MBA8530 – Final Exam – S. Skoog
Sof-Optics – Background (External Factors)
Sof-Optics is a small (specialty-niche) player in a $155M contact-lens market. (Three competitors occupy 75% of this market (Bausch + Lomb (51%), American Optical (14%), Continuous Curve (10%); approximately twenty players (including Sof-Optics’ ~3%) occupy the remaining 25%.) This consumer space is already appreciable in size (~5M contact-lens wearers in 1980), and promises exponential growth in future years (only 10% of ~50M prospective lens-wearers in America have even tried soft contact lenses).
Contact-lens magnates recognize a dual-segmented product space – private practice (i.e., doctor/ophthalmologist supply) versus retail (i.e., health + beauty, pharmacy). Lost/broken lens replacement (constituting ~30% of sales) and lens supply products (roughly $50 per wearer per year) comprise strong subsidiary markets. In stark contrast to larger players’ generalist/mass-market offerings, Sof-Optics strives to differentiate itself as a higher-quality (often custom-fabricated) product supplier. This approach has borne some fruit; Sof-Optics lenses are widely perceived as having quality and standards superior to their Bausch + Lomb counterparts, granting Sof-Optics preferential reception in the specialty (doctor/ophthalmologist) lens segment.
Sof-Optics – Background (Internal Factors)
Sof-Optics, headquartered in San Francisco, was founded by ophthalmologist Carl Wagner and physicist Dr. Johan Schmidt in 1977. The corporation employs 248 staffers (including twelve customer-service agents and twenty geographically-distributed sales representatives), maintains a 50,000 sq-ft manufacturing facility (also in California), and produces ~2000 lenses (one-third of max theoretical capacity, using an advanced plastic-rod grinding/machining process) per day.
Sof-Optics fulfills two types of contact lens orders – “standard” (off-the-shelf preformed lenses, in forty variants, fitting ~75% of the human lens-wearer population) and “custom” (lenses with unique parameters). Standard lenses are shipped the next day after order, and kept in bulk (warehouse) inventory to be replenished whenever stock falls beneath a predetermined quantity. Custom lenses require 3-to-4-week manual fabrication before shipment.
Sof-Optics sold 36,214 lenses (yielding $1.3M revenues) in fiscal 1977-1978, and 211,422 lenses (yielding $5.8M revenues) in fiscal 1979-1980. Sof-Optics has not yet turned a profit in its three-year lifespan; after two rounds of financing ($10M and $3M, respectively), venture capitalists are losing patience. Customer service and dissatisfaction (see below) may be causing lost sales...
Sof-Optics – Problem Statement
The Sof-Optics telephone/order process(including but not limited to queuing, staffing, priority and capacity utilization) is a significant cause for concern. Many customers, faced with unacceptably-long wait times during mid-day peak volume, terminate (hang up or “abandon”) their orders; worse still, an as-yet indeterminate number of customers, experiencing busy (all-lines-occupied) signals, disconnect before even entering the wait-queue (“immeasurable abandon”).
Nancy Langstaff (Director of Sof-Optics Marketing) fears these excessive-wait/abandon numbers are direct contributors to lost sales (particularly lucrative doctor’s-office sales from the specialty-lens segment) and resultant diminished revenues/profits (to Bausch + Lomb or similar).
MBA8530 – Final Exam – S. Skoog
Sof-Optics – Data Supporting Problem Statement
Exhibit 8 shows 81-sec avg customer wait time (approaching 127 sec during 10:00-to-2:00 peak).
It can be reasonably assumed that excessive wait time is causing customer
dissatisfaction, as Sof-Optics is experiencing premature order termination.
What does this wait-time mean for Customer-Svc Reps during peak hours?
Incoming calls range from 47 to 75 calls per half-hour in the 10-to-2 window;
if each incoming call requires 130.65 sec to process on average (calculations
shownon next page), plus 82-to-127 seconds’ delay per call, this means
47 to 75 calls at peak => 6140 to 9798 sec during peak
=> + 3872 to 9540 sec delay at peak
=>10012 to 19338 sec, inc. delays at peak
=>166 to 322 minutes at peak
Which is to say, certain very-egregious peak conditions may emerge beyond
8 staffers’ ability to cover (8 staff x 30 min = 240 staff-minutes, 240 staff-
minutes cannot cover 322 min of calls + delays even in perfect conditions).
Exhibit 8 shows 136/1164 = 11.7% avg customer abandons (approaching 34.1% during peak).
