What metrics do I need?

My last post talked about the need for organizations to invest in and take the time to develop key metrics for their business.  If you buy into this, then the next question you ask is, “OK… what metrics do I need?”.  The key to good metrics is that they objectively measure the changes you implement in your organization.  The idea is that you only make one small change at a time and then measure that change to evaluate if the change actually improved anything.  This is essentially the scientific method, and is the same process Thomas Edison went through to create his many inventions, including the light bulb.  You would think that in the last hundred years of science and innovation, we’d have a better understanding of the type of activities that went on in Edison’s lab, but sadly many businesses still operate out of intuition and feeling versus the hard information that come out of objective analysis of facts.

What metrics do is get us knowledge instead of information.  This knowledge gives us visibility into the “improvement” activities we are doing in our organization to see if they are actually working.  We call these metrics economic engines from Jim Collin’s book Good to Great.  There are two engines that give us visibility into improving the economic health of our organization— growth engines and profit engines.  It is important to separate growth engines from profit engines because we have all heard of stories of companies that grow like crazy, but end up growing out of business because they didn’t understand the economic realities of the cost structure needed to support their sales.  On the flip side we’ve heard of companies that have an incredibly profitable and well tuned machine, but seam to have troubles growing.  Let’s look into each engine more.

Graph from The Lean Startup by Eric Reis. Click on the image to buy from amazon and support the book.

Growth Engines

Growth Engine metrics are tied to how you get new business in the door.  One of the great tools for this metrics is looking at funnel graphs.  This type of graph shows the process with which you a lead into a sale.  For a company that focuses on direct sales, the steps in their funnel might be: lead -> appointment -> presentation -> sale.  For an online web application, this process might be: visitor -> trial sign-up -> first login -> paid account.   The first step is to identify the process our organization goes through to increase business.  The next step is to implement some sort of tracking plan that looks at the sales process within segments of time.  Time is important because numbers are only useful when they are compared to other numbers.  When evaluating numbers in the context of time, you can see if the changes you make in your growth engine are actually improving results.  The graph to the right shows a funnel graph taken from Eric Reis’ book “The Lean Startup“.  It shows the % of people that moved through each step of the growth engine for a company called IMVU.  Their process was Registered -> Logged in -> Had one conversation -> Had five conversations -> Paid.  In his book, Eric makes the point that IMVU was making an incredible amount of improvements in their product, but as they analyzed the funnel graph, they realized these changes were not translating into more paid customers.    IMVU started to realize that their activities were not actually creating value for the product.  This knowledge forced them to make some hard decisions about what they thought their product should be and why customers were interested in it.  What an incredible example making better decisions with just ONE simple graph.

In my last article, I told the story of when I worked in a marketing department if a computer training company and my job was to track marketing expenditures and compare them with the results of sales.  I created a report for management with just a couple simple metrics.  One of them was the cost per lead and cost per sale of each marketing medium (eg yellow pages, direct sales, television, newspaper).  One of the things we realized from the reports was that our ads in yellow pages and newspapers where becoming less effective.  It was the mid-90s and the economy had really started to take off and was nearing full employment.  The mass amount of people were not looking for new skills because they already had a job.  So, we changed to more “intrusive” ad mediums placing more ads on TV with a different message focused on the idea that computer skills could provide a better job.  We changed one thing at a time and then measured the effect.  From the cost per lead and cost per sale metrics we found that the new TV ads were much more effective than other types of ads.

Profit Engines

Jim Collins says in Good to Great“If you could pick one and only one ratio – profit per x ( or in the social sector, cash flow per x) -to systematically increase over time, what x would have the greatest and most sustainable impact on your economic engine. ”  He goes on to show that each company in their study had created value by focusing on a simple and singular metric that gave them key understanding of what the economic drivers where of their organization.  Jim Collins provides many examples of an economic engine: profit per employee for Wells Fargo, profit per customer visit for Walgreens or profit per ton of finished steel for Nucor.

I experienced the value of profit metrics first hand when I took a break from technology for three years and managed the plant of a vinyl window manufacturer.  The owner was great at establishing simple metrics for evaluating the performance of the plant.  Like any business if you wait to view information at the end of the month or at the end of a quarter, it is too late.  So, at the end of each day the owner wanted to see two metrics from me: completed product and shop wages.  These metrics gave him a picture of the value of the product that went through the shop and also gave him a picture of what the cost of wages were for that product.  While material goods was the biggest cost of manufacturing, we had optimization software in place that made this cost fairly easy to predict and fairly consistent over time.  This metric wasn’t something the shop had an incredible amount of control over.  But wages were the next highest expense and we had incredible control over this metric.  And in a low margin business like most of the manufacturing sector a metric like wages could mean the difference between sustainable profits and going out of business.

Again, any metric we create must be simple and it must give us data in some sort of context.  This gives us better decision making ability so we can see if we are improving or not.    When we create our metrics correctly, even my eight year old son can understand them.  But don’t let simplicity fool you, because it does not mean easy.   It takes hard work, discipline and vision to implement systems that give us valuable metrics.  So start to push for these metrics now in your organization.  Test your processes by making small changes and then measuring them with metrics.  As you start, don’t worry if you don’t have things automated right away.  Once you have metric creation systems put in place, and you are sure you have chosen metrics that measure things that actually effect one of your economic engines, then you can start to think about automating the process.  The light these metrics shine on your ability to make decisions may seem as magical as the first light bulb would have seemed to the people of Thomas Edison’s day.

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