Unravelling regional insight
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- Maurice Osborne
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1 Unravelling regional insight By Steve Riley, TIA Insight Specialist (May 2017) Introduction While national-level insight provides a clear picture of how the tourism industry performs in New Zealand, a regional insight view is also important to better understand performance at a micro-level. This can help identify the Tourism 2025 economic aspirations of a region and what capacity and investment decisions need to be made based on current regional trends. Regional insight can be defined as insight that tells the tourism story at a more local level. For example, it could be to understand how your regional spend compares with other regions, or to determine the regional make-up of the tourism industry, e.g. the mix of accommodation, transport and other tourism spend. Regional tourism insight can generally be defined at the Regional Tourism Organisation, Regional Council and Territorial Authority level. There are also ways this data can be provided at an electorate boundary level. A high level view of the regional insight available to tourism operators follows. We acknowledge that the list is not exhaustive and that there are a number of other regional data sources that are not attributed in this report. Regional expenditure data The Monthly Regional Tourism Estimates are calculated by the Ministry of Business, Innovation & Employment from electronic and credit card transactions. The results are released within a month after the reference period, for example March results are released by the end of April. The MRTEs measure the level of spending by international and domestic visitors in regions across New Zealand. Regional expenditure data can be viewed in various ways depending on the research question. For example, an accommodation provider in Wellington might want to understand how much visitors in their region spend on accommodation and how this compares to surrounding regions. Figure 1 illustrates that Wellington recorded $238 million in visitor spend on accommodation in the year ending March 2017, Nelson Tasman $74 million, Marlborough $44 million, Wairarapa $15 million, and Kapiti- Horowhenua $8 million.
2 Total spend ($) Figure 1 Spend comparative Accommodation Wellington and surrounding regions $300m $250m $200m $150m $100m $50m $0m $8m $44m $74m $15m $238m Region 2017 Source: MRTEs, MBIE Figure 2 shows Auckland (25%), Canterbury (13%), Waikato (11%) and Wellington (11%) dominate the share of domestic visitor spend, with these four regions making up 60% of total domestic spend. 2
3 Figure 2 Share of Domestic spend by region, YE March 2017 Auckland Bay of Plenty Canterbury Gisborne Hawke's Bay Manawatu-Whanganui Marlborough Nelson Northland Otago Southland Taranaki Tasman Waikato Wellington West Coast Source: MRTEs, MBIE 3
4 Auckland (36%), Otago (18%) and Canterbury (12%) dominate international spend, with 66% of spend attributed to these regions (figure 3). Figure 3 Share of International spend by region, YE March 2017 Auckland Bay of Plenty Canterbury Gisborne Hawke's Bay Manawatu- Whanganui Marlborough Nelson Northland Otago Southland Taranaki Tasman Waikato Wellington West Coast Source: MRTEs, MBIE 4
5 Other sources of regional insight The Commercial Accommodation Monitor measures regional trends of commercial accommodation across New Zealand regions. This includes measures of international and domestic visitor guest nights and accommodation capacity levels. Figure 4 illustrates the distribution of guest nights by region and compares the year ending February 2017 with the 2016 year. Over this period double digit growth in guest nights was achieved by a number of smaller regions: Mackenzie (+18%), Fiordland (+15%), Gisborne (+14%), Whakatane-Kawerau (+12%), Hawke s Bay (+11%) and the Wairarapa (+10%). Figure 4 Guest Nights by Region YE February 2017 Region Whakatane-Kawerau West Coast Wellington Whanganui Wanaka Waitaki Wairarapa Waikato Timaru Taupo Taranaki Southland Ruapehu Rotorua Queenstown Northland Nelson-Tasman Marlborough Manawatu Mackenzie Kapiti-Horowhenua Hurunui Hawke's Bay Gisborne Fiordland Dunedin Coromandel Clutha Central Otago Canterbury Bay of Plenty Auckland YE Feb 2017 YE Feb Number of Guest Nights Source: Commercial Accommodation Monitor, MBIE 5
6 Regional data from Infometrics, provided through ServiceIQ (figure 5), identifies the number of tourism business units across the 16 regions. The largest number of business units are recorded in the Auckland region (10,861, or 35% of tourism business units nationally). The Gisborne region has the smallest number of business units (248 or 0.8% of tourism businesses in New Zealand). Source: Infometrics and Service IQ data 6
7 Domestic Growth Insight Tool (DGiT) The DGiT tool was released by TIA and a Domestic Tourism Working Group in November This interactive online tool is designed to help tourism businesses and RTOs identify their target domestic audiences and the best way to market to them. The following example identifies what characteristics of the domestic visitor market a hostel/backpacker business based in Northland could expect. In this example we consider the market that may not be interested in going to Northland and those that find it difficult to get there. This can be adapted to just show those that are interested in visiting Northland. In figure 6 there are a total of 181,167 trips that a business of this type could tap into. Figure 6 Northland Market Profile for a hostel/ backpacker business 7
8 In figure 7 DGiT shows that around half the potential domestic market would come from Auckland. This can be further broken down into markets from different areas of Auckland. Figure 7 Northland Market Profile for a hostel/ backpacker business origin of visitors 8
9 Figure 8 identifies the activities and accommodation that interests them. The majority are looking for a beach holiday. Figure 8 Northland Market Profile for a hostel/ backpacker business who s interested 9
10 Figure 9 Northland Market Profile for a hostel/ backpacker business who s interested Figure 9 above shows the key messages, triggers and barriers to a domestic trip for this market. It also shows the media, planning channels and at what stage activities are decided on. To activate DGiT, click here. 10
11 Table 1 illustrates the spread of tourism employment across the regions. Employment in tourism grew fastest in the Otago region in 2016 (+3.4%). Other regions in the South Island showed decreases in tourism employment over this period. Table 1: Regional Employment Tourism Total economy % growth pa Share of Total 2016 Share of Total 2016 Northland Region 7,200 7, % 3.80% 2.90% Auckland 53,618 60, % 32% 35% Waikato Region 15,985 17, % 9.30% 8.70% Bay of Plenty Region 11,849 12, % 6.60% 6.00% Gisborne Region % 0.40% 0.90% Hawke's Bay Region 4,681 4, % 2.30% 3.30% Taranaki Region 2,794 2, % 1.40% 2.40% Manawatu-Wanganui Region 6,375 6, % 3.30% 4.70% Wellington Region 21,445 20, % 11% 12% Tasman Region 2,061 2, % 1.10% 0.90% Nelson Region 2,508 2, % 1.20% 1.30% Marlborough Region 2,798 2, % 1.30% 1.10% West Coast Region 2,887 2, % 1.40% 0.70% Canterbury Region 25,984 23, % 13% 14% Otago Region 16,504 19, % 10% 5.00% Southland Region 4,085 3, % 2.10% 2.20% Source: Infometrics and Service IQ data How regions are using regional insight to inform long term aspirations While the Tourism 2025 $41 billion aspirational goal is relevant for the regions, it is also important they drive their own regional framework that resonates with local operators and broader industry stakeholders. This was recently achieved by the Dunedin Host Growth Framework with their clear articulation of their aspirational goals at a regional level. A number of other regions have adopted a similar approach, such as Destination Coromandel s Beyond Insight Gaps It is acknowledged that there are a number of identifiable gaps in the current data available at a regional level. This includes a set of regional forecasts, domestic and international volumes and visitor nights by region. This is currently being considered as part of TIA s Insight Framework and government plans for tourism insight. 11
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