There is a second (difficult-to-measure) cause of customer abandonment
(i.e., customers who reach busy (all-12-lines-occupied) signal w/o a wait).
Though not explicitly given in the case, extrapolating a rough parabolic
trend-line from Exhibit 8 data (see attached spreadsheet + curve diagram)…
…suggests as many as 156/1321 = 11.8% additional busy-signal customer
abandonments(in the 10:00-to-13:30 timeframe) may be happening
before the customer even reaches apre-recorded hold/wait message.
Clearly lost sales amounting to 11.7% to 23.5% ($680K to $1.37M, as a
portion of Exhibit 1 FY80 revenues) are unacceptable! Even the low end
of this range (~$680K) would have turned FY80 loss into $300K profit.
MBA8530 – Final Exam – S. Skoog
Sof-Optics – Data Supporting Problem Statement (cont.)
What should Sof-Optics’ daily call volume look like? Statistics detailing call-categories (Exhibit 3) can be used to compile average-call-length, average-service-time, and thus max-daily-capacity.
An Average Customer Call (handled by Customer-Service Rep):
(60% are 85 sec) + (15% are 120 sec) + (15% are 220 sec)
+ (5% are 450 sec) + (3% are 125 sec) + (2% are 120 sec)= 130.65 sec
An Average Customer Call (handled by Data-Entry Operator):
(60% are 30 s) + (15% are 40 s) + (5% are 240 s) + (3% are 50 s)= 37.5 sec
Assuming perfection (no busy-signals, no customer-abandons), a Customer-Svc Rep can handle (8 hrs) ÷ (130.65 sec) = 220.4 calls/day, or 206.6 calls/day with a 30-min break. A Data-Entry Operator can handle (8 hrs) ÷ (37.5 sec) = 768 calls/day, or 720 calls/day with a 30-min break.
8 Cust-Svc Reps=> 1652 to 1763 calls/day (theoretical max capacity)
actual (Exhibit 5) performance is 159 to 166 calls/day,
which (over 8 staffers) should be 1272 to 1328 calls/day.
Cust-Svc Reps are operating at 75.3% to 77% capacity
even *with* the built-in stretches of idle time estimated
in Exhibit 5… handling the 11% to 23% abandon volumes
calculated on the previous page should be no problem
with existing staff, if said abandons could be prevented.
4 Data-Entry Opers=> 2880 to 3072 calls/day (theoretical max capacity)
Data-Entry Operators are nowhere near capacity. Even
making the unrealistic assumption that all 1272 to 1328
calls/day require data-entry, Data-Entry Ops are operating
at 43.2% to 44.2% capacity. (Exhibit 3 suggests that only
83% of calls require data-entry, so this number is actually
more like 35.9% to 36.7% of capacity.)
This means that Data-Entry Operations are approximately
double-staffed, and could theoretically complete their
current daily workload with only two data-entrants.
It is important to note that, although these figures are calculated using daily/hourly averages, incoming call traffic is *not* evenly distributed; that is to say, calls are “clumped” (highest incoming-call volume hovers at 64-to-71 calls between 09:30 and 14:30), as are delayed-calls (highest number-of-delayed-calls hovers at 60-to-68 between 10:00 and 14:00) and delay-per-call (highest delay ranges 82-to-127 seconds between 10:00 and 13:30). Though Jane Scott has attempted to compensate for these “clumps” via staggered shifts (manpower most concentrated during these peak hours), these persistent logjams show her efforts to be incomplete (max-clumped calls outpace available staff time at peak, see prev. page); more attention is needed.
MBA8530 – Final Exam – S. Skoog
Sof-Optics – Root Cause Analysis
A simple but representative Ishikawa (“fishbone”) root-cause diagram might look like this:
man method
/ /
customer svc / / customer svc
reps differ / insufficient / reps not well
in speed, / # of reps / trained, not
training / manning the / coming up to
/ busy clumps, / speed fast enough,
/ esp. at peak / not getting calls
customer calls / windows / off line fast enough
are being lost / /
due to delays ----+------+------
and/or busy- \ \
signal logjams \ \
\ 12-lines max \ order-status
computer \ causes some \ lookups on
system \ customers \ two CRTs
downtime \ to not even \ makes for
causes data \ reach the \ delays,
entry backlog \ wait-msg \ logjams
\ \
machine materials
Sof-Optics – Possible Approaches and/or Solutions
Excess capacity should be diverted from the Data-Entry Operations team immediately; Customer-Service Representatives are being badly swamped at peak hours, whereas Data-Entry Operators have “cushy lives” rarely if ever burdened by backlogs or overload. If 1½ Data-Entry staffers were re-tasked to work Customer Service phones (two phones are currently idle/unused), Cust-Svc max throughput would become 1962-to-2093 calls/day (current 1272-to-1328 volume would constitute 63.4% to 64.8% of capacity), while Data-Entry max throughput would reduce to a still-manageable 1800-to-1920 calls/day (current 1081-to-1128 volume would constitute 58.8% to 60.1% of capacity). For optimum utilization, the 1½ Data-Entry staffers so re-tasked should work during busiest/peak Customer-Service hours (e.g., two staffers both working the 6-hour stretch from 08:00 to 14:00). This staffing model could sustain 50% volume growth into 1981.
