Institutional Real Estate, Inc.

NAREIM Dialogues: Spring 2017

The Institutional Real Estate Inc Sponsorship brochure, Connected-Investor Focused, We connect people, data and insights, sponsorship, events, IREI Products

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Causes & Characteristics of the Problem Let's review several of the root causes of this problem: • DISTANCE BETWEEN SOURCE AND USERS: Quite commonly, the enterprise that captures and creates source data (e.g., property managers) is different from the enterprise that uses that data to create value and manage risk (e.g., investment managers). And the movement of that data – sometimes in summarized form, sometimes in very granular form – from one group to another is a fragile and error-prone. Worse, these problems tend to compound each other with each upward 'leg' in the journey of data from source to user. • POOR SPECIFICATION OF DATA NEED: While agents acting at a lower level in the data supply chain are universally expected to supply information upward, it is generally the case that the specification – of what information will be provided, according to what standards, and when – is poor or lacking altogether. Investment managers too often assume that since the lower-level provider "is in the real estate business they will know what I need and will get it to me…"' • ALTERNATING DEMAND FOR SUMMARY AND DETAIL: Users of information at higher levels in the chain often assert that they only need summary information, since it's their job to 'see the big picture', not to redo the work of those below. This is fine when things are going as expected! But as soon as there is something in the summary that is unexpected or troubling, then that same user wants immediately to 'drill down into the detail' – which either isn't available, requires massive effort to compile, or is beset by errors. • FALSE SOLUTION – 'GET EVERYTHING': In those moments when an investment manager suddenly needs to 'drill down', there is often a knee-jerk demand to 'get everything' – since "Get everything!" is much easier to say then "Get me these specific things at this specific level of detail...' And, because if getting everything was possible, that would be great! However, for a host of reasons, 'get everything' has never been known to work at scale. • FALSE SOLUTION – 'SHINY ANALYTICS': Perhaps the most common response to the conundrum of real estate data is to try to 'solve' the problem by adding analytic tools (e.g., data warehouse, BI solutions, or even big data processing tools) at the 'top' of the investment manager's application stack. But of course, since all such tools rely on complete and trustworthy source data, these shiny solutions are likewise doomed to consume a great deal of energy, and generate a lot of noise, but ultimately either under-deliver or outright fail. Costs & Risks While navigating these various problems, both GPs and LPs spend significant time and effort capturing – and building trust in – the information they need. The costs involved, and the risks associated with the effort, can be significant. • EXPENSE OF DUPLICATED WORK: Because throughout the enterprise, individuals must find (and re-find) and verify (and re-verify…) data before it is used. This duplicated work is, at best, redundant and inefficient. But when highly compensated individuals – asset managers, for example – report spending 25% or more of their time on such 'data wrangling', the economic consequences become very material. • RISK OF PICKING UP THE WRONG DATA: Because data is stored in many places, what seems correct may be an old copy that is inaccurate or out of date. • RISK OF RELYING ON THE WRONG NUMBER: Because a business measure has a common name, the user assumes he or she knows the underlying calculation, when, in fact, a different calculation may have been used. • RISK OF INACCURATE REPORTING: If any of a number of potential errors aren't caught, the wrong number could be published, causing reputational damage and potentially triggering specious decisions. Effectively managing enterprise data is demanding. But the costs and risks associated with not rising to the challenge are likely far greater than the cost of addressing the challenge with a solid strategy. Strategic Options: Application-Driven Strategy vs Data-Driven Strategy So, how should a committed investment manager go about building a solid information foundation? The question has resisted easy answers throughout the several-decade-long rise of real estate as an institutional asset class. To keep it simple, there are two common strategies for getting the information they need. One strategy can be called an "Application-Driven Strategy." This strategy is currently followed by a number of large managers, most of whom adopted the strategy years or decades ago and have not re-evaluated this strategy – even though it tends to lead to a state of FEW REAL ESTATE INVESTORS – either fund managers or plan sponsors – today doubt the importance of data as critical to their business. Yet, as an institutional asset class, real estate has long lagged other asset classes with respect to data transparency and standardization. And whether a cause or effect, the flow of information – from the lowest, source level to the portfolio and asset managers who act on that information to create value or mitigate risk – is problematic at best. ©iStock.com/chekat 17 NAREIM DIALOGUES SPRING 2017

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