My lawn man fired me last week. Actually, he fired my wife Candy and I was just the collateral damage.
To explain, he has been maintaining our yard for my wife the past five years. I know this because the cancelled checks come my way every month at statement time. We got the call on a Sunday morning. “Ms. Johnson, I’m not coming to mow your grass again.” His reasons? We’re his only clients in this part of town and the costs of keeping us as clients are higher than the lost opportunities of adding two clients in his part of town if he drops us. I couldn’t argue logic that was so well supported by data. And now I have to mow the grass this weekend. In Houston’s pre-summer balmy season we call spring and still comfortably enveloped in the extra fifteen pounds I let myself gain under the guise of needing insulation for my winter trips to Boston.
Apparently our former lawn man has embraced a Sales & Operations Planning best practice known as tradeoffs-derived decisions. He finally evaluated his overall cost of doing business with us versus possible opportunities of taking on new clients who are closer to his home. We’re less profitable. We got fired.
That got me to thinking about the power of integrated information for business people. The more trusted information that is accurate, available, and accessible to enterprise processes —like S&OP—the more business tradeoffs can be evaluated. That’s pretty much a foregone conclusion. For S&OP teams, much of that data might reside in a data warehouse, data mart or demand signal repository, and they are constantly adding new data sources as they come available.
As is nearly always the case, the dilemma is time. Planners work in three time horizons—tactical, operational and strategic. Add to the time horizons the increasing drumbeat for agile business processes and agile market responses across nearly every business segment and the challenge is time. For product manufacturers, the need for the most easily and quickly reconfigurable data relationships is in the tactical time horizon when their analytics are asking questions that will support inventory mixes during pricing promotion, new product introductions or channel-specific packaging to capture market share. They are almost always one-shot, time bound opportunities to get things as right as possible.
Although large scale data warehouses and repositories are the perfect support structure for strategic planning, they can often miss on the need to support agile business processes. Forget the cycle time between formulating questions to getting them in a queue to getting answers. Business people are, well, business people. They think in terms of products, customers, markets and other groupings of data elements that define their business models. From my experience, they work best in environments where THEIR models are their interface to data hierarchies, flows and logic. It’s how many of their applications work. It’s how they configure their promotions and target store clusters, regions and competitors.
Thinking about my S&OP experiences, I can see how strategy could be translated to tactical execution so much quicker if data could be gotten at sooner. And from the context of a business person, that speed comes through insights created through contextual models that reflect the way they think.
I’m a big fan of contextual model driven interactions with data. And a huge proponent of business agility as a disruptive market force. The two go hand in hand and that’s why I love the raw potential where I work. A model driven approach to integrating, managing and accessing data makes it an asset that can drive agility for business people.
This weekend, I’ll likely reminisce about the good old days when our lawn man was the yard man instead of the strategic thinker he’s become as I push the mower around grass that grows too fast. I’m guessing that I’ll assume it was one of the signals from the Fickle Finger of Fate that I need to look really hard at how much speed I think we can drive into data/time-sensitive business processes like S&OP and then go help some businesses make their data warehouses go fast. Imagine that. Agile warehouses for the masses.
What do you think?