Alternately, supervisory staff (Ms. Scott herself) could work a customer phone line during the aforementioned 10:00-to-14:00 peak period. This action will boost capacity as above, but to a lesser extent; it has the collateral benefit of being minimally disruptive to existing staff plans.
Neither of these solutions addresses the 12-lines-maximum issue. The customer-reaches-busy-signal phenomenon *must* be prevented at all costs; worse even than long-wait frustration, the busy signal is literally flushing money down the drain. Two additional phone-lines are scheduled for December installation – although expensive ($1700/month per extra phone-line), if they prevent even one out of every ten customer abandonments, they will more than pay for themselves (11.7% current abandonment ≈ $680K loss per year, if reduced by one-tenth this becomes 10.5% abandon ≈ $612K loss, a $68K/yr savings for $40.8K/yr of phone-line costs). This logic could be applied to adding four phone-lines, or six, or eight, or ten or twelve…
MBA8530 – Final Exam – S. Skoog
Sof-Optics – Possible Approaches and/or Solutions (cont.)
General (less easily quantified) human-resource issues seem to be plaguing Sof-Optics’ customer service department. Customer-Service staffers should explore new training options (it is taking too long for new hires to “ramp up” to 159-to-166 daily call volume) and/or implement bonus compensatory systems (e.g., award P paid for meeting or exceeding daily volume Q, award X paid for minimizing customer delay beneath target Y, etc.) These countermeasures may incidentally serve to mitigate Customer-Service’s excessive turnover (much greater than other sub-10% neighboring organizations).
Additional Customer-Service hires are always an option (particularly if high volume growth persists through 1981 and out-years), but should *not* be considered without first procuring additional phone lines (to avoid 12-max busy) and/or re-tasking Data-Entry staffers (making use of excess capacity). Ten Customer-Service staffers can be supported before new workstation purchases become necessary.
Sof-Optics – Action Plan, Implementation, Next Steps
- As an interim step, Customer-Service Dept. needs to re-stagger/re-task staff immediately
[shift 1+ additional staffer(s) to 09:30-to-14:00 peak, or re-task Data Entry staffer(s)]
- Longer-term, Customer-Service Dept. must show peak/delay numbers to highers-up
[present numeric justification for additional phones, workstations, staffers if needed]
- Add 2+ additional WATS phone-lines or retool 12-max-lines system as soon as possible
[get rid of the busy-signal problem, or at least find some way of quantifying/tracking it]
- Consider renovating Customer-Service training curriculum, new hire ramp-up process
[goal is to get cust-svc staffers up to speed faster, keep them on the job longer]
- Consider restructuring Customer-Service compensation, time/volume-based bonus plan
[define an “acceptable” customer wait time, say 30 sec., and manage to those targets]
- Re-evaluate Jane Scott’s supervisory skills, consider bringing in additional assistance
[possibly re-classify Ms. Scott as “shift supervisor,” making her a ninth cust-svc staffer]
- Introduce “thank you for holding, average wait time is now XYZ sec” recorded message
[cable-supplier ComCast now uses such a recorded-message system, to marginal benefit]
[even if it does not appease the frustrated customer, it may at least free up a phone line]
[in Sof-Optics’ current system, the 2nd best thing a waiting customer can do is hang up]
- Introduce non-phone-dependent technology… e.g., secure Internet/Web-based ordering
[may also reduce need for data-entry staff, but watch out for HIPAA + similar legalities]
** Sven’s Supplemental Note: Two lesser/subsidiary problems can be found in this case (inventory-mgmt
and the consignment stocking system). I chose to focus on call-queues given the five-page maximum.