By Laser 1 Technologies
Data Overload: Distilling Data For The Win
After all the advances in computing power in the last few decades, we’re in the era of big data, and we’re not going back.
We’ve talked about big data before. Here’s how Wikipedia defines it:
Big data is data sets that are so big and complex that traditional data-processing application software is inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source
Obviously, that’s pretty subjective—for some people, that describes their relationship with their checking account.
But the point is: It’s easy to feel like you’re drowning in data these days, because there is so much of it. When faced with the huge volume of data that’s at your fingertips every day, week, month and year, it’s no surprise you might feel overwhelmed and suffer analysis paralysis. However, data is your friend, especially in manufacturing, so it’s crucial to make peace with it and figure out which elements you benefit from staying on top of.
Here are three arenas to think about when harnessing data for operational benefit: Data management, inventory, and gross margin. They can be viewed independently, but they are also interconnected.
Data Management
Here’s the ideal scenario: A company’s data is gathered and channeled into a data eco-system, then business intelligence hardware dissects it. A team of analysts assess the information, revealing what needs to change in daily operations. Sounds simple, but it seldom is, especially as the volume of data grows. The greater the volume of data, the greater the skills and time required to process it meaningfully.
Ask questions like these to help narrow down the most pertinent data for your company’s needs:
- What sources of data have paid off in the past to measure, analyze, and sustain your business? Which have turned out to be unproductive?
- By crunching current sources of data, where can you instigate rapid improvement for quick impact on your bottom line? Consider inventory management, ERP efficacies, EDI effectiveness, and so on.
- What information is hiding in the data, accessible to someone who understands how to read it? There may be unseen gaps in critical information and data; unforeseen vulnerabilities in inventory cost and overall expenses; missed opportunities.
- What’s the most useful way to visualize the information that drives your business? For some, it’s year-to-date profit/loss; for others it might be order fulfillment or pending orders.
- What matters most as you make decisions to grow your business? It might be market awareness and trends, goal creation and recognition or personnel effectiveness and performance.
Inventory Issues
Inventory has a huge impact on profit margins. Hitting the sweet spot is a challenge, but worth the effort. Excess inventory translates into sunken expenditures along with costs relating to storage, management, insurance, and possibly deterioration or obsolescence. Inventory shortages translate into unfulfilled orders and production disruption. Both are to be avoided, and data analysis is the primary tool for addressing inventory issues.
Gross Margin Management
Gross margin is a lens into profit and productivity—it’s a leading indicator profits and cash flow. You depend on gross margin to cover expenses, and it’s a key indicator of how productive an inventory investment is.
Some tips for managing gross margin:
- Careful control of suppliers pays off: Commit to cost control in purchasing.
- Strategic markup: You don’t want to leave money on the table, nor do you want to drive customers to lower-priced competitors.
- Consider the industry. Figures vary widely across industries, so make comparisions within the appropriate industry.
Choose Your Data Battles
If you’re feeling overwhelmed by data, you’re not alone. It’s the “new normal” in this technical age. Accept that you’ll never master all of it, choose your battles, and extract the information that best serves your needs.