Age-Care Live-In Facilities Market of Tallinn, Riga and Vilnius Areas

Age-Care Live-in facilities market of Tallinn, Riga and Vilnius areas.

Comprehensive analysis.

By Senior Group.

Paris- Riga- Tallinn- Vilnius.

2016

1. Objectives of research. The research was performed by the team managed by Senior Group experts as part of preparation of a detailed business plan for “Senior Baltic” project — to create the network of aged-care live-in campuses in three Baltic States: Estonia, Latvia, Lithuania.

2. Research Area The researched geographical areas — the metropolitan areas around the three Baltic capital cities — represent the most populated and well-off parts of Baltic states. We are going to create our 6 campuses there.

3. Results. In summary, our research shows that the unmet demand backed by purchasing power exceeds 10,000 beds and ALF units in the capital regions of the Baltic States. The total purchasing ability is estimated at 15,400 beds compared to 4649 available. This means that the market can easily absorb our planned expansion of 612 beds & ALF units. Research into pricing at existing residences shows that we should be able to charge 30–40 euros per bed per night.

3.1. Need (Demographical and Geographical Background)

At the end of 2013 there were 36,856 Long Term Care beds in the 3 Baltic States: Estonia, Latvia, Lithuania- BaS. (We use LTC data of1 OECD, which we assume includes the Assisted Living Units.) We estimate the additional need to be 18,038 beds between now and 2030. The estimate is based on the expected increase in the number of people over the age of 65 — by 133,856 through 2030 — and the expectation of reaching the current average OECD level of 44 LTC beds for 1000 persons over 65. This conservative estimate means that the demand will grow at the rate of 1,202 beds per year. (We do not take into account the changing family models of care for the elderly in Eastern Europe or increase of the income of households — the factors which significantly stimulate the penetration of the European Senior Care model into society). So from 2016 till 2019 we can estimate the growth of necessary quantity of Senior Beds in region as 4,810 beds approximately. We intend to develop additional 400 beds/units, or 8% of this conservative estimate.

The geographical strategy of development pursues the “footprint” approach. We plan to assure presence of the network in three capital areas of Baltics: Riga, Tallinn, Vilnius. Approximately 1,690,000 people, or 26% of all the population of Baltic states, live in the 20km radius areas around our residences. That gives us 307,383 people over 65 living within a 20 min driving distance from our Nursing Homes and Assisted living facilities of Senior Campuses. “ At the end of 2013 there were 36,856 Long Term Care beds in the three Baltic States- BaS (Estonia, Latvia,

Lithuania) . stats.oecd.org

”

3.2. Demand (a need backed by purchasing power) We’ve analysed 35 residences that have 4649 beds in total in the 20 km radius areas around Tallinn, Riga, Vilnius.

1 http://stats.oecd.org//Index.aspx?QueryId=30140 2

Here are the occupancy rates by type of residence2.

SUM of Q of empty SUM of Q-ty of Beds beds Occupancy Church 15 1 0.93 Municipal 2704 8 1.00 Private 977 102 0.90 State 953 54 0.94 So the average occupancy rate is greater than 90% for each type of residence.

3.3. The pricing of existing residences In order to compare residences we developed a single measure of the completeness of services and of the level of quality of residences. We call it the "A-score". It varies from -100 to +100 points.

We can see that the average price per day of existing residences varies from 16.50 to 53.00 euros per day.

2 https://docs.google.com/spreadsheets/d/1kiRnLh-SxkVhTJPO9RsKgWVJcvzRj86KyVfFNKjwBVM/ed it?usp=sharing 3

3.4. Target audience. We consider upper middle class families as our clients. The aged people belonging to these families use our services but they are not in a position to pay for - in Baltics as in France.

We should emphasize that we are talking about families, not about households. A family can have multiple households: the household of aged parent(s) and several households of adult children. All these households participate in financing of the stay of aged relative in Senior Care live-in facility.

