“The Bear” on Business

I used to think people who didn’t cash out big during the telecom and dot-com boom were simply unlucky. Then my phone rang. It turns out Mark Cuban follows BearOnBusiness.com. 

After reading yesterday’s post, he called me up. At first I was skeptical but the more he explained, the more my perspective changed. Who says the Bear doesn’t respond well to feedback? 

Our conversation went something like this: 

“Dan, what do you mean most people were unlucky?”
 
I started with an easy example. “Take for example my niece. Smart as a whip. Straight A’s throughout high school and college. Unfortunately, she is 13 years younger than me and she didn’t graduate until 1998. She was a bit late to the roaring 90’s telecom/dot-com party.”

Mark didn’t buy it: “Bill Gates wrote DOS while still in high school. And did you see how young that Myspace guy is?”  

I brought up my buddy John. After graduating top in his class at Prairie State (a.k.a. Harvard on Halsted), he became a consultant and ended up assigned to automotive companies. He did well over the years as he helped car makers and their suppliers avoid bankruptcy and restructure their operations. “Through no fault of his, he ended up in the wrong industry.”

Mark wouldn’t have it. “Was he an idiot? Didn’t he see how telecommunications was going to change the way people lived, worked and were entertained? Didn’t he smell the Internet coming? He has no one to blame but himself, though I’ve heard good things about Prairie State.”

“What about my friend Lisa? She worked for ICG Communications in 1999. She was offered a job at Verio, a rollup of ISPs. ICG was doing so well at the time and Verio was an unknown start-up. It turns out she passed on the job. Verio was sold to NTT for $6B in cash while ICG went bankrupt. She told me her options would have been worth $3M if she took the NTT job.”

Mark shrugged his shoulders. “Silly her. She made a bad decision. Sloppy more than unlucky.” 

(phone call continues on Monday)

Yesterday’s post asked were the dot-com/telecom boom millionaires just lucky?

Lucky doesn’t mean they didn’t work hard nor does it mean they aren’t smart. But let’s face it, lots and lots of smart people are out there, and many of them work very hard too. Most of these high IQ hard workers don’t make millions of dollars in the span of a few years.

A safe conclusion is that these dot-com/telecom millionaires should be thankful for their good luck. Perhaps they were blessed with with exceptional business or technical capabilities, but these attributes are unlikely the reason for their new-found fortune. A more likely explanation is that they hit the jackpot when their numbers came up in the telecom/dot-com lottery.

“So what?” you ask, perhaps sensing I might be rubbing it in a bit. After all, my number was one of those that popped. Tomorrow I will address the “so what” question.

I suspect the majority of BearOnBusiness.com readers were part of the telecom and dot-com boom. With this as an assumption, I ask you to think about people you know who cashed out big. 

Perhaps their company was sold at the just right time and their equity was converted to a cash windfall. Or perhaps their company went public, and they sold their vested stock options at the peak of the bubble. 

Though I never counted, I probably know several hundred people who ended up making millions. I know a few dozen who took out more than $10M.

So here is my question: Of the people who made millions, what portion was lucky—that is, how many were simply in the right place at the right time?

More to follow on next several posts…

Jerry Mills Collins was one of the original members of the Trammps. The following quote is from Wikipedia:

In 2000, group member Jerry Mills Collins was convicted of beating his wife with a handgun on Valentine’s Day when he suspected her of infidelity. Collins was found guilty and sentenced to 12-35 years in prison.

If you don’t believe me, click here to see it.

Given my newfound affinity for Disco Inferno, I pondered what could have caused Jerry to take such a horrible turn in his life. I researched further into it and found this–please click here. It certainly explains why after 1999 he was never the same again. 

This last disconnect post (for a while) will cover a few odds and ends on churn.

1. Establish a clear definition of disconnect: For example, a disconnect is an event where an existing customer no longer needs a particular service thereby causing revenue to be removed from our billable run rate.
2. Include re-rates: It is usually better to retain a customer and lower the price than lose the customer all together. However, the disconnect process must capture the impact of price decreases. It should be categorized differently than a pure disconnect.
3. Disconnect metrics should capture both disconnects and re-rates: Though re-rates are less painful, they still must be included in reports that track the revenue attrition.
4. Include disconnects that are associated with upgrades: In Telecom-land, a customer disconnect is sometimes the result of the customer stepping-up to a higher level of service. For example, the customer replaces an OC-3 with an OC-12. Sometimes these are referred to as good disconnects especially if the amount of revenue is higher after the upgrade. My philosophy is to treat these disconnects just like all others–and treat the new service as a new sale. The net positive impact comes out in how we track net installs (that is, gross installs less gross disconnects.) For those who treat good disconnects differently, I offer a word of caution. Read my prior post again to understand how tempting it is to call murky situations a good disconnect if this term is more socially acceptable than a bad disconnect, thereby creating false security.
5. Verify accuracy of reporting: I’m not sure exactly how our folks do this but I know they do. In general, they run billing reports that compare this month’s recurring revenue to the prior month. Changes are flagged and compared to the disconnects that are tabulated in the managements reports. The goal is that 100% of actual billing changes have been included in management reports–and vice  versa. When there are exceptions, the process is analyzed for what caused the miss and the process is tightened as a result. The goal is two-fold: (1) we don’t want a false sense of security about what is really happening with disconnects, and (2) we want to make sure revenue that should be billed is in fact billed.
6. Set reasonable goals: Generally speaking, a disconnect rate of 1% or less is excellent. (1% means that 99% percent of last month’s revenue was retained during the current month.) 1.2-1.4% is usually acceptable. 1.4 to 1.7% is manageable but not comforting.  Above 1.7% is generally a sign of bigger problems.

