The Occupancy Equation: What It Really Takes to Build Stability

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Occupancy Matters Deborah Howard, Founder, Senior Living Smart Carlene Motto, Chief Marketing Officer, Belmont Village Senior Living


Trends affecting our business Conventional approach to occupancy Reframing the occupancy model Exploring the drivers Discussion 2

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Red Ocean or Blue Ocean?

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Think different: think Blue

Blue Ocean Opportunity

Red Ocean Reality • •

• • •

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Compete in existing market space Beat the competition Exploit existing demand Commodity/ Vanilla Operational model will not work for next wave of residents/ families Increased lead acquisition costs/ 3rd party

• • • • •

Create uncontested market space Make the competition irrelevant Create and capture new demand Niche/ Specialty Personalization and choice of the prospect/ resident journey Organic lead generation


Churn: Occupancy is volatile

Move-ins are not always keeping up with move-outs

“With more volatility in the marketplace … remaining competitive means senior living companies must be vigilant with their strategies“ January 3, 2016

Source: NIC MAP 1Q2016

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Understanding move-outs: by the numbers

Death is not the only reason for move-outs.

92% cite resident health as leading reason for move-out (up from 72%) 22 months average length of stay in assisted living (down from 36 months) 54% annual resident turnover pressured by rise in acuity (up from 41%) $4,000 cost per resident turnover. $200,000 annual community cost to replace residents from turnover (100 bed community) Source: Illumination 2016 Analytics 10 year analysis

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New construction: Competition with new buildings

Source: NIC MAP

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Low penetration is everyone’s challenge

Source: The Scan Foundation, Data Breach

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Commodification: Crest or Colgate? We’re all selling the same things:  Chef-prepared dining  24 hour clinical coverage  Rehabilitation  Fitness  Computers  Memory care Assisted Living customer decision making boils down to price and location.

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Pressure above and below the line

Shorter resident stays Increased resident acquisition costs Increased operating costs Reduced top line revenue Increased Risk and Liability

Revenue DOWN

Expenses UP

Reduced bottom line NOI

NOI DOWN 10


Conventional Thinking: Sales = Occupancy

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Conventional Sales Team

Inside sales

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Outside sales


Conventional Work Flow

Inquiries

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Tours

Closing

Move-in


Conventional Occupancy Model

Sales Fills Building Occupancy Declines

Sales Fills Building Repeat

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100%


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Busting the myth: driving sales will not be enough

New challenges thwart performance

100% The Occupancy Gap

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Blue Ocean Occupancy Equation

Stable Occupancy = Move-Ins +/- Service Delivery +/- Retention

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From Sales Team ‌

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… to Occupancy Team

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From sales plan ‌ to Occupancy Plan

Stable occupancy: Is the common goal. 2. Requires participation of entire staff. 3. Is supported by coordinated strategies for clinical, operations, sales. 4. Is supported by a culture of service. 1.

CLINICAL

SALES

OPERATIONS SERVICE 20


Exploring the Blue Ocean Drivers

Sales Operations Clinical

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Sales Drivers

Consumer

SALES Personalization

Drivers

24/7 22

Website


“You must know your customer if you want to sell to them.” – Margaret Wylde, ProMatura Group

Recent study by the ProMatura Group suggests spending more time on each senior living sales lead, as opposed to calling and giving tours to as many prospects as possible, could be the most successful way to convert leads into move-ins.

“Industry sales counselors generally focus on the product instead of the prospect,” Wylde said. “Then when confronted by resistance, which is predictable, most simply give up too soon. For prospects that ultimately closed and moved in, the salespeople on average invested almost 18 hours for independent living and approximately 10 hours for assisted living and memory care to learn about them, address their hesitation, and follow up with creative approaches that were personally relevant. If you get to know the user, you’re going to sell more product—period.”

Source: Senior Housing News, May 3, 2016, reporting on analysis of lead and sales data from 502 senior living salespeople using Sherpa during period 1, 2015 to Dec. 31, 2015, conducted by the ProMatura Group

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Jan.