Based on the research of existing residences we plan to set the price of our residences at the 900–1200 euros level (30–40 euros per day).

3.4.1. French comparision We have to compare our target regions (around the capitals of Baltic States) with Ile-de-France — the region what includes Paris in France. The total quantity of beds in live-in facilities in the region is 93730 beds & ALF units (62% of them nursing beds) for the population of 12 million (or 18 .2 percent of the population of France.)3 The average pension in France is around 13004 euros

The residential part of price of retirement facility is 3 294 euros in Paris 5 (2501 euros in Ile de France). This sum exceeds the pension almost 3 times.

We know that in Baltic states the pensions vary from 2506 euros per month (Lithuania), through 350 euros per month (Latvia)7 to 380 euros per month (Estonia)8, which is 2-3 times lower than prices charged by totally filled functioning commercial aged-care residences.

3 https://en.wikipedia.org/wiki/%C3%8Ele-de-France 4http://www.latribune.fr/economie/france/la-pension-moyenne-de-retraite-s-eleve-a-1-306-euros -bruts-mensuels-475756.html 5 “La France face à la pénurie de maisons de retraite”- OBSERVATOIRE 2014 CAP RETRAITE 6 http://greece.greekreporter.com/2015/06/26/eurostat-greek-pensions-average-e882/ 7 https://lnkd.in/eNq4B-7 8 https://lnkd.in/eXBtGNd 4

So the situation is the same as in France. The families of the upper middle class pay for the private live-in aged-care service, not residents themselves. So we have to compare the income of upper middle class of Baltic states with prices of the residences to be constructed.

3.4.2. Upper middle class We will consider as “middle class” the 60% of population — from 3rd to 9th deciles — according to the distribution of income.

Upper middle class will be the seventh, eighth and ninth deciles of population — or 30% of all the households.

We see that the distribution of income by quantiles in Baltic States is quite homogeneous and resembles the distribution of income in France.9

To get the total income of the upper middle class, we’ll summarise the values of the Seventh, Eighth and Ninth deciles

9 http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=ilc_di01&lang=en 5

QUANTILE Estonia Latvia Lithuania France First decile (%) 2,2 2,2 2,5 3,7 Second decile (%) 4,3 4,3 4,4 5,3 Third decile (%) 5,3 5,4 5,5 6,3 Fourth decile (%) 6,3 6,4 6,5 7,2 Fifth decile (%) 7,5 7,6 7,5 8,1 Sixth decile (%) 9,0 8,8 8,8 9,1 Seventh decile (%) 10,6 10,4 10,3 10,2 Eighth decile (%) 12,8 12,6 12,4 11,5 Ninth decile (%) 16,1 15,7 15,4 13,9 Tenth decile (%) 26,0 26,6 26,7 24,6 And we’ll get the upper middle class shares of Income.

Estonia Latvia Lithuania France Upper middle class share of Income 39,5 38,7 38,1 35,6

Not surprisingly the the income of upper middle of Baltic States is higher than of French one.

3.5. How many spots in residences can the middle class afford in the capital regions of Baltics. We know that the population of the capital regions of Baltics (Riga, Tallinn, Vilnius regions) is 1,7M, or 26% of total population.

Mean net income data are available from Eurostat10

10 http://appsso.eurostat.ec.europa.eu/nui/show.do?query=BOOKMARK_DS-053408_QID_575E70E7_ UID_-3F171EB0&layout=TIME,C,X,0;GEO,L,Y,0;HHTYP,L,Z,0;INDIC_IL,L,Z,1;UNIT,L,Z,2;INDICATO RS,C,Z,3;&zSelection=DS-053408INDICATORS,OBS_FLAG;DS-053408INDIC_IL,MEI_E;DS-053408 HHTYP,TOTAL;DS-053408UNIT,EUR;&rankName1=HHTYP_1_2_-1_2&rankName2=INDIC-IL_1_2_ -1_2&rankName3=UNIT_1_2_-1_2&rankName4=INDICATORS_1_2_-1_2&rankName5=TIME_1_0_0 _0&rankName6=GEO_1_2_0_1&sortC=ASC_-1_FIRST&rStp=&cStp=&rDCh=&cDCh=&rDM=true&c DM=true&footnes=false&empty=false&wai=false&time_mode=NONE&time_most_recent=false&lang= EN&cfo=%23%23%23%2C%23%23%23.%23%23%23 6