With this completed, I hope to never have to write about disconnects again. More importantly, I hope I side-step the next Disconnect Inferno.

A while back, I wrote posts pertaining to how we expect operations to accurately predict when sold (but not yet installed) orders (which we call pipeline) will get installed. Prior to that, I covered how our account execs are expected to accurately predict how much revenue they will sell. The past week of posts pertained to disconnects. 

Like sales and installs, we develop processes around forecasting disconnects. At Zayo, the disconnect forecasting process is in its infancy, though I suspect it is still more advanced than many other telecom companies. 

It is helpful to break disconnects into three categories:

1. Disconnects that might happen
2. Disconnect orders that have been received but the disconnect itself has not yet occured
3. Disconnects that have already occurred

A solid-as-a-rock disconnect process is one that enables management to focus on Category 1 situaitons.  If you have early warning of where you might be vulnerable, that probably means that your company is taking steps to avoid the disconnect.

Category 2 is important as well.  Often, customers will send in disconnect orders prior to their contract expiring.  Or, perhaps, there are ramifications, such as early termination penalities, associated with certain disconnects. A tight process flags these orders on the front end and ensures that the company is not short-changed in the process. As importantly, this stage sometimes provides the opportunity to make one last ditch effort to save the opportunity.

It is almost by definition that Category 3 means it is too late to save the order. However, Category 3 is important for forecasting cash flows–which BearOnBusiness.com readers know is one of my fundamental management principles. Moreover, accurate and timely reporting on Category 3 helps improve customer retention processes. 

We have a long way to go at Zayo before our processes will be what I want them to be. I’d like to see us using Salesforce.com as a tool for flagging potential disconnects in the same way we highlight potential sales. I’d like to see verification that we have spent weeks trying to avoid each and every disconnect before it hit our system. I’d like to witness the creativity and persistence of our employees as they turn churn opportunities into new long term contracts. 

We will get there, but it will take some time.

A title on one of my recent blogs was Like Fingernails on a Blackboard. One of the people on the Zayo team felt as passionately on that topic as me–but she felt a better title would have been Like a Pencil in the Eye. Well, I know she will be pleased that title was still available for this post.

“Disconnects just happen.”    

Give me a pencil. Give me Scarano’s eye. 

It is true that disconnects are sometimes unavoidable: a customer might move, their business might shut down or their needs might change in a way that your company simply can’t address. My educated guess is that the majority of disconnects do not fall into this unavoidable category. 

“I have a report that will show you are wrong,” you might be thinking. Be careful. Read the previous post. Is the report tabulated using ‘objective reality’ or is it influenced by ’subjective ass-covering’? Let me explain.

Let’s say we had a tracking process to explain reasons for disconnects. The process had only two check boxes.  

Check box #1 if the customer disconnected for any of the following reasons: 

• Customer moved to a geography ourside our service territory
• Customer went bankrupt
• Customer’s needs changed in a way that we were unable or unwilling to serve them

Check box #2 if the customer disconnected for one of the following reasons:

• I have no idea; I’ll check with the customer and get back to you
• I just got this account last quarter; can you check with the previous account exec?
• The decision-maker changed a few months back–I haven’t gotten around to building a relationship with her replacement yet
• I have bigger accounts I’m worried about
• Why would I care? My commission check is based on new sales. It is hardly worth my time to preserve existing revenue.
• The customer upgraded their service and, in the process, choose a different provider; by the time we found out what was happening, it was too late
• A competitor offered better pricing; if we only knew, we could have saved them
• The service from us was out-of-term. I didn’t want to bring this up for fear of losing them as a customer
• Our service has been spotty. If I were them, I would have switched too.
• The customer needed things from us that required a few simple modifications to our product. It is easier to move a mountain that to get something out of marketing and IT.

Got the picture? Assume you can do something to avoid the majority of disconnects. Use this assumption to improve customer retention. Don’t be too quick to rationalize that disconnects just happen.

