1. Make a strategy: First, identify your goals – what can data do for you? Perhaps you’re looking for new leads, or you want to know what processes are working and what aren’t. Our Lean- and business developer partners can help in this step.
  2. Identify key areas: Data is flowing into your organization from all directions, from customer interactions to the machines used by your workforce. It’s essential to manage the multiple sources of data and identify which areas will bring the most benefit. What area is key to achieving your overarching business strategy? Our Industry 4.0 and finance experts can help in this step
  3. Data targeting: Now it’s time to target which data sets will answer all those questions (which identified in Step 2). This involves looking at the data that you already have and finding out which data sources provide the most valuable information. Our Data science partners can help in this step
  4. Collecting and analyzing data: Identify the key players who will be managing the data. This will usually be heads of departments. To analyze the data effectively, you may need integrated systems to connect all the different data sources. Our Industry 4.0 and IT experts can help in this step
  5. Turning insights into action: The way you present the insights you’ve gleaned from the data will determine how much you stand to gain from them. We have multiple business intelligence tools that can pull together even complex sets of data and present it in a way that makes your insights more digestible for decision makers. Our Data science partners can help in this step