Data collection systems work. However, they mean an investment in technology. Before we can justify that investment, we need to understand why we may want to utilize a data collection system in place of people with clipboards.


When deciding to invest in data collection, the first question to ask is “Why?” Our objective is never “data collection” but some business objective like lower inventory, higher quality, better customer service or more accurate costing. For example, we can often meet these objectives without a data collection system, we can have people writing data on clipboards and later keying it in. Our data collection question is one of improving on the results we can get without using data collection.


A frequent motivator for data collection systems is visibility. Simply put, we want to know more and know it sooner. The right information, accurate, at the right time is one definition of visibility.


Accuracy


Errors happen. Errors happen because people are people. People will continue to misread a number, miscount, record a different number than they intended or have handwriting that others cannot understand. Other people will take those numbers and misread them or key them into a later system incorrectly. Software edits can catch some of these errors, for example item or location numbers, but not all for example quantities. Errors are not intentional -- they are human.


Errors cost money. The costs of errors are real. If detected soon enough, it may be as simple as sending someone out to determine the correct data and then correcting the record. Still, this process cost time and therefore money.


If the error goes undetected, the impact and therefore cost can be much greater. Some inventory errors mean that an item’s balance or location is wrong. With some inventory errors, we may actually have two errors, one item’s balance is overstated and another is understated. In both cases, we make decisions based upon incorrect data. For example, if an inventory error happens and goes undetected, we may make decisions that affect the business. We tell a customer we are out of stock when we have inventory, or worse, we promise a customer the product but we do not have it. We schedule production or a purchase order when we already have inventory on the shelf.


What is the value of improved accuracy? It is very difficult to assign a number to the value of improved accuracy. Accounts like to talk about adjustments to inventory values and that is important. However, the impact of accuracy is the improved decisions that can be made and the financial impact of those decisions.


Of course, the more accuracy you want, the more it cost -- that is a trade-off you need to consider.


Time


The phrase “time is money” is well known. However, a good question is “When do we want to know?” Immediately is often the answer. To gain “real time” (an overused term which frequently means “soon enough”) data must be collected and entered into the system as the event happens. When the need is termed “real time”, we should ask what that really means, it often means as soon as the person needs it, which could be once a shift or once a month.


When looking at the time factor, beware, will the processing systems be able to handle it? Getting accurate data in a timely fashion is good. However, the value of this data is dependent on the system that will process the data. For example, if we run a system once a day, real time data does not add any value to the output of that system. Perhaps the answer is to run the system more frequently than once a day. The question should be, if the system were run more frequently than once a day, would we make better decisions?


Of course, the more speed you want, the more it cost -- that is a trade-off you need to consider.

Costs


Collecting data cost money. A production warehouse person who must manually record data is being less productive in their primary role, making product or working with inventory. The step of later keying in this data (and correcting errors) cost time and money. These variable costs, realized each minute of each day.


A data collection system avoids some of these labor costs but that system still cost money. Production and warehouse people become more productive due to the greater efficiency in collecting the data, either by arming them with a device (a bar code reader) or making the data collection fully automated (case counter, flow meter, etc.)


The costs associated with a data collection system are very different. A one-time investment in equipment, software and training are required. The justification is frequently not a calculation of how many hours are saved but the business impact of more data, higher quality data and more timely data.


Summary


Data collection systems need to be justified, like any business investment. The justification comes from two sources, improved information and cost reduction or avoidance.


A data collection system can improve the value of existing or planned systems. The value of data collection is dependent upon these other systems. Think about the impact of these other systems receiving more accurate or timelier data. Will better data mean better decisions and therefore better business results?


Data collection systems can also cut the cost of gathering data. It can improve the productivity of production workers for example, giving them more time to add value to products instead of recording data. Can a proposed system improve productivity, cut cost or avoid the need to add cost?