Mean equivalised net income Estonia Latvia Lithuania France 2014 11 287,00 € 8 912,00 € 9 408,00 € 22 444,00 €

Based on it we can calculate the net income for 1 person of upper middle class per year

Estonia Latvia Lithuania France Upper middle class share of Income 39,5 38,7 38,1 35,6 Upper middle class share of population 30% 30% 30% 30% Equivalised net income for upper middle class person (each of household) per year 14 861,22 € 11 496,48 € 11 948,16 € 26 633,55 €

So taking into account the population of each of the countries we’ll get the equivalised net income for upper middle class person (each of household) per year for all the 3 Baltic Countries of 12 417,47 €

Now we will calculate the population of the households of Middle Class of the capital regions of Baltics — 507 000 (30% of 1690 000).

Based on the quantity of beds/ALF units in Ile-de-France (93 730) and the average price (2501 euros per month) and the net Income of households of Paris region we can get the percentage that the French upper middle class spends on the payment of spots in live-in facilities- 2.9%

% of Net Income Upper middle Net income of the of households Total class households of upper spent for NH Population population middle class and ALF Baltics Capital Areas 1 690 000 507 000 6 295 655 057 € 0,029 Ile de France 12 000 000 3 600 000 95 880 768 000 € 0,029 By applying this percent to the net income of upper middle class households of Baltics capital regions and using of 1000 euros per month as the price for live-in facility, we get that 15400 beds/ALF units can be paid by Middle Class families.

Average Spending per % of Net Income of Q-ty of beds/ALF price year for beds households units Ile de France 2 501 € 2 811 900 000 € 0,029 93 730 Baltics Capital Areas 1000 € 184 632 985 € 0,029 15 401 The ratios of aged people to total population/middle class are quite similar in Baltic states and in France. The percentage of all population older than 65 years is 17.0%, 17.9%, and 18.4% in the three Baltic states compared to 17.5% in France. We can conclude that the presented calculations are appropriate and the purchasing power of the upper middle class of the capital regions of the Baltic States is sufficient to pay for

15 401 beds/ALF units, which easily covers easily our plans for 612 beds & ALF units.

3.6. State and municipal participation in reimbursement When we talk about the comparison with French situation, we should mention, that the presented figures - as 3294 euros per month in Paris is the price of lodging only (le tarif hébergement). The total cost of the staying in EHPAD consists of three parts

- Lodging - “Tarif hébergement” - ADL (Assisted Daily Living) - “Tarif dépendance” (totally covered by state program APA) - Medical care - “Tarif soin” (covered by medical security)

Lodging is not covered in France by municipality of state. In Baltics the total sum of payment for a day in municipal and private residences is not structured the same way, but is consolidated. Only one price exists that includes Lodging, ADL and Medical care, if needed.

In the last few years municipalities started to intervene in coverage of services supplied by private operators. For instance 33 residents of Dzintara Melodia get the subvention from social department of Riga Duma on a 250 euros level basis, what doesn’t depend of the level of income of their families. This system is not yet well developed or clear. For instance in Vilnius and Tallinn the compensation may reach 400 euros per month, but will depend on the level of pension of the resident.

Taking into account the possible and inevitably forthcoming municipal participation in reimbursement of stay of residents in private residences makes our calculated proofs of the balance of supply/demand even stronger.

