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Host Analytics has introduced AirliftXL, a new feature of its cloud-based financial performance management (FPM) suite that enables its software to translate users’ spreadsheets into the Host Analytics format. I find it significant in three respects. First, it can substantially reduce the time and resources it takes for a company to go live in adopting the Host Analytics suite, lowering the cost of implementation and accelerating time to value. Second, it enables Host Analytics users who have the appropriate permissions to create and modify models and templates that they use in planning, budgeting, consolidation and reporting. This can enhance the value of the system by making it easier to maintain. Third, it can make it far easier to routinely collect and connect planning and analytical models used by all departments and business users as it has outlined in its planning cloud offering. Although it has limitations in its initial release, AirliftXL gives corporations a workable alternative to stand-alone spreadsheets and has the potential to substantially increase productivity and effectiveness of an organization in the full range of budgeting, planning, consolidation and reporting functions.

AirliftXL addresses a fundamental issue that diminishes the productivity vr_ss21_spreadsheet_maintenance_is_a_burdenof companies, especially finance departments. I’ve noted in the past that desktop spreadsheets are indispensable tools for individual tasks and ad-hoc analysis and reporting, but they are poorly suited to repetitive collaborative enterprise-wide functions such as planning, budgeting, consolidation and reporting. Spreadsheets are seductive because so many people are well trained in using them that they can translate their ideas into even complex models, do analysis and create reports. However, the productivity that spreadsheets afford in authoring is more than offset when they are used over time. Desktop spreadsheets have fundamental technological shortcomings that make them unwieldy for any repetitive, collaborative task. After more than a few people become involved and a file is used and reused, cracks begin to appear. Very quickly, a large percentage of the time spent with the file is devoted to maintaining and updating them, as our spreadsheet research has shown with up to 18.1 hours per month in maintenance that I have analyzed. Spreadsheets are notoriously error-prone. In addition to monetary losses, some of which have been spectactular, there is a drag on productivity as users try to locate the source of errors and discrepancies that routinely occur in spreadsheets and then fix those mistakes.

AirliftXL enables ordinary users to create spreadsheet models and reports in Microsoft Excel and then quickly convert these to the Host Analytics enterprise system. Those that “own” a model, analysis, report or process can control these in Host Analytics. This speeds the process of setting up Host Analytics because there’s no need for someone to “translate” the company’s current set of spreadsheet models, analyses and reports. This cuts the time (and therefore the cost) of setting up the new system.

It also means that whenever changes need to be made, those responsible can make the changes themselves. Allocations and analytical models used in planning and consolidations can become part of a company’s system almost immediately. These alterations can be effected by “exporting” the Host Analytics object to a spreadsheet, modifying it and uploading back to the system. As well, users can create new models, analytics and reports in Excel and import them into the Host Analytics system. There’s no need for resident expertise or consulting time to make such changes. AirliftXL provides an organization with the best of both worlds: first, the up-front productivity that comes from enabling the author, a subject-matter expert, to quickly translate his or her ideas into a spreadsheet and, second, the ongoing productivity that is achieved when the plan, analytic model or report is kept in a centralized, easily accessible and controlled environment. These same authors can update and expand their analytical models or reports. Host Analytics can render models back into an Excel spreadsheet and the owner – not a consultant or trained IT person – can make the necessary changes and then upload them back into the system. This is an important capability because change is a constant in businesses and these changes must be reflected in financial performance management systems.

Organizations have hundreds, sometimes thousands, of spreadsheets circulating that support a multitude of processes and users in every department and business unit. AirliftXL can help incorporate them into a controlled enterprise software environment. Information that today is kept in one part of an organization can be viewed and used by others. Budgets and integrated business plans can quickly incorporate the most up-to-date information. Complex models now held in spreadsheets can be more controllable, consistent and safely accessible to a wider group of users. Creating links across individual spreadsheets (say, sales forecasts prepared by the sales organization and a company income statement forecast prepared by Finance) is straightforward, although linking to external data sources (say from a spreadsheet to a relational data store) is a little trickier. As well, Excel’s built-in financial, statistical and logical functions are all maintained in Host Analytics.

AirliftXL has the potential to be an important differentiator for the company. IBM Cognos has had something like this in Cognos Insight but from my analysis it is not as easy to use as the Host Analytics feature. Some corporations have finance IT professionals with deep subject-matter expertise as well as IT systems skills, but even their presence does not address the root cause of the misuse of spreadsheets. Most people who understand the needs of the business lack the IT skills necessary to use their company’s systems. They default to using spreadsheets because it is more expedient than trying to transfer their knowledge to someone who understands IT systems.

