USING SMARTPHONES AND SMART SENSORS TO CONNECT

OXFAM’S DONATION INFRASTRUCTURE

1

Oxfam community network

Localised LogisticsMan-with-van

‘Cascading’

The challenge & relevance to IoC

• Lack of driver ‘visibility’ & understanding• Optimising activity & balancing workload• Scope for being more reactive to opportunities• Fostering greater collaboration between shops

- Can smartphones & sensors benefit decision making in a charity setting

App functionality

- ios for iPhone, iPad

- Server at Uni of Edinburgh

- Smartbin banks report

03:00 and 15:00

- Banks (B), Shops (S), Other

sites (O), Driver (D)

- All sites are active

- Click on sites to view menu

- Messages appear through

push notifications

Understanding driver activity

6

Viewing driver path into the future

8

Remote monitoring of banksfor more sustainable logistics

Fill

leve

l

Trials – Longitudinal app trials

- 21/3 to 28/6 Watford (mon-fri)- 3/5 – 20/9 Dorset (mon-fri)- 5/6 to 13/9 Cambridge (mon-wed)

- 4 drivers, 3 area managers, 10 shop managers, 1 depot manager.

Managing Time & Activity- 83% of managers believed that their planning and/or

decision making had improved from knowing where the driver currently was and would likely be

- All but 1 manager agreed that their understanding of how time was used in the business had improved

- The app could just pass on scheduling problems to other people unless the rules governing its use were not tightly controlled

“It was useful several times to know he was in the local vicinity so I could phone him and ask if he could do extra work but I’m not sure he was to chuffed”

- 25% of messages sent after 17:00 and 19% after 19:00- 67% of managers happy to message out-of-hours

(younger smartphone enabled managers more inclined).

“People communicated in the evenings. We are all quite pressurised by time [during the day]”

“Sometimes one has a ‘eureka’ moment when half asleep and you want to send a message straight away”.

- Few messages left on physical infrastructure during trials

Managing Time & Activity

Monitoring asset performance

0

50

100

150

200

250

300

Net

cur

rent

val

ue p

er v

isit

Re-appraising service needs

Site Currently visited Suggested visitsSnells Wood Every Tuesday Every 3rd TuesdayDatchet Every Friday Every 2nd FridayKingfisher Drive CarPark

40% of Thursdays 20% of Thursdays

Farnham Common Every Tuesday Every 2nd TuesdayAsda Tilehurst 60% of Thursdays 40% of Thursdays

Suggested reductions in bank visits on the Watford round

Scope for shops adopting banks and servicing using volunteers

Optimising bank collections

Area 11,000km2

56 bank sites, 68 shops

Monitored 40 banks at 21 sites

Live demo (9 May-19 July, 2013)

Devised 4-6 vehicle rounds each day

- visited banks when >50% full

- fixed collection days for shops

Results - distance savings

15

Total fleet savings = 1159km = 32 km /day = 3.2% reduction

Understanding activity patterns

0

100

200

300

400

500

Mon Tue Wed Thu Fri

Dwell time forothers activitiesBanks dwelltimeShops dwelltimeTravel time

Quantifying the apps impact

Before the app With the app %Shop dwell time (min)

18.67 15.59 -16.50%

Bank dwell time (min)

25.83 23.40 -9.41%

Before & after analysis – difficult to identify app benefits: (Oct-Nov V Mar-May when yields are significantly greater during the former)

Round orders did change once app implemented and Area Managers were influenced by the real-time information provided

Scope for greater collaboration

- 67% managers agreed they had collaborated more- Lack of engagement by some members over time- Targeting stock to specific outlets and shops sorting for each

other according to specialism could be a way forward- Pressure to meet shop targets can work against collaboration

- Greater live visibility of stock can put pressure on drivers

Conclusions – IoC & ITS in a charity setting

- Live visibility of vehicles & volunteers welcomed- No privacy issues, but drivers can become swamped with

requests & ‘back track’ on round- Competition for prime stock advertised by driver- Driver prediction function only used to estimate arrival times

by a few managers- Setting area/cluster targets and use the app on a more local

level to manage cascade (sorting for others)- Management structure not geared up for live reporting

- Ahead of its time!