Situation:
Imagine you own an ATM and cash register maintenance services business, with same service level agreement structure for the last 20 years:
1) % of end points with response time below [2-4] hours
2) % of end points with resolve time below [8-24] hours

Let us now put ourselves in bank’s/retailer’s shoes, where we know:
1) Location matters: <20% of ATMs/ stores drive 80%+ of their revenue
2) Peak times critical - flexibility when low volume (e.g. middle of night)
3) High volume end points need to be prioritized AND break down more

How could you differentiate yourself vs. competition, better aligning your offering to customer business drivers and pain points?

Initiatives:
Customer pain to be solved is the revenue loss when end point is “out of service”, of course also the end consumer experience & impact on loyalty.

This is a client from Gregory’s time as a transformation consultant, and here are some of the solutions we put in place:

1) Through customer discovery we identified top customers and leads with the highest pain, interested in switching away from plain vanilla service to differentiated service levels by location, time etc.
-> Large, growing customers (attractive segment!) liked value proposition

2) We estimated value of this differentiated offering looking at the revenue by end point (and estimated losses when down) to help define price points.
-> Answer: high value for customers, directly impacting top & bottom line.

3) Then we reviewed customer end point data (e.g. transaction volume by location and time, repair history with root cause analysis) to estimate what the incremental cost would be and how operations would have to evolve.
-> Answer: introduce preventative maintenance at predictable times (e.g. maintenance at night) and selective white glove service in top tier cities.

We then went on to transform operations (see other case studies), and after 18 months this services unit went from being flat to double digit growth in revenue, with increased margins and better SLAs.

Situation:
Imagine you are responsible for staffing and dispatching a team of technicians to service ATMs and cash registers, and your performance is based on reaching service level agreements for the customers (i.e. how quickly can you repair an ATM that is out of service) and team cost/margin.

You just won a big contract and/or opened up a new servicing channel. How would you decide how many technicians to staff and how to build work schedules for them?

Why important?
By aligning work schedules to the actual demand pattern, margin at ATM services company increased 15% (in some geos up to 40%). For example by servicing more customers without adding more techs.
You can scale business up/down confidently (bye bye long customer wait times), provide flexible work hours and better manage team performance.

Initiatives:
1) Build a reliable demand forecast
Start with historical data and add in expected new demand based on # of customers, end points (ATMs) per customer and expected service calls per end point. Refine range using ongoing actual data as feedback loop.

2) Compute required tech hours and FTEs to meet demand each month
Illustrative example: 3000 service calls per month, 2 hours per service call with travel, requires 6000 tech hours. If a tech works ~150 hours per month (consider holidays, vacation, pto, sick days), you need 40 FTEs.
How does your FTE need evolve month over month? Do you need temporary workers to manage busy season? Can techs take more pto during low season?

3) Optimize weekly work schedule from tactical demand pattern
Every services company has their own predictable spikes, e.g. Monday mornings. Staff techs accordingly: consider changing start of day time or introduce 4 day workweeks with longer working hours!
This allows you to serve more customers and ensure your pto, part time and overtime policies match business needs .

4) Optimize dispatching and routing - reduce drive time per day per tech
Get intimate with traffic patterns and typical drive times in your geo, and match insights to your tech routes. Many technicians spend more time on the road than repairing stuff, so it is worth the investment. Save up to 2 hours drive time per day in big cities (= 1-2 extra service calls per tech)!

Situation: When we started working with the ATM services company, most managers were “on call” 24/7 dispatching and coaching technicians in the region.
They had no time to work on improving their processes (e.g. set-up start of day calls with the whole team) as they were always in firefighting mode! Technicians also did not know how well they were performing as no data was shared back with them on an ongoing basis, and incentives were “gameable” undermining the system.

So how did we equip managers to be better frontline leaders? And how did we motivate techs to be at their best each day?

Initiatives:
1) Transparency on metrics that matter, creating positive peer pressure
Each tech received a weekly 5 star rating based on productivity/utilization, quality, parts usage and customer satisfaction.
Tech rating was compared vs. average and provided tips on where/how to improve, creating positive peer pressure. A more holistic dashboard was available for managers with broader metrics, including their regional P&L.

2) A supportive performance culture. A strong vision and purpose was defined, and recognition was embedded across day-to-day processes.
Below average techs got dedicated coaching and best in class techs shared best practices with peers in guru sessions.
Incentives were based on both team and individual components, gaming the system was not tolerated (and ways to game it were eliminated).

3) Extensive frontline leadership curriculum for managers
Building high performing teams of course depends on the quality and training of your managers. Initially, performance variability was high.
We focused on teaching 8 core skills (e.g. how to manage P&L, how to recruit right techs, how to give feedback).
Key principle: the best managers teach the rest. Each manager built their own action plans with monthly follow-ups to track progress.

4) Once culture is in place, tactical field performance initiatives can be deployed to help techs improve their ratings, behaviors and skills (e.g. how to ensure no revisits/retrips needed, how to improve your repair times, how to manage parts)

Impact:
We helped this services organization mature towards a continuous improvement culture. Productivity increased 15%+, morale was at an all time high 18 months after start of journey.

Situation:
You are in a competitive bid to win a ATM servicing contract in Dallas Fort Worth.

How can you increase chances of winning bid, without giving up margin?

Initiatives:
1) Simulate how your cost per call will evolve if revenue changes
If you have superior operations with the possibility to breakdown cost per service call, including average repair and drive time per technician, you can estimate how the cost per call will evolve if your technicians can operate in higher ATM density areas and reduce their drive time.
If you can increase amount of service calls from 4 to 5 a day, your margin per tech goes up by 25% all else equal!

2) Compare your potential cost and margin with the competition, gathering some competitive intel, to decide what a good bid might be for the contract (and if you should give up some margin uplift or not).
Once you reach a certain scale, better unit economics will give you a sustainable competitive advantage to grow in this area.