Come to think of it, though, there are worse things in life than poking Scarano in the eye with a pencil.

Zayo Group is a roll-up of fiber-based telecom companies. We began (sort of) in late 2006. We researched every telecom company that had a fiber-based network. We contacted nearly all of them. We met with over half. We were impressed with some of the day-to-day operations. In other cases, we were simply perplexed. In any case, we were privy to the inner-workings of lots of the telecom boom survivors.

In some of the impressive situations, we observed a strong focus on preserving revenue. These teams either learned from the meltdown or, perhaps, they weren’t the ones guilty of ignoring their embedded base during the boom. 

Some situations were so-so. 

However, we also encountered companies that didn’t pay sufficient attention to disconnects. In a few cases, they didn’t even attempt to tabulate how much revenue was churning. 

Somewhat humorous were those situations where management teams insist their churn is low; yet, when pressed to provide evidence, they admit or discover they don’t actually track disconnects. ”But if we did track them,” they often persist, “You’d see how low they are.” Really? 

I’ve even heard, “We don’t track disconnects because they are low.” If there was a such thing as a ‘double really?’, I’d use it here.

Another situation we encountered is companies that had the data to support their claim of low churn. The data, however, was flawed. That is, the data was incomplete and/or inaccurate. 

Weak processes were often the culprit. Disconnects were happening–they just weren’t captured in those reports whose purpose was to tabulate disconnects. Obviously, this isn’t a good outcome. It happens frequently, as rigorous capturing of disconnects takes discipline, focus and tight processes.

Worse, though, are situations where management’s intent is questionable. Management, at times, becomes too enamored with their desire to show that disconnects are impressively low. That is, they don’t understand that the purpose of tracking disconnects is to provide a complete and accurate picture, regardless of whether the results are good or bad. Tracking must be the actual score of the game–not the desired score. The highest responsibility is for the reports to be thorough, accurate and objective. If the results are not good, address the problem; don’t blur the data. 

This sugarcoat tendency happens in various areas of business reporting–but it is likely more prevalent in the area of disconnects than in most other areas. Why? First, ascertaining disconnects and validating reporting is tedious. Second, it is highly unlikely the auditors, board of directors, shareholders or even CEO will tune into reporting methodology until problems become pronounced. By the time the problem is big, it is usually too late. The company now is in crisis mode. 

The first-order problem in crisis mode is what to do about the high disconnects and shrinking revenue. Once in crisis mode, the fact that inaccurate reporting contributed to the problem is, frankly, a secondary concern. Ironically, executives that thrive in crisis situations are in their element at this point, even if it was these same executives who caused the crisis by taking their eye off the ball.

Does your company track disconnects? Are the processes tight? Is the reporting accurate? Does your company use the data to measure its effectiveness in minimizing disconnects? If not, what will you do about it?

During the telecom meltdown, many companies discovered disconnects were a powerful force. Painful too.

The problem is that they discovered this DURING the meltdown (instead of during the disco revolution.) In many cases, the meltdown had already crippled their business.  Only then did they begin to focus on tightening their processes around disconnects; only then did they re-think their incentive schemes. By the time “disconnects” became part of the culture, it was a negative and devastating influence. In many cases, the last surviving memory of the boom-era customers is collapsing revenue.

At this point, you’re probably right–I am being a bit too dramatic. But perhaps not.

The overall theme of the BearOnBusiness.com blog is “what have we learned” as a result of the telecom boom and meltdown. Well, the need to rigorously and thoroughly manage disconnects is a lesson learned that many in our industry have yet to get a grip on.

This is amazing to me. I will repeat. Amazing.

How do I know this is true? See tomorrow’s post.

Do you like that as a tongue twister?

The past few posts referred to the disconnect inferno of the early 2000’s. “That was then,” is the hallway chatter I heard throughout the telecom universe. “It is good it is behind us.”

Is it? I don’t know if you noticed, but we might be smack in the middle of a recession. The telecom industry continues to consolidate. Technology continues to change. If disco returned, I might be somewhat nostalgic. If the telecom meltdown reared its ugly head, nauseated would be a better description how those in the telecom world would feel.

My point is this: disconnects need to be a focal point of operating a telecom business in both good times and bad. Preserving revenue is just as important–perhaps even more important–than selling additional revenue. Culture, business process and incentive plans should reflect this.

I hope those readers who are part of Zayo, Envysion and NGT reflect on this. In addition to observing evidence of this in your day-to-day work situation, I’d like you to ponder additional ways in which we can combat disconnects. And by the way, combat is a good word for this topic–especially in tough times. Remember the swimming upstream analogy–simply swimming harder is not a good plan. Combating disconnects requires focus, cleverness and persistence. More on this in future posts.