Leveraging analytics in a thriving self-storage industry
The self-storage industry is a thriving market in the pandemic and post-pandemic era. By the year 2025, it is expected to become a $115.62 billion USD market according to Mordor Intelligence research. This sets the compound annual growth rate (CAGR) at a whopping 134.79% over the forecast period of 2020–2025. This means the rate of return on investment will compound over years and this sounds like a great recipe for investment. In a recent bid of investment, Microsoft co-founder Bill Gates and GIC Private Ltd. (Singapore’s sovereign wealth fund) became a joint owner of one of the largest self-storage operators in the USA.
“The self-storage sector is rapidly evolving, and companies that can deploy technology, enhanced operations, and a truly memorable customer experience are going to outperform.” — Cris Burnam, CEO, StorageMart
This forecasted growth rate, however, comes with strings attached and does not guarantee the performance of the industry in the future. Deploying the right technologies in place that enhance the operations is key. What could potentially maintain, neigh, propel this growth is its marriage with analytics. We have seen many such examples in the past both where industries benefitted manifolds by early adoption and of those who were late to join the bandwagon and missed out on their potential.
In this blog, I’ll touch upon:
1) the ways analytics is impacting self-storage
2) what future holds for this space
3) risks that the self-storage industry should look out for
Analytics impacting self-storage
Data is the new oil”. — Humby 2006
In my five years of working with the world’s largest pure-play big data analytics company, I have seen organizations thrive when they followed a layered approach to setting up their analytics teams: Data Engineering layer where data related to processes and day-to-day operations is captured, Data Analysis layer where data is transformed and analyzed to extract its value, Data Science layer which leverages statistics to build sophisticated models and find patterns in the analyses, and Decision Science layer which is the most critical for the generation and consumption of insights bring in the business knowledge and communicates with a larger audience.
In my more recent experience, with one of the world’s largest self-storage companies, it is evident that the self-storage industry has not shied away from adopting big data and analytics. It is being used to personalize the customer experience, in automated kiosks on-site, and in bringing about digital transformation. The self-storage business is disrupting and there are a lot of fuzzy problems that the businesses need to answer to stay current. How many consumers visit my website? What part of geography are my customers coming from? Which social media is most effective at attracting people to my website? Analytics has deep potentials in coming up with solutions to these fuzzy problems.
Future Scope of analytics in self-storage
According to Salesforce, 61 percent of marketers agree that AI helps them hyper-personalize their campaigns, and 59 percent believe AI increases their productivity.
Advancements in technology directly impact the experience of a self-storage customer. Leveraging analytical projects such as the use of Artificial Intelligence would help personalize the content for consumer cohorts, analyze the return on investment on marketing channels, identify buyer purchase propensity. This will provide a strategic advantage to the self-storage industry which will increase conversions and will optimize their operations.
The adoption Internet of Things (IoT) in self-storage would revolutionize the field by effecting the paradigm shift from descriptive/inquisitive analytics to predictive/prescriptive analytics. I have worked with an energy sector client that adopted IoT in its fledgling form and reaped benefits where they are were able to leverage data collected by millions of sensors to run predictive maintenance and preempt failures in their wind turbines. The possibilities are endless — from avoiding breakages and thefts to providing real-time monitoring of energy consumption and humidity thus making the overall operation more efficient.
Risks associated with the implementation
There is no two way about the impacts of analytics. However, what distinguishes a successful adoption of analytics from a failed one is the implementation. There are risks associated with the implementation of analytics in organizations. According to MIT’s management review, most data science and analytics projects fail when the teams do not have consumption and impact as their focus. When analytics teamwork in silos in an organization, they are seldom close to the reality of business and are restricted till the Data Science layer of an organization. They are unable to adopt the Decision Science layer, are not able to communicate their insights, and hence often end up not satisfying the end stakeholder.
To conclude, this calls for the Chief Information Officers and Chief Data Analytics Officers to adopt a more encapsulating and comprehensive meaning of the role of analytics within their companies. It should entail higher collaboration between data scientists and business stakeholders responsible for diagnostics, administration, and implementation.
References:
[1] https://www.smartdatacollective.com/ways-big-data-impacting-self-storage-industry/
[2] https://www.insideselfstorage.com/technology/using-iot-technology-and-predictive-analytics-conquer-self-storage-challenges
[3] https://www.insideselfstorage.com/marketing/google-analytics-online-tools-assess-performance-your-self-storage-website
[4] https://www.storedge.com/using-analytics-to-measure-the-success-of-a-self-storage-marketing-campaign
[5] https://www.cpexecutive.com/post/keeping-a-self-storage-business-viable/
[6] https://www.cpexecutive.com/post/self-storage-to-maintain-steady-growth/
[7] https://www.cpexecutive.com/post/self-storage-everyone-wants-a-piece-of-the-pie/
[8] https://sloanreview.mit.edu/article/why-so-many-data-science-projects-fail-to-deliver/
[9] https://www.kdnuggets.com/2014/10/interview-toni-jones-business-insights-social-media.html
[10] https://www.forbes.com/sites/theyec/2019/11/25/four-predictions-about-the-self-storage-industry/
