If you had to rank your organization’s data systems on a scale from cutting-edge to in need of updates, where would they fall? If they lean more toward the latter, chances are it’s not your fault. You’re likely working with siloed systems that have been bolted on over time to address different needs as they arise.
Your estimating and quoting processes, for instance, may take place in a different system than you bill from. And for things as interrelated as estimating and billing, system silos can become a big problem. You can very easily end up with an estimate and bill of materials (BOM) in a format in one system, and the invoice in a different format somewhere else. This makes it extremely difficult to connect any data points between the two and understand what a customer bought on an individual level, much less at scale across all your customers.
That’s enough data entanglement for one entity alone – not to mention acquisitions, consolidation, and mergers – which can add another set of disparate systems that increase the complexity exponentially. While some inherited systems will be in better shape than others, you’re still left with the challenge of bringing them all together.
Without the right people and skillsets, this is where the web of data systems gets really complicated. The more systems you have that don’t or can’t talk to each other, the less control you have over them, and the less reliable and functional your data becomes.
You might be thinking, why does this really matter? You know you aren’t the only packaging provider operating this way, and you've been running like this for years or even decades.
What You’re Risking
Take two estimators, for example. One is rolling through estimates with a stamp of approval, while the other is meticulously correcting cost inconsistencies. With separate systems and no real way to look at any of this data together, you can end up with customers who are highly profitable and others who are significantly less or entirely unprofitable.
These challenges exist across countless other businesses, too. But when you combine the custom nature of packaging providers with the variability of human estimators, they become much more pronounced. So now, in addition to other priorities, you have to figure out how to clean up your data and right-size siloed systems and processes to help make that happen.
While costly consultants may devise a plan that looks good on paper, they won’t stick around and help with implementation to see it to fruition. That’s where a partner like Revenue Analytics comes in.
With Pricing-as-a-Service, built specifically for complex industries like yours, you get ongoing support from a team with the IT horsepower, skillsets, and technology to process your data from any source, in any format. Once it's all together it can be validated at scale to help identify outliers and what caused them to address root causes of profit erosion, like siloed systems and data.
To learn more about how we can help turn your siloed data into profitable decisions that align to your business’s unique needs, talk to one of our pricing experts.