4. SIGNATURE Nicolai Kobliakov, 1/9/2016, Riga.

5. ANNEX.

5.0.1. ACSAF (Aged- care services analysis framework). To compare all the aged care residences that exist around the capitals of BaC we have used our own Framework developed based on our marketing experience of positioning of the newly opened residences. Nine groups of parameters (A-I) are inspired by the traditional Maslow Pyramid and represent the ability of a residence to satisfy the basic needs of the resident, while three others (J-L) characterise the management processes in the residence.

5.0.1.1. Groups of parameters of aged-care residence

The value assigned to each of the 12 groups is the sum of values (+1, -1, 0) corresponding to replies to 12 precise questions11, which are collected during the visit to the residence.

“ Nine groups of parameters (A-I) of ACSAF are inspired by the traditional Maslow Pyramid and represent the ability of a residence to satisfy the basic needs of the resident

”

11 The example of filling of the framework (144 questions) according to results of the visits to residences round Tallinn can be found here https://docs.google.com/spreadsheets/d/1pn33zvqvnmjIRYM2_1Jck63HmDTVIKbWS880gvU16QE /edit?usp=sharing

As a result we receive 12 values that present a portrait of the residence.

GROUP OF PARAMETERS DESCRIPTION The value of real estate object, its general comfort Real Estate Value level, location etc. The level of adaptation of the real estate object for Housing Adaptation needs of aged persons Security The level of security assured by residences The parameter characterising the range of concierge Concierge services supplied in the residence

GROUP OF PARAMETERS DESCRIPTION This parameter characterises the quality of cooking Food and of catering processes. Assisted Daily Living services (bathing, toileting, ADL feeding, dressing assistance) Medical Medical services and access for medical services Family Connections Stimulation and support of family connections

GROUP OF PARAMETERS DESCRIPTION The degree of independence, social life, prevention of Social Life/Prevention loss of mobility Marketing of Residence The quality of marketing of residence Operations The quality of operations in residences The way of pricing, of presenting the prices for residents, the comparison of prices with general Pricing assumptions

The theoretical range of change of each of the group value is from -12 to +12. We place all the values on the rays of a radar chart and get a clear visual presentation of the residence in the ACSA framework.

5.0.1.1.1. The example of ACSAF Portrait of residence

We can see from this portrait that the SA PJV Hoolduravi residence positions itself primarily as extremely medicalised, with high level of control of quality of operations, occupying a building that is highly adapted and whose security level is high. At the same time (what we see from orange sectors), the RE value is not so high (the building is specialised), concierge services and family connection can be improved.

5.0.1.2. A-score And the sum of those values we call “A-score”. It characterises the visible coverage by residence of different needs of aged-care residence of quality of services. The ACSA framework is permanently adapted to meet better the requirements of market strategy development.

5.0.2. Tallinn area residences analyses

10 residences were visited and analysed in the 20 km radius around Tallinn area. Name of Maximal Q-ty of "A"- Residen Facade Portrait Price, Beds Score ce euro

Iru Hoolde 385.00 30.00 4 kodu

Nõmme Sotsiaa 18.00 30.00 -15 lmaja

Rannap ere 64.00 32.83 13 Pansio naat

Eakate Hoolde 20.00 34.00 -25 kodu

Kursan a Reside 144.00 39.40 66 nce Tallinn

Pansio naat 18.00 25.00 -36 KOSE

Rae Hoolde 24.00 36.00 12 kodu

Hiiu Ravikes 150.00 43.73 28 kus

Paunkü la 80.00 26.00 -45 Hoolde keskus

Benita 100.00 42.00 85 Kodu

SA PJV Hooldu 150.00 29.96 31 sravi

We’ll use the findings of the implementation of ACSA framework in Baltics for - Marketing positioning of our residences - For pricing strategy But first of all we should verify that our ACSA is reasonably balanced, i.e., that the chosen criteria and grouped parameters correspond to consumer perceptions of the aged-care market. The detailed file is presented here: https://drive.google.com/open?id=1kiRnLh-SxkVhTJPO9RsKgWVJcvzRj86KyVfFNKjwBVM

5.0.2.1. MDS Analyses12

To assess the effectiveness of the developed “A-Portraiting” method we have performed the MDS Analyses of the existing residences’ dataset. Our interviewers filled the table with the subjective visions of their similarity after the visit to all the residences.

