DHL Consulting Case: Local Commerce

a) The candidate should acknowledge that she/he has to solve a prioritization task and a set of characteristics/factors/KPIs is required to create a shortlist of cities​.

b) The candidate should define a meaningful structure for these factors and name multiple categories, e.g.​:

1. Demand (Consumers)
2. Supply (Retailers)
3. Capabilities (DHL)
4. Infrastructure (City size, layout, streets, etc.)
5. Ease of doing business (Politics, laws)​

c) The candidate should be able to name multiple meaningful factors for the chosen structure, examples could be:​

1. Demand (Consumers): # of inhabitants per city; purchasing power in the city; sociological factors (average age, # of students, unemployment rate), “pull factor” (are people going into the city to go shopping or are they driving somewhere else?), etc.
2. Supply (Retailers): # of retailers in the city; diversity of retailers (chains vs. unique stores); ecommerce “readiness” of retailers; existing local/online solutions; level of competition, etc.
3. Capabilities (DHL): DHL infrastructure (number, location & capacity of sorting centers) and capabilities (available teams, skills, vehicles etc.)
4. Infrastructure (Logistics): Size (km2) of the city (relevant for driving distance); quality of public road infrastructure, traffic jams, bike lanes etc.; potentially: labor pool for additional employees
5. Ease of doing business (politics): Existence of subsidies/funds for new businesses; degree of political support; existence of organized interest groups (e.g., local “Einzelhandelsverband” in Bonn); vehicle bans for certain areas in the city (pedestrian areas)

a) Revenue stream: One-off cost for each new retailer on the platform:

• Candidate should assume if all/ how many of the 100 retailers in scope join the platform​
• When candidate asks if we know the percentage: DHLC conducted a survey with the retailers 30 % want to join​
• 30% participating retailers x 100 retailers in scope x EUR 100 = EUR 3,000 one-off​

b) Revenue stream: 5 % of the revenue

• 30 participating retailers (see above) * EUR 150,000 * (10 %  transform + 2 % upsell) = EUR 540,000 total revenue​
• EUR 540,000 total revenue * 5 % (DPDHL fee) = EUR 27,000 p.a. ​

c) Revenue stream: Revenue per parcel

• Candidate should either ask for additional information on how to calculate the revenue stream OR come up themselves with a feasible solution path ​
• Potential solution: Estimate number of parcels by average value per parcel (eCommerce average: EUR 50 per parcel)​
• EUR 540,000 total revenue  / 50 EUR/parcel  * 5 EUR/parcel = EUR 54,000 p.a.​

a) How do you evaluate the calculated expected revenue?

Candidate should understand that the revenue of 84k EUR p.a. is very low (even without business context or background knowledge; 1) by understanding that this is revenue, and all costs need to be subtracted; 2) understanding roughly the cost of labor in Europe)​

b) How would you increase the revenue?

Candidate should identify three options:​

1. Increase prices (either marketplace fee and/or price per parcel)
2. Increase # of retailers (only 30/100 targeted and 30/2000 overall retailers participate, e.g. via targeted marketing/communications campaign)
3. Increase # of consumers shopping online / increase online share of retailers to more than the current 10 %

c) What are possible options, and which one would you recommend?

Candidate should evaluate the options and recommend one with solid reasoning:​

1. Increase prices: Unclear if there would be any positive impact due to retailers/consumers leaving platform in face of higher prices; do not recommend
2. Increase # of retailers: Rather easy to implement, makes platform more attractive for consumers; no real downsides recommend
3. Increase # of consumers shopping online / increase online share of retailers: Rather easy to achieve via marketing measures, but might not be welcomed by retailers (fees for platform and parcels are likely cutting into retailers margin for online sales in comparison to offline sales) (no) recommendation depends on reasoning​