[ad_1]
In a prior article, entitled The First Rule for Better Business Decisions: You Must Have Timely and Digestible Data, I discussed the importance of having access to financial and operating information that is both timely and digestible. Let's call that type of information "good data."
So you've got good data ... now what do you do with it?
Slice it and dice it, milk it, decode it, leverage it! In industry parlance, "apply intelligence" to the data.
What does that mean?
It means using the power of a software application to identify data relationships and absolutes ... then using that information to make better, smarter, and quicker management decisions.
Huh?
In practical terms, it means (i) comparing and benchmarking individual units or any group of units side-by-side with other units, groups of units, or the enterprise enterprise, and (ii) looking at aggregated financial and operating numbers and ratios , using filters customized to your business, to:
(a) first find, and then broadly implement, specific best practices,
(b) spot anomalies and specific problems early, and then correct them proactively,
(c) measure and test (in real real time) marketing initiatives and operational changes, and
(d) profit from what the aggregated data reveals and from the intrinsic value of the system itself.
Eyes glazing over? Let's cut through the gobbledygook by looking at some examples.
How about a side-by-side P & L-report comparison of Unit A, which is blowing the doors off, with Unit B, which is performing 20% below the average across the network? Both are in the same region, with similar demographics. What gives?
You see that Unit A's revenue is 30% higher than Unit B's, and Unit B's labor costs are 20% higher than Unit A's, with overtime being a whopping 50% higher. Advertising costs are equivalent.
This information - available to the franchisor and (if both units have the same owner) the multi-unit franchisee - pinpoints the areas to drill down on. What exactly is Unit A doing with advertising that Unit B is not, and vice versa? How are Unit A's employees interacting with customers - are they upselling consistently, while Unit B's employees are not customer-centric? What's behind the anomaly on labor with Unit B - manager or training issues? Why is Unit B having difficulty keeping a full staff? The franchisor, Unit A, and Unit B should collorate, even if the units are run by different franchisees; no sharing of specific financials between the units is necessary. Unit A's best practices should be adopted by Unit B. Unit B should focus on getting labor under control.
How about a franchisor or a multi-unit franchisee benchmarking all units against its best (top 10%, top 20%), down to the line-item level? How about seeing how the units rank on the "Big 5" (total revenue, cost of goods, gross profit, expenses, net income) with one click? Or side-by-side comparisons of units using an array of financial ratios?
The franchisor, multi-unit franchisee, and even the one-unit franchisee (who can generate reports on his own data and benchmark against the numbers generated by the top 10% or 20% in the system) can mine golden nuggets of information from these types of relative data comparisons.
The data further increases in value as more intelligence is added. Custom filters enable the owner to set up subsets unique to its operation. For example, franchise XYZ has stand-alone units, in-mall units, units within big-box retailers, footprint layouts of various sizes, and locations in all regions of the country. The franchisor or multi-unit franchisee can compare financial metrics of any subsets or combinations of subsets. It may use that data to optimize footprints, fine tune its mix of types of units, expand or eliminate a particular type of unit, or encourage new franchiseses to stay the course (by showing data from the subset of established franchiseses) - or to take any number of other management actions.
How about measuring one marketing initiative against one or more others? How do Campaigns A, B, and C stack up? On similarly-positioned units (choose your metrics), which campaign boosted revenues the most? Which campaign won on gross margin and net income results? Are there regional or other differences, such that a mixture of parts from each campaign or some of the campaigns is the best approach? Remember, this is fresh, current data that you can observe daily; you can see changes and make adjustments almost immediately. Think about the competitive advantages. Think about the improved bottom lines.
What about using aggregated data to your advantage? By aggregating expense-by-vendor data across the enterprise, you discover that group spending on item X (for example, office supplies, for a QSR franchise) is a significant number, spread across a dozen vendors ... yet this information has never been leveraged. So you take the dollar volume amount and get bids from two or more national office-supply vendors, and may the best man win. The result? That line-item expense is cut by an average of 5% across all units.
Here's one last example.
What if you, the franchisor, or you, the big multi-unit franchisee, want to sell? What will the buyer do if you can not provide current financial and operating data on all units in the enterprise, in an organized, usable form? Most likely, it will apply a "black box" discount for the unknowns. Top-line numbers and trending are only the first level of due diligence. How does the buyer get a handle on how things are going at ground level - the day-to-day operating conditions of the units themselves? If that information is opaque or entirely MIA, the buyer will make certain assumptions, but those assumptions are more more likely to tilt in the buyer's favor, to discount the risk of unknowns returning their ugly heads after closing.
On the other hand, if the seller can show the buyer (a) exactly what's happening financially at the unit level, regional level, and national level, and (b) a level of sophistication and operational knowledge about optimizing results by proactive management through use of technology and collaboration, then the seller has eliminated the black-box discount and further boosted valuation by having an in-place system that the buyer can hop into without missing a beat. Similar benefits would apply in a financing scenario.
For well-managed franchise systems, particularly fast-growing ones, providing this visibility is essentially providing your worth and quantifying your valuation. The reward is a higher multiple and higher sales price.
Getting smart with good data is all about having a system that allows you to extract every possible nugget of information generated by your enterprise, easily and quickly, to take action to optimize performance and boost the bottom line at every level. It's a platform for profitable collaboration.
[ad_2]
Source by James M Wallace Jr
No comments:
Post a Comment