Four Ways To Start Data Collection
Have a central Team
Even if your company has an automated system for data collection, someone still has to manage the data and make sure that it is organized correctly. Data teams are becoming significantly more important because manufacturing companies are realizing the work needed to execute the collection and management processes. Whether your team is hand-collecting data on the floor or sensors are tied into a centralized system, there is a human that needs to be involved with every step to oversee the operation. Step 1; find someone that cares about the little things. All you need is one person to make sure the data is collected at the right times, appropriately, and stored in the right place. This can be a simple process or a full-time job depending on how much data is being collected and managed in a system. The point of having a central team is that data is crazy. If you let data run wild, it will become low-quality and useless for your organization.
Don’t overlap systems
Confusion and data-collection don’t go well together. So, if you are a company with multiple systems in place that tracks data for your company (i.e. an accounting platform, CRM platform, inventory control platform, and HR platform) that all operate as individual technology, this can be hard to collect and manage the data altogether. By using many different systems for data collection, the hairs of the data can get tangled, difficult to identify, find, and organize for an intelligent output. Thus creating mass confusion for data decision-makers. Overlapping systems is the quickest way to get burnout and give up on the data-collection process.
Data Quality – Crap in, Crap out
Not sure if this is the best analogy to use, but it certainly gets the point across. For example, if you put a pile of dog crap on a pan, stick it in the oven on bake (350 degrees) for 15 minutes, pull the pan out of the oven, you have baked crap. That’s how data works. Start the data-collection process with something you know you can get value out of and don’t be tracking data that’s not getting you anywhere. Our advice on the data-collection journey is to start small and start where you can improve something the most through data insights. The quality of the data is a very important aspect because it creates clarity on what the data is, where it’s coming from, and its ultimate purpose. Start small with an organized system through Google Sheets or Excel to make sure everything is formatted correctly and have everything in one central location. Lastly, the setup of the spreadsheets should be super clear and concise, so that confusion is minimal and it can be integrated into any type of analytics system if needed.
Have a process (top-down approach)
Who is the data for? What is the purpose? What is to be accomplished? These are some of the questions that need to be asked to begin an efficient process. Our Top-Down Approach allows decision-makers to well, make decisions on their primary levels of operation. Every level of decision-maker wants different data for insights. What concerns the CEO of a company doesn’t always directly correlate to what a QA Manager wants to see on a day-to-day basis. The point is to have clearly defined goals and principals that will tailor to the decision-maker on different levels of various departments. And have that process fit uniquely into each department for your company. You don’t have to create the next BluWave Analytics of data-collection. All you have to do is be clear, concise, and meaningful in the data that gets to the end-user and how they receive it.