Time spent with prospects pays off Average Time in Minutes per Prospect Worked in 2015 by Quartiles of 2015 Conversion Ratios and Level of Care IL AL/MC 126 112 98

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94 79 62 53

Quartile 1 (Top Performers)

Quartile 2

Quartile 3

Quartiles of Conversion Ratios

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Quartile 4 (Worst Performers)


Sales and Marketing Drivers

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Red Ocean Strategy

Blue Ocean Strategy

Transactional Measuring tasks & activities More leads, more leads! Focus on “Hot Leads”/ Urgent needs Website is the “all-about-me show” No effective after hours sales plan

Relational Measuring relationship building Work fewer leads deeper Focus on earlier stage leads Website is resource rich and focused on consumer 24/7/365 plan to manage inquiries and tours


Consumer – Stages of Readiness What are the options? What do I need to know? How can I make the best choice?

Timeframe, Funding Solutions, Transition

Awareness Research Planning

Action 26

Daily Life, Accommodations/ Amenities, Care, Cost, Floor Plans. Comparing other Options

Room Planners, Move-in Coordination


Consumer - Top of Mind Questions

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Where Will I Live?

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What Will I Do?

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Can I Afford It?

Will Take Care of 04 Who Me? 27


Your Website

87% of Prospects Research Online Before Contacting a Community 1.5 million Searches per Week

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45% of Your Website Prospects Will Make a Decision Within 12 Months

75% Will Buy From The 1st Person They Speak To


Your Website – Lead Generator

Live Chat Interactive Surveys Inbound Content Videos

Tracking Behavior 29


24/7/365 Response Plan

MOD

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Live Chat

Call Center

Marketing Automation


Personalization

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Conventional Industry Indicators

LAGGING

LEADING

? New Leads 32

Call Outs

Tours

Move Ins


PCSSM Leading Performance Drivers

LAGGING

LEADING

Total Time in the Selling ZoneSM

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Time Per Lead

Planning

Creative Follow-Up

Move Ins


Occupancy Optimization

Predicted Length of Stay

Likelihood of Conversion Ranking each prospect based on likelihood of becoming a resident

Ranking each prospect based on their projected LOS in the community

Prospects that OPTIMIZE ALOS Ranking each resident based on the risk of an unplanned move-out

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Move-Out Risk


Number of Call Outs/Tours - Correlation is not Causation

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Operational Drivers

Engagement

Operational Drivers Recruitment and Retention

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Surveys


Operational Drivers

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Red Ocean Strategy

Blue Ocean Strategy

Yearly surveys Hiring, firing and performance reviews Holiday family celebrations Set operational structure

Point in time surveys Pre-emptive recruitment, value recognition, and development Ongoing and proactive family communication and engagement Choice


PreMove-In

Clinical Drivers

Clinical Drivers Predictive Analytics

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ProActive Care


Clinical Drivers

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Red Ocean Strategy

Blue Ocean Strategy

Clinical intervention starts at move-in Reactive approach to care Care Plan No “ownership� of residents in acute settings Not utilizing data

Clinical intervention starts pre move-in Pro-Active approach to care and wellness Personalized Care Plan Protocols for MLOA residents Utilizing predictive analytics


Short Length of Stays: a Real Problem! Move outs in 90 days

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Difficult to catch and monitor Very costly to maintain and operate Creates a vicious cycle… 1. Sales constantly trying to fill beds 2. Focused on quantity of leads over best match 3. Quantity and quick leases result in even shorter length of stay

Familiar pattern with many clients 40


What’s the Solution? Focus on… Smaller number of qualified leads; identify the best candidate Actively monitor and manage resident health and satisfaction This is difficult to do and nearly impossible without tools: Spans sales and clinical staff Large data set, key info not captured or recorded on paper ALIS and Life2 have teamed up to do just that. We have developed tools that… Select prospects based on likelihood to move in and predict length of stay

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Identify current residents at risk of move-out in the next 90 days

Suggest actions that staff can take to improve outcomes


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