5.0.2.1.1. Table with the levels of similarity of visited residences in Tallinn area. (0- similar, 10- far)

Iru_Ho Nõmme_S Rannapere Eakate_H Kur Pansion Rae_ho Hiiu_Ra Paunküla_H Benit SA_PJV_H oldeko otsiaalmaj _Pansionaa ooldekod san aat_Kos oldeko vikesku ooldekesku a_Ko ooldusrav du a t u a e du s s du i Iru_Hoolde kodu 0 7 5 10 6 8 6 2 10 7 4 Nõmme_So tsiaalmaja 7 0 8 7 8 10 8 10 7 10 8 Rannapere _Pansionaa t 6 8 0 8 6 8 7 6 10 6 7 Eakate_Hoo ldekodu 8 5 8 0 8 6 6 8 8 8 8

Kursana 5 8 5 7 0 8 8 5 10 4 7 Pansionaat _Kose 7 9 7 7 8 0 7 10 9 8 10 Rae_hoolde kodu 8 8 8 8 8 6 0 7 8 6 6 Hiiu_Ravike skus 4 10 8 10 6 10 7 0 10 8 4 Paunküla_H ooldekesku s 10 5 10 6 8 7 8 8 0 10 10 Benita_Kod u 9 10 5 10 4 10 10 10 10 0 7 SA_PJV_Hoo ldusravi 4 10 8 10 6 10 7 4 10 7 0 Based on this table the MDA analysis was performed what allowed us to make the perceptual map of the Aged- Care landscape

12 https://en.wikipedia.org/wiki/Multidimensional_scaling 17

We see that all the visited residences are concentrated in 4 groups. We see that in the upper right quadrant there are 3 private residences with highest “A”- score. Residences of the upper left quadrant have relatively high level of housing adaptation, security, and medical component. Upper left Quadrant residences Upper right quadrant residences

The bottom right quadrant is characterised by relatively high level of concierge service and operations. The residences of the bottom left quadrant are focused only on ADL services without covering others possible spheres of aged-care. Bottom left quadrant residences Bottom right quadrant residences

We can conclude that the ACSA framework doesn’t contradict the perceptual mapping, so we will try to use it for pricing strategy.

5.0.3. Implementation of ACSAF for pricing strategy. If we make the chart of dependency of the Maximal price & Minimal prices charged by residences of our “A-Score” we will see a near linear dependence

5.0.3.0.1. Prices vs “A”- score for Tallinn area

The representatives of Estonian live-in aged-care market whose “A-score” exceeds 90 points currently charge from 20 to 45 euros per bed per day. “ The representatives of Estonian live-in aged-care market with “A-score” over 90 points charge from 20

to 45 euros per bed per day.

” This confirms that the price we are going to charge is in line with the market if we take into account the planned “A-score” of our NH and ALF clusters.

Currently we are performing the ACSAF research in Riga and Vilnius areas. The first results conform to the ones received in Tallinn.

Residences analyzed around Riga Residences analyzed around Vilnius

5.0.3.0.2. Prices vs “A-score” for Riga area

5.0.3.0.3. Prices vs “A-score” for Vilnius area

5.0.3.0.4. Prices vs “A-score” for All the three capitals (Riga, Vilnius, Tallinn) area

5.0.4. Not modern The chart of years of construction

5.1. Size of bubbles: with toilet or without toilet

5.2. Size of Bubbles: Medicine

Horizontal axis can be considered as a level of medical support

5.3. Size of Bubbles: ADL Vertical Axis: ADL

5.4. Size of Bubbles: Social Life

Vertical axis is the level of social life except for small and extra small residences

5.5. Color: is private or not We see that the upper part are all the privates

5.6. Size- Quantity of floors