Note: Names and logos have been changed for privacy reasons
Tidy is the workforce management app that prides itself on solving complex problems in the most simple way possible. There have been many apps before Tidy that focus on workforce management, but none are targeted towards the commercial cleaning industry. This was the beginning of Tidy’s point of difference.
Problem 1
A large segment of the commercial cleaning workforce are casual or contract workers. Alongside this dynamic, a large portion of when the cleaning is required is quite flexible. Most scheduling software only cater for fixed shifts, which has a fixed start date/time and end date/time. Through a series of user interviews, we gathered the most common use cases, built the feature, tested and released to our customers.
Most common use cases:
- High rise office clean 3 times a week between 6pm and 11pm for 3 hrs
- Manufacturing plant clean over the weekend for 4 hrs
- Retail weekday clean for 4 hrs with a 1 hr buffer on the start time and end time
Problem 2
Finding availability for shifts was a highly time consumming problem for managers. Most delt with it using the “Where’s Wally” approach of searching for gaps in workers calendars. There was an ongoing debate wheither search or suggestion was a better solution to the problems. Through user interviews, it became apparent that both methods were wanted by our customers.
For the suggestion, we used the following criteria to create a basic recommendation algorithm.
- Shift clashes - If the cleaner has an existing shift clash
- Availability - If the cleaners are available to work
- Best Location - Which cleaners have the shortest driving distances from home or the shift
- Best Suitability - Prioritise cleaners who have worked at the site before
While the suggestion gathered a whopping 50% of shift engagement, it was still missing some human elements of the decision making process which the remaining 50% used in the searching approach.
- Workers collaboration - Which workers work best with together
- Affordability - Full time, part-time, casual and contract workers all have different hourly rates
- Certifications - Sites requiring certifications like schools with working with children checks
Problem 3
When Tidy first developed the shifts, it was developed to be an MVP approach that caterred for 85% of shifts that are published with only a single worker. As we continued to interview our customers, it become clear that the remaining 15% of shifts were causing some problems, and it was now time to prioritise a solution in the roadmap.
- Workers like to know if there is another worker performing work on the same site for safety and awareness
- Workers share equiptment and like to coordinate transport
- Workers can carpool to sites to save on transport costs
Problem 4
The ideal customer profile were owners who, as the ol adage would state, want to work on the business, not in the business. To paint a picture, this meant that owners would be meeting prospective clients all day tendering for new business, while their workforce of over 200 staff was providing day to day services. To give owners confidence that they could do this while maintaining qaulity services, we needed to give them peace of mind that they had full visibility over their daily operations. Through user interviews, we identified these main areas of concern:
- What needs my attention?
- What shifts are scheduled for today?
- Did all the shifts get attended today?
- How have inspections performed in the last 30 days?
While these daily operations analytics were important, there was also another need of having visibility on long term client retention. Through user interviews, we identified these main areas of concern:
- Highest performing clients
- Lowest performing clients
- How are inspections performing?
Success metrics
The North Star metric for Tidy was Number of sites cleaned per month. This was a practical metric to use as it showed growth from both sides of the product. While important, we also used metrics like new vs churned customers to make sure our retention rates were high. With the addition of three major features, of which being Flexible shifts, finding availability and multiple workers per shift, Tidy went from from 159 sites cleaned per month to 5,226. This was an increase of over 3000% over 5 months.
