Every successful client is experiencing rapid growth and changing customer requirements. To support this growth in a scalable, profitable manner, turning data into insights is of paramount importance.

Data Overload

Every client has an overload of data. Whether using a modern ERP system or struggling with a complex maze of manual spreadsheets, the one item in common is an abundance of data. We have worked with clients with archaic ERP systems, but so long as we can extract data, progress can be made. On the other hand, we have worked with clients with Tier 1 ERP systems such as SAP or Oracle, but if they cannot get data out of their systems, the client is in a worse situation than the one with an archaic ERP system. Every manufacturer has products, defines how to produce those products (whether captured in someone’s head, in spreadsheets, or via an ERP system), has customers, receives orders, purchases from suppliers and so on. Each of those transactions and associated data is stored somewhere.

Data and related transactions adds up quickly. If you think about your typical day, you receive an overload of data before you even arrive at work. Your phone gives you the latest news and alerts. The news provides additional insights into key events. You drive by billboards and listen to the radio or talk with people on your way to work. You receive automated reports in your inbox. You most likely receive thousands of inputs before even arriving at work. Its no wonder we are overloaded! Since the pandemic might have cut out your drive, you might have replaced it with a walk or workout although you are still receiving data via the radio, a podcast or on the phone. To make matters worse, we employ people to run reports and track metrics on spreadsheets. Every time corporate, a Board member or a customer asks a question, another metric is created. Soon, we employ loads of people to publish data that no one uses to make decisions. How do we throw a line to save ourselves from drowning in data?

Take Stock of Your Data

Collect your data. It is likely to be an eye opening exercise. Take stock of standard reports your ERP system provides. Find out which reports are run frequently, and ask those people what they do with the information. Find out if the reports have to be massaged or adjusted to provide useful information. What has to be changed and why? Take a survey of the metrics your organization is collecting, tracking, or publishing. Ask who is using the metrics and what decisions are made based on the information.

In addition to understanding the volume and use of data, check into your data accuracy. Can folks make directionally correct decisions with your data? Or are there several exceptions that have to be discussed before taking action? If someone not intimately familiar with the data evaluated the report or dashboard, could he/she make a decision?

Reduce the Number of Reports to the Meaningful

We have not yet met a client that wasn’t collecting too much data. It is easy to get too ambitious and lose track of what is meaningful. Ask who would notice if the reports weren’t completed for a week? Go talk to that person and find out why. If no one knows or has a compelling reason to review the report, turn it off or tell the person compiling the information to stop compiling it for the next week or month. See if anyone asks about it.

Attend the meetings where data is discussed. Are people arguing about data or having meaningful discussions about what to do based on the data? If they are debating the accuracy, get the group together to develop ONE report that everyone agrees upon to illustrate the data. Eliminate the rest. For example, a building products manufacturer had several nuances to how they calculated OTIF (on-time-in-full), and so the team would debate the way the data was captured at each meeting instead of acting upon the data. We took a step back and aligned on the meaning of fields, how the data was captured and used, and we consolidated several reports into one cross-functional process to collect and analyze a single source of data. Although it certainly wasn’t the only reason, having meaningful reporting supported key decisions and actions which led to an increase in OTIF by 30%.

Turn Data Into Insights

Simply reducing the number of reports isn’t enough. It is essential to make the information meaningful for decision-making. Understand your sources of data. Connect the data. Cleanse the data. And turn data into insights with dashboards, data models or simply by retrieving the appropriate data for decision-making. It sounds much easier to do than it is in reality. For example, an aerospace client captured open orders and shipment data. Because they selected the data by the order creation date instead of the shipped date, the reports didn’t contain the correct information and didn’t reconcile to the invoicing data. Additionally, because they didn’t have their customer segregated in a key field they used to pull the report, the records that were blank didn’t get captured. Both were easy fixes but poor decisions were being made until the data was reconciled and cleansed. On the other hand, once the data was directionally-correct, they used it to determine the machine capabilities, capacities and staffing required to support their growth plans so they could get in front of their demand.

In another client, they had a proactive executive team for a small, rapidly growing building products company. They tracked potential sales leads, probability of success, sales history by geography and much more in their CRM system. Thus, they knew they needed to focus efforts on a key product line in the northeast because sales were lower than expected. By having this key information at their fingertips, they could target their sales efforts on the customers, products, and locations that would make a meaningful difference to their growth plans. They were recognized as the fastest growing company for several years in a row due to the expert ability to turn data into insights and take appropriate action.

You can turn data into insights no matter what systems you have supporting your business. It is far more important to have the appropriate processes and to focus people’s attention on how to dig into data and use it to make meaningful decisions. With that said, if you can support your data efforts with a business intelligence solution, you will gain a leg up on the competition. The great news is that BI tools are scalable; start small and scale up with complexity as it makes sense to support your business. Once you can slice and dice data and have dashboard available with the push of a button, consider moving on to advanced data topics such as predictive analytics. Instead of solely using data for decision-making, you can take it to the next level and predict your future to get ahead of pack.

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