While AirliftXL is an important first step in taming the spreadsheet problem, it has limitations. For one, it’s not possible at this point to create a dynamic model such as an integrated income statement, balance sheet and statement of cash flows. This is a snap in a two-dimensional spreadsheet grid but much harder when working with a relational or multidimensional database. Moreover, there’s no guarantee that the spreadsheets imported into Host Analytics will be free of formulaic errors or even if it is well constructed. Thus, companies will need to put quality control processes in place, especially if a spreadsheet can have a material impact on the accuracy of financial statements or could defeat controls for fraud. It also would be handy if some vendor would create a product that could automate the digestion of masses of spreadsheets floating around companies as described in this patent for extracting semantics from data.

Despite these reservations Host Analytics’ AirliftXL provides an VI_FPM_Hot_Vendorimportant capability that can cut costs of deploying and maintaining its software and increase its value to a company. This advancement builds on top of its recent rating as a Hot Vendor in the 2013 Value Index on Financial Performance Management.  I recommend that corporations looking to change or upgrade all or some of their financial performance management suite consider Host Analytics and how AirliftXL helps transition the use of spreadsheets to a dedicated application approach.


Robert Kugel – SVP Research

Host Analytics has added new analytics and reporting resources to its cloud-based performance management suite. Business Analytics will offer a broad set of built-in analytics and reporting capabilities or, for companies with an existing business intelligence infrastructure (from vendors such as IBM, Infor, Oracle or SAP), the option of a self-service approach. I believe these new analytics and reporting capabilities give companies considering only on-premises performance management deployments another reason to consider a cloud-based option; for Host Analytics it broadens the set of features it has to compete with other cloud-based vendors.

People in finance and accounting have been doing analytics for centuries: balance sheet ratio analysis, margin analysis and financial performance metrics (to name three) are established, well-developed techniques in finance departments. The challenges they face are not with the analytics themselves but with the data being analyzed. Our Finance Analytics benchmark research finds that, for example, only 31 percent of finance organizations consider their data used to prepare metrics and indicators to manage performance to be accurate. More than three-fourths (78%) of finance professionals said that they spend the biggest chunk of time on getting the data ready for analysis. Half (51%) of companies said that the difficulty of collecting data impedes the creation of useful metrics and key performance indicators (KPIs). These are serious issues in terms of efficiency and effective use of information.

With its Business Analytics Host Analytics attempts to address these issues by giving people in Finance access to data that currently may not be able to get, and not just financial data. In addition to prebuilt connectors for a variety of ERP systems (including those from Epicor, Intaact, Microsoft Dynamics GP, NetSuite and SAP ByDesign), Business Analytics can pull in sales pipeline data from or Siebel, marketing analytics from Eloqua or Marketo, operations analytics from Plex or SAP and HR analytic data from PeopleSoft and SuccessFactors.

To cut the time spent in preparing data, self-service capabilities are important. Fully 60 percent of finance professionals in our research said that analytics are too hard to build and maintain, and half said the process is too slow. One reason for the latter is that many analytics are created by IT departments or require IT intervention.

Combining financial and operational data can address another issue we find in our research. Understandably, Finance departments focus their efforts on standard financial analytics but pay less attention to areas where the combination of financial and operational data could produce analytics that provide deeper insight or better performance metrics. For example, incorporating up-to-date pipeline or lead conversion information in a weekly or monthly financial review can be useful in providing leading indicators of out- or under-performance relative to the plan, as well as useful trend data. Having detailed headcount data can help executives uncover the root causes of cost variances to determine what steps to take – if any – and to what degree current projections must be modified to reflect recent experiences. And having ready access to source data addresses another issue: Only 31 percent of finance organizations said the data used to prepare metrics and indicators is accurate enough to manage performance.

Providing Finance, HR and potentially other functions of a corporation with self-service analytic capabilities addresses another often-unmet need. Nearly all (89%) of participants in our Finance Analytics research said that it’s important to make it simpler to provide analytics to those that need them.

The addition of Business Analytics follows Host Analytics’ introduction of its Decision Hub, which I reviewed last year. The Hub provides a common data repository for information that companies can access, which may be from third-party sources as well as internal. It is another component that makes it easier for organizations to work with a structured, common data set.

I recommend that finance organizations considering the purchase of a system that can perform any combination of planning, budgeting, consolidating and reporting consider a cloud-based approach. This is especially true for midsize companies (those with between 100 and 999 employees, by our definition) or divisions of larger corporations; both often lack the scale or resources to support the underlying IT infrastructure or find that managing these capabilities in-house chews up too much valuable management time. If your company assessed a cloud-based offering more than a year ago and decided against it, I suggest it’s time to re-evaluate your options. If your company is evaluating cloud-based performance management systems, I recommend including Host Analytics in that assessment.


Robert Kugel – SVP Research

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