Utilizing Technology: Analytics • Section 7
ics is the using the technology of computers and software to per- form thousands and even millions of calculations to find connec- tions and correlations from the massive amounts of data about our tenants, policies and procedures. It helps us find millions of dollars of potential income that is being overlooked. We can turn mounds of data into useful information, then turn that informa- tion into knowledge, that knowledge into predictions, and those predictions and repetition of testing into wisdom. Wisdom is a result of knowing how and when to use our new
A
knowledge to achieve our desired results. We can also get a bet- ter understanding the boundaries or limits, and exceptions to the rules. It is critical to know how and when to use the new rules and exceptions in order to avoid negating any of our income en- hancements. By further optimization and sensitive analysis of this new found knowledge, we can also find the points of diminishing returns and thus save both time and money. In Table 7.1, data from over 1000 facilities was assembled to
indicate the median number in various categories such as late fees waived, delinquencies, late fees waived, etc. You can com- pare your operations to those of the median to see if you are do- ing better or worse than the industry on average. For example, the median number of transfers between units at a location per month is three units. If your facility is doing a much larger number than this, you should investigate why. Are the managers not prop- erty trained to show the correct size units, or are the managers stealing from you by manipulating the computer system? Other data can inform you if you are not on top of your collections or not auctioning off bad tenants often enough.
Rate Management Currently, the self-storage industry uses rudimentary forms of rate management. Typically, the REITs use between 25 and 35 param- eters to determine who, how much, and when a tenant gets a rent increase. Our industry can now become like the airlines and car rental companies with very sophisticated analytical techniques to vastly improve our bottom line numbers. By exporting the data from your management software into analytic programs, you can write macros and put the data into various charts or reports to as- sist you in analyzing the data in ways that can lead to some very interesting discoveries. Some types of auditing software are designed specifi- cally for the self-storage industry to do these things for you. These programs can automatically convert the data to create hundreds of different self-storage reports and charts. These can answer, for example, who, how much, when, and even why tenants should be raised. Since there are so many possible combinations, it’s nec-
essary to use complex computer analysis and algorithms to handle each of the thousands of tenants. For example, soft- ware can analyze every move-out your site has ever had and indicate important parameters as to why and when tenants move out, the length of stay, and how long it takes to release
s we seek answers to our questions about how to improve our operations or make more money, man invents new methods to get these answers. Data mining or data analyt-
each type and size of unit. It can calculate each tenant’s tolerance to rent increases. One such software analysis found that the 10 percent of ten-
ants who move out because of rent increases typically do so less than 10 days prior to the increase; 45 percent move out in the first 30 days of the increase; and the next 45 percent will do so within the next 34 days. Another discovery was that while credit card tenants in general don’t stay any longer than check writing tenants, American Express card users do stay approximately four months longer than Visa, MasterCard or Discover users. Knowing the actual length of stay for each unit type, and
knowing historically what you actually collect, you can determine the average amount of income you can expect to receive each time one of those units is leased. When you see that a particu- lar unit might typically bring in thousands of dollars each time it is leased, you might be willing to offer more from a marketing perspective to get that tenant. Some operators may even offer a Kindle or an IPad to get a particular type of unit leased. With such knowledge, good judgment and some restraint will
be necessary in order to not alienate our tenants with too rapid or excessive increases.
What Is Economic Spread? Other than leasing more units, a tremendous amount of money is being left on the table by inefficient operations. By measur- ing and watching your “economic spread” you can increase you income by thousands if not tens of thousands of dollars each month, even without increasing your occupancy. In Chart 7.1 on the next page, the distance between the physi-
cal occupancy line and the economic occupancy line is the eco- nomic spread. Economic occupancy is calculated by dividing your actual income by the gross potential income if you were 100 per- cent occupied. It mainly consists of the money not collected from discounted rents, concessions, uncollected accounts receivable, employees waiving fees or rent, and employee theft. You can open the spread by increasing your standard rates, and then close the spread by focusing on the items above. By opening and closing the economic spread, you can drive
your income up without leasing a single unit. As you can see from the chart, the physical occupancy even dropped a little during the timeframe, but the income increased by $20,000 per month.
Table 7.1 – Median Comparison 1st of
Late Fees Waived Per Month Late Fees Charged Per Month
Number of Tenants/Amount 0-31 Days Delinquent Month-End Goal*
Number of Tenants Over 31 Days Delinquent Amount Delinquent Over 31 Days Median NON-EXP. Rent Disc./Mo. Rent Concessions Per Month
Transfers Between Units Per Month * Goal is to be at these numbers or less at the end of the month
Month Billing $105.00
$1,011.00 38
3% 11
$2,644.00 $4,666.00 $1,790.00 3
Anniversary Billing
$105.00
$1,011.00 $7,660 11.30% 11
$2,644.00 $4,666.00 $1,790.00 3
Source: © 2014 District Manager 2015 Self-Storage Almanac 81
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132
