Top 5 Mistakes in Managed and Cloud Services Business Models

For any product or service, being able to create realistic and achievable business models is key to setting expectations as to the revenue and profit potential. This particularly applies to managed and cloud services, which often have high up front investments and barriers to entry, as well aslong complex, sales cycles. Especially with managed and cloud services, careful consideration needs to be paid to the variables that affect the cost and revenue curves: they both have sensitivities that are not immediately apparent.

Throughout my career, I have built many managed and cloud services, and I also have reviewed many partners’ business models - I wanted to share with you the top 5 mistakes I have come across.

1. Customer On-Boarding Rate

An easy mistake to make - I have 100 customers billed at $100 dollars a month - what is my revenue for year 1 ? 100 x $100 x 12 = 120,000 right ? Wrong - consideration has to be made using the rate at which these customers come on board. If they come on at a linear rate over the course of the year (i.e. you exit the year with 100 customers), then to approximate the revenue you divide the above by 2 - so the revenue would be $60,000. More complex "curves" can be used to model the customer on-boarding rate.

An associated area, the so called "Rule of 78" (a term borrowed from the finance industry) also has to be considered. If you miss your new customer target in Month 1 by 5 - you have to get more than 5 additional new customers (on top of the existing target) in Month 2.

2. Churn

In some commoditized managed and cloud services markets which have relatively low switching costs for the end customer, consideration has to be given to the "Churn Rate", meaning how many customers will NOT renew after their initial contract rate. This can be low, single digit percentages - but can reach up to 15% in more cut throat markets.

3. Hockey Sticks

The classic hockey stick revenue curve. I launch my service day 1, and it just keeps getting exponentially better and better from there on out. Product Managers have to consider the lag between launch and First Customer Acquisition, they need to think about sales cycles, they need to think about provisioning timelines, bedding in and turn up periods. It’s not unusual to see no revenue coming into the business for 6+ months after the launch. This is the reality of the managed and cloud services business - particularity in cases where the organization is entering into new markets. Often, many aspects of the company have to be re-tooled: sales, marketing, customer relationship and finance. It doesn't matter how great the service offering is - if these pieces are not in place, then revenue goals will not be achieved.

4. Step Function Costs

Managed and Cloud Services have high barriers to entry - much higher than the costs for a VAR or even a Professional Services Systems Integrator. OSS Costs, BSS Costs, NMS Costs 1. Don't even get me started on OSS / BSS / NMS costs.

5. NOC Staff Costs

On the subject of Step Function Costs. Usually, the largest part of a 5 year cost profile is the NOC Staff Costs and Customer Engineer Costs - even for organizations that are already in the business of managed and cloud services they can be prohibitive. For example - if you want to have 2 people in your NOC 24 x 7, then you need to hire 12. That is just the way the math works when you think about training, vacation, work weeks, failover capacity, etc. 12 people at, let’s say $120K loaded annual salary – that’s $1.4M .... day 1 ... as you go live with customer 1. This is the area that I usually see the grossest underestimation - so working with your service delivery teams and organizations to make accurate estimates of this is key. However,this is not a blank check for your NOC manager - always be challenging the assumptions. What existing skills sets can be leveraged? What tools can be used to drive closure of tickets to your level 1 NOC teams? What technologies can be put in place (such as event correlation technologies) that reduce the noise that comes up to the NOC teams? What knowledge bases can be put in place to drive repeatable codified ticket closure ... all these aspects should be considered when modeling this key cost center.

I have collected a number of tools over the years that can be used for this complex task - if you are interested in getting your hands on some then drop me a note