Workspace Analytics Definition
By providing a framework to help make high-level IT decisions, workspace analytics essentially extends meaningful perceptions into the overall productivity of the business. This can be achieved by the analysis of end users, the technologies leveraged to work on and the business processes involved to get the work done. Decision makers can better allocate resources and provision time by looking at IT operations from a holistic standpoint of a business engine, rather than just a sequence of isolated gears. This further helps in addressing the evolution of technological needs that surface in the modern workforce.
Many solutions have made appearances in the marketplace today, and the very evident trend of innovation is impressive. Each of them extends to clients, new sets of capabilities that further aim at provisioning deep insights into the digital workspace. This further enables the planning of Unified Endpoint Management (UEM) and the delivery of strong automation. In an all-encompassing point of view, these capabilities aim at helping the IT industry improve upon their security services, compliances and the overall user experience across various environments. Additionally, choosing a solution that takes into account, the information from the digital workspace and makes IT-based decisions accordingly is vital.
Currently, IT is being faced with issues to manage the digital workspace efficiently; this is mostly fueled by the amount of data that is available to IT admins, with no one perfect tool to help generate value out of it. Hence, the concerns with regard to taking a reactive approach towards employee demands, rather than being proactive.
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The inherent basis of progressing the workspace analysis procedure is simply the creation of an analysis idea, followed by the capability to follow it through with a flow of conscious decisions. This quality is sought after in particular by analysts, as it can be portrayed as an ideal quality: the ability to look at a particular segment and analytically ask questions, after which follow-up questions proceed in an unbroken stream. Often, this is not possible through means of traditional analytics reports. There are a few exceptions wherein a report can be broken down by another, but this is not always the case; they are limited in number. Additionally, this limitation is fueled by the capability of breaking the chain of thought, wherein instead of spending time mustering up a suitable follow-up question, analysts stumble upon the work that needs to be put into the tool in use, or even worse, add implementation items.
For instance, if you—as an analyst—would like to deduce the product that had the most orders for a particular month, the products report is simply opened, followed by the addition of an orders metric. Next, if the abnormal peaks in data have to be identified, the data must be exported to Excel, after which a standard deviation formula must be applied for the last few months. While this seems relatively achievable, exporting data and ensuring that the correct formulae for standard deviation must be given significance to, each time. This procedure becomes a tad bit monotonous and frustrating when the analysis must be performed on a weekly basis; this would involve conjuring a report builder, creating a data block and applying the standard deviation formulae on them, followed by its scheduling to be sent out on a weekly basis. As evidence, the procedure is just a tad bit cumbersome.
Apart from being bulky in nature, this procedure involves many manual steps when dealt with Excel, ReportBuilder, etc. At any particular instance, distraction may set in, breaking the train of thought. This is overcome by workspace analytics software, which is essentially built to be two-fold. Firstly, the tools are very user-friendly, and everything required is built into the same tool, so that jumping from one to another is not required. Secondly, the elements required for analysis are just a click away; it may feel as though you may be slowing down the tool.
Often analysts find this factor just a little frustrating. When there is a need to pull up a high-level report on the main KPIs of the site, and the analyst notices that they have 6 KPIs that they wish to see. The key metrics report does not permit the display of more than 5 metrics at a go. This leaves the analyst in a predicament: are two reports supposed to be published: one with five KPIs and another with one? While this split between the KPIs shouldn’t have any serious effects on the end result, it does often stand as an obstruction between being able to view them all together, whilst noticing the trend that occurs. Thanks to workspace analytics tools, you no longer have to restrict the metrics to 5.
Many tools such as Adobe Analytics create segments almost instantly. In fact, analysts who have some experience using similar tools will know that these segments are very common. With newer, better tools that are being offered in workspace analytics, such as Adobe Analysis Workspace, analysts can now spare seconds that would otherwise be lost in the process of creating segments. The best feature is that analysts never have to leave the same page they were working on earlier: everything occurs within the actual report. This is further beneficial in that fewer pages are being used for reports, which equates to lesser waiting time, and better analysis.
Let us take into consideration the Adobe Analytics Reports and Analytics. Here, the display options that pull up in a report are fairly limited: dimensions are visible on the left, wherein metrics appear on the right. With Analysis Workspace, as you need not leave the same page of the report, by aid of the premeditated metrics, analysts can now make two separate divisions and calculated metrics.
Abode Analytics, and many other tools are being worked on to combat challenges that are presented by the use of traditional reports and analytics. They will definitely make a giant leap in the workspace analytics arena with their attractive characteristics, and the primary goal of making the procedure of analysis easier on all.
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