This is my first post of 2005. Happy New Year!
It's always great to talk to senior V and C-level executives to get the 30,000 foot level view of the world. And you just can't get a better feel for the trends and market forces shaping the industry and their impacts on the business.
But the key challenge is to then delve into the details of those business trends and understand how they affect business processes, individuals and the ongoing trajectory of a company's performance. This is where diving into business data becomes invaluable.
In my experience, getting and analyzing business data is an art. Take customer segmentation realted analytics. Even though there are a host of CRM solutions that help examine different customer based performance activity, the trick is to first figure out what you need to look at. As an example, we can look at customer segmentation with respect to different working capital processes:
(You can read my previous posting on Customer Segmentation to Manage Working Capital Risk to get a better background on what I'm talking about).
Some key data elements to look at are:
1. Customer payment history over time - DSO by customer, average days late, average time to pay, broken promises to pay, etc...
2. Customer level inventory metrics - Inventory Turns, % of spend attributed to specific customers, if possible, excess & obsolete inventory by customer...
3. Forecast and demand changes/variations over time per customer
4. Customer level credit scoring, both for new and existing accounts
5. Revenue segmentation by customer and customer region, gross margin by customer
and it goes on and on and on...
I also like the Gross Margin Return on Investment calculation that a lot of retailers use to plan and measure their assortments. One great thing about this is that it gives a great view into which customers and products to protect, which to nurture and grow and which to prune from the portfolio.
Again, having the right data is key in any type of analysis. Specific to working capital management, I'd recommend keeping in mind the following:
1. Remember that working capital data is often strewn around the supply chain - account for different data sources, different trading partners, different global regions, etc
2. You have to have a representative sample of historical data to analyze. For example, if you are aalyzing an A/R portfolio, you need to get at least a year's worth across multiple business lines. This helps to identify cyclicality in payments, billings, etc.. Also you can slice and dice the data to see the effects on different operating theaters
3. Oftentimes, the important parts of the data analysis is seeing what is not shown. Although many people might disagree, I think if you're cofortable with your data integrity, you can do some correlation and estimate whether you assumpations about working capital operations is true. For example, if you were analzying revenues for a CPG (Consumer Packaged Goods) company, you may expect to see a great deal of seasonality in revenues. However if the data does not point tot his situation, you can then dive into the root causes - maybe deductions are higher due to New Product Introductions, complex promotions, slotting fee hikes, etc...
It's helpful to keep an open mind to possibilities and think outside of the box when really trying to infer business knowledge from a stream of data.
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