Getting Started with Data Analytics: Five Questions You Need to Ask

It’s impossible to visit industry events and news sites without coming across articles and “experts” trumpeting Big Data as the answer for everything that ails the world. It has been hailed as the perfect fix for every challenge and inefficiency found in the supply chain and warehouse.

Data analytics does offer tangible benefits and real business value for supply chains, warehouses and distribution centers. Unfortunately, the benefits and value have been overshadowed by all the hype. This has resulted in a lot of confusion, frustration and false starts as pilot projects don’t deliver on exaggerated claims or require more resources, time and dollars than initially suggested.

Much of this can be blamed on overpromises and unrealistic expectations. However, it is also caused by a failure to help supply chain executives and warehouse managers understand how to get started with data analytics; how best to manage the process to work toward measurable, obtainable goals and deliver value; and how to identify, prioritize and act on the data that is gathered.

Making an investment in Big Data is important. While cost and complexity are valid concerns, when done correctly and deliberately, data analytics can provide valuable visibility into your operations. Much of the technology involved is proven, relatively simple and available today. 

When you approach Big Data with an informed and strategic focus, you can position your facility for future optimization and give your company a powerful tool to identify and resolve issues that drain productivity and hinder efficiency.

For instance, consider the forklift. There is a wealth of forklift data that can be gathered through forklift fleet management systems, including data on operator performance, equipment status and health, and product movement.

So, in an effort to help you move beyond the hype and take a deliberate and informed approach to Big Data, here are five questions you should ask as you get started.

1. WHAT DATA DO YOU WANT TO GATHER AND TRACK?

A common mistake many companies make when starting with data analytics is that they lack focus. They try to track and gather too much data. They quickly are overwhelmed, and in many cases, they end up turning off sensors or alerts and data goes unanalyzed and unused. When it comes to Big Data, I’m always reminded of the Desmond Tutu quote: “There is only one way to eat an elephant: a bite at a time.” The key to successfully tackling Big Data is small bites.

An ideal, manageable approach for beginners is to focus on one or two operational objectives. For instance, maybe it’s monitoring forklift impacts with the goal to reduce them. By tracking and analyzing the data you can easily determine responsibility and frequency, and identify a course of action.

2. DO YOU WANT REAL-TIME OR HISTORICAL DATA, OR BOTH?

When you go to your ATM and check your bank balance, that’s real-time data. When you log onto your account to see the dates and amounts of your withdrawals the past year, that’s historical. For some companies and applications, it might be easier to start with real-time data because it does not require much analysis. If you want to add historical data, you will need to make sure your provider and/or system has batch processing and data analytics capabilities. You will also need to decide whether the data will be housed in the cloud, by your vendor or on a company server.

With forklifts, a real-time data approach would be getting an alert every time there is an impact above a certain threshold, or a maintenance issue that needs to be addressed. A historical data approach would be tracking the frequency of impacts to identify operators who may need additional training, or tracking certain maintenance issues to determine the pattern of occurrence for predictive maintenance.

3. HOW ARE YOU GOING TO RECEIVE THE DATA?

It is important to choose a system and service provider that enables you to consolidate the data and deliver it to the people who need it in a way that is useful and supports decision making. You also need to have processes and algorithms in place to help analyze the data so actionable information can be shared with the right people so they can address issues more accurately and efficiently.

From a technology perspective, you also need to ensure your facility network infrastructure has the capability and capacity to move data from equipment and sensors to your management system. How will it then be shared with the right people? For instance, forklifts can be equipped with communication devices that allow information to be communicated directly to operators. You also will eventually want to share data from one system with other warehouse systems, and vice versa, to get a more complete view of your operations.

4. HOW ARE YOU GOING TO ACT ON THE DATA?

While most organizations put significant effort toward planning the implementation of data analytics, many don’t give enough thought to what comes next. You need to have a plan in place to institute accountability and action. To realize success, you need to have in place the processes, resources, support (internal and external) and commitment to make decisions and take action based on what the data is telling you. And you need to make sure the data gets to the right people.

Let’s again look at forklift impacts. If an impact alert is sent, a manager can take that information and investigate the situation and speak with the operator. If data shows impacts routinely happening in one area of the facility, the facility manager can be brought in to consider any changes to facility layout. If certain operators continue to have a high number of impacts, managers can consider incentives and additional training to ensure correct behavior.

5. HOW ARE YOU GOING TO MEASURE PROGRESS AND SUCCESS?

This goes back to the data you are tracking and the goals you set out to achieve. Demonstrating the value of your data analytics through achievements—such as a reduction in impacts, increased efficiency, or higher productivity—creates internal buy-in and can provide the confidence and additional resources to tackle more complex challenges. Once you have made progress on your initial goals, you can target new goals and data points.

The technology is available today to gather and track data that can provide insight into your operations. However, in order to get the most out of your data analytics, you need to see beyond the hype and remember that it’s not about how much data you can collect, but rather the type of data and what you do with it.

While there can be challenges to effectively implementing data analytics, working with the right partner, asking the right questions and developing the right approach will help you make meaningful changes to your operation and realize short- and long-term returns on your investment.

Collin Rush is general manager, Crown Insite customer support, with forklift manufacturer Crown Equipment Corp.