How Data Analytics Changed Profits and Culture

This blog is a MESA Member Point of View


By Patricia Panchak

Click to download the slides from Vecima’s session at MESA’s 2018 North American Conference.

You don’t have to be a large enterprise with a big IT staff, a team of data scientists and a large budget to implement culture-changing data analytics in your organization, according to Paul Little, Business Intelligence Analyst, Vecima Networks. The company conceptualizes, designs and manufactures cable network equipment and software for cable and networking vendors such as Comcast, Charter and Cox.

At the 2018 MESA North American Conference, Little described how the $71 million (Canadian) company made just such a transition.

No “Burning Platform”

When Vecima set out to improve its use of data analytics and visualization, it had enjoyed 29 consecutive years of profitability, but believed that “Success can hide inefficiency,” Little said, explaining that when everything seems to be fine, “you should still want to take that introspective look at everything you do as a company, to see areas where you can still improve, so you continue to have success into the future.”

What Vecima wanted to get under control was the proliferation of reports, especially the many Excel spreadsheets maintained by individuals, and to make sense of the data it was gathering. As at many companies, for example, “At Vecima, we’re very good at gathering data,” Little said. “We have huge databases of our tests, how our parts got put together, what goes into each unit--but we didn’t use it.” 

Of the data it used, much of it was maintained in disconnected spreadsheets, “Excel silos,” Little said. As a result, meetings devolved into debates over whose data was most accurate, and operational and other business decisions were made based on “gut feel,” not data. 

Changing the conversation—from arguing over who had the best data to collaborating on the actionable response to agreed-upon data--required that the company build a data platform that decision-makers could trust--“one source of truth.” Vecima opted to implement a BI Appliance from SAS, which allowed it to easily import existing data and make it available to users in an easy-to-use, visual interface.

Early Successes

Three areas where Vecima achieved early success included manufacturing, sales and finance.

Manufacturing: Vecima tracks two main metrics: Volume Made and Product First Pass Yield. Using the BI platform, the company put an end to arguments over whether problems were caused by equipment failure or human error. The data clearly identified that 20% of failures were due to employee distraction, lack of training and not using standard operating processes. Drilling down into the data revealed “the exact tasks that were problematic,” Little said. Armed with that information, Vecima executed mitigation plans that resulted in the reduction of human errors from 20% to 2%, for a total savings of $32K per year.

Sales: Before implementing BI Appliance, sales analysis was done using siloed Excel spreadsheets. With no overall database where trends could be identified, there was a 12-month lag in identifying top or fast-growing customers.

With BI, the sales team now has standard data and analysis that is updated daily, with views into customer demands and trends. This allows sales to generate more accurate future sales budgets based on standardized sets of data. 

Finance: While most companies don’t view finance as a data issue, at Vecima 50,000 transactions per month put a strain on finance to create unique reports for each  department.

With the BI solution, Vecima 

• automated the budget review process
• implemented inexpensive Row-level security, which allowed all departments (except R&D, but that’s another story) to use one report template 
• standardized the business and transaction view for easy comparison and to highlight problem transactions quickly

“In those three places at Vecima, the conversations changed,” Little said. “By building that trust, building it together, you really get the user to that Aha! moment, where they say ‘not only do I see a chart, not only do I see that we’re good, but I know what that means. I know I can use that, and I can now start driving decisions based on it.” 

He’s quick to note that the IT support staff had limited experience with BI, and only one had experience with SAS. “All it really took was one person with a good understanding of the business and a good understanding of data,” Little said, noting that that could mean one person or two people closely collaborating.

He concluded: “Now we can see what’s causing our roadblocks and start working ahead of them, rather than trying to catch up to them.” 

Patricia Panchak is an independent business and technology journalist, editor and public speaker. She can be reached at ppanchak@roadrunner.com.