Archive for the ‘Service Revenue’ Category

New TSIA Benchmark Survey Lauched

Monday, July 26th, 2010

Last week, we launched the completely new and much anticipated Field Service and Support Services TSIA Benchmark Survey. This new benchmark survey is a significantly revised and updated version of the TSIA benchmark survey, which TSIA member companies have been using for the past 3 years.

I have been absent from these blog posts for the past several weeks because I have been feverishly working – along with others in TSIA – on finalizing this new benchmark survey and benchmark tool. I’m proud to say we’ve finished our initial efforts, and the new benchmark survey and survey tool is now available to our member community.

The benchmark survey has undergone a radical transformation. We’ve developed completely new online software members can use to access the benchmark survey. The old benchmark survey questions have been revisited, revised, and updated, and we’ve added more than 100 new questions to the new survey.

The new online software includes many features aimed at easing the process of completing the survey, including:

  • The ability to logon, log off, and log back on again later and resume the survey where you left off.
  • Multiple user logins, which allows different people in an organization to complete those portions of the survey with which they are most familiar.
  • Built-in “skip logic” automatically “hides” those questions in the survey that are not relevant to the survey respondent based on answers he or she provided to earlier questions.
  • Detailed explanations and instructions tied to the questions eliminate different interpretations of the questions, thus ensuring consistency in the answers.
  • And much, much more.

The new TSIA benchmark survey covers all major aspects of customer support operations:

  • FINANCIALS, including:
    • Service & support revenue and growth, margins, cost center vs. profit center, service revenue allocations, SaaS/Cloud revenue allocations to service, etc.
  • SUPPORT CENTER OPERATIONS, including:
    • Quality programs, direct vs. outsourced employee data, call handling statistics, service incident response & resolution times, multiple support channel data (phone, email, web portal, chat, social media, etc), priorities & types of incidents, support rep labor rates, costs per service incident, customer/support rep ratios, much more.
  • FIELD SERVICE OPERATIONS, including:
    • Assignent & dispatch methods, response & resolution times, first visit fix rates, call back rates, SLA compliance, remote diagnostics & remote problem resolution data, training, muti-vendor services, field service labor rates, costs per field service incident, more.
  • SERVICE SPARE PARTS, including:
    • 1st pass fill rates, backorder rates, call backs due to lack of parts, spares inventory values as a % of revenue, inventory variances to book values, parts used per incident, parts $ per incident, DOA & NTF data, security measures, spares planning methods, outsourcing practices, end-of-life practices, more.
  • DEPOT REPAIR, including:
    • Customer repairs, “walk-up” or “drop-off” repairs, field technician repairs, RMA processes, advance exchange practices, “new” vs. “equivalent to new” exchanges, 3rd party repair vendors, turn-around-times, not-economical-to-repair (NER) thresholds, repair technician labor rates, etc.
  • ENTITLEMENTS, including:
    • Maintenance contract & warranty data, methods of pricing contracts, list vs. net pricing, contract pricing fees, T&M fees & per incident fees, initial contract attach rates, contract attach rates during/at end of warranty, contract sales compensation practices, warranty credit allocations, much, much more.
  • CUSTOMER SATISFACTION, including:
    • Customer survey methods, survey completion stats, customer satisfaction scores, satisfaction data by support channel (phone, email, web portal, chat, etc.), satisfaction by direct employee vs. outsourced employee, customer loyalty data, compensation based on customer satisfaction.

Of course, we also gather DEMOGRAPHIC data in the survey, such as industry and company size. So we can segment the data we gather accordingly for meaningful comparisons among our member companies.

We can honestly boast that no other survey anywhere gathers the breadth and depth of the data the TSIA benchmark survey gathers about service and support operations. If you are a TSIA member, we urge you to complete the new benchmark survey at your earliest possible convenience.

If you are NOT YET a TSIA member, I personally encourage you to check out this valuable association for service and support organizations here. You can also CONTACT ME and I’ll put you in touch with right people who will explain all the benefits and details.

Thanks for your interest – IT MATTERS!

MICHAEL ISRAEL

POLL RESULTS: “HOW DO YOU ALLOCATE SOFTWARE MAINTENANCE REVENUE BETWEEN SUPPORT AND ENGINEERING?”

Tuesday, April 27th, 2010

A few weeks ago this blog launched a brief poll in which we asked participants to identify how service revenues are allocated between their service and support organizations and their engineering organizations. I promised to publicize the results of the poll in this blog, here they are.

Unfortunately, only 17 companies provided information. Fewer data points than I had hoped to gather; enough to provide some information though. But the data doesn’t identify any clear trend, in fact it seems to point to somewhat of a dichotomy in the way companies allocate service and support revenues internally. As you will see from the below results, service revenue allocation practices are widely diverse.

       Revenue Allocation            Number of Poll Respondents
  • 100% to Service/Support                                         8, or 47%
  • 90% to Service/10% to Engineering                               zero
  • 80% to Service/20% to Engineering                               zero
  • 70% to Service/30% to Engineering                               zero
  • 60% to Service/40% to Engineering                               zero
  • 50% to Service/50% to Engineering                          1, or 5.9%
  • 40% to Service/60% to Engineering                          1, or 5.9%
  • 30% to Service/70% to Engineering                          1, or 5.9%
  • 20% to Service/80% to Engineering                          1, or 5.9%
  • 10% to Service/90% to Engineering                          4, or 23.5%
  • 100% to Engineering                                               1, or 5.9%

Truth be told I think the 4 responses for 90% of revenue going to engineering probably really belong in the 100% to engineering slot. That’s because I didn’t provide a “100% to engineering” answer option in the actual poll.  How naïve of me.  I didn’t really expect people to respond that engineering would get 100% of the service revenue. Yet one of the first emails I received in response to the poll was exactly that – 100% of the service and support revenue was actually allocated to the engineering organization, NOT to service and support, and this was from a very large software company. I realized then that I had made a mistake by not providing that option as a possible answer in the poll. My suspicion is that everyone who answered “90% to engineering” probably would have answered “100% to engineering” had that option been available to them in the poll.

To summarize the poll responses more broadly:

  • 47% allocate all of the service/support revenue to the service organization
  • 47% allocate all or the majority of the service/support revenue to the engineering organization
  • 6% split the revenue equally

As I said earlier, no definitive trend here, which is not surprising given the relatively small data sample. Even so, the data does highlight a stark contrast in philosophies about how service revenue should be allocated internally.

TSIA members will be interested in knowing that we’ve added this question to our updated benchmark survey. So we’ll gather this data on an ongoing basis going forward from more than 300 member companies. As a result, we’ll have a much more significant pool of data on this topic in the coming months.

Thanks for your interest – IT MATTERS!

MICHAEL ISRAEL