ANALYTICS: THE SMARTEST PATH TO SMARTER IT. Why it s Time to Upgrade from Reporting to Analytics

Transcription

1 ANALYTICS: THE SMARTEST PATH TO SMARTER IT Why it s Time to Upgrade from Reporting to Analytics

2 INTRODUCTION When it comes to financial investments, many find themselves obsessively checking market indexes and stock prices on a daily or even hourly basis. Following rising and falling prices and trends is certainly useful but only up to a point. These numbers don t tell you whether the stock is over or undervalued, if you should consider selling or buying more stock, or if you should diversify your portfolio. You only get that information by consuming deeper analysis that combines knowledge about industries and people. That deep analysis tells you what you really need to know in order to materially change your investment returns. Similarly, for IT service managers, simply generating reports on trouble tickets or backlogs the indexes of IT processes is not actionable without the accompanying insights. Along with the what, they must have the why, or they won t have the knowledge necessary to make more informed decisions. Additionally, generating even these basic reports represent a significant time investment. Reports and KPIs do add value to the business and are often the first step in a business s journey to a smarter IT organization. For instance, it s good to know how many tickets were opened in the past 24 hours, but reports leave much unsaid - like why those tickets were opened and whether that number is much higher compared to the average for the same day last week or past several weeks. Analytics can illustrate how to connect the dots among data sources, which ultimately helps improve IT service delivery and boosts customer satisfaction. Here s how to understand the difference between reporting and analytics applications, and the distinct roles they each play in improving IT service. Inadequate training for this group is resulting in a rising backlog

3 There s a lot of data in reports, but no knowledge. I can t really act on anything. Paul Mitchell VP IT Service Management, PGI 1. OBJECTIVES Reporting provides a snapshot of what s happening in IT operations right at that moment, like the number of trouble tickets opened in the past hour. This makes it easy to keep track of incidents as they occur. On the other hand, analytics role is to show why there is a sharp spike in trouble tickets or why incidents keep recurring. Analytics can identify patterns within the data, as well as deviations that may shed light on why service is not as efficient as it could be. In addition, analytics can play a part in predicting future trends, which helps IT plan for growth. In reporting and KPI tools, the type of questions that can be answered is limited by data versatility, computational power, and mathematical capabilities. You might be able to determine How many incidents were open in the past seven days by priority and category? But with analytics, you can answer more sophisticated questions - For instance, How many incidents opened in the last week missed the SLAs? Is there one assignment group that stands out? or How does this compare with the previous week as well as the historical average SLA by category?

4 2. DATA VERSATILITY Reporting and KPI Tools usually rely on a single data source, and often just a single table within an area. On the other hand, analytics solutions bring multiple data sources together with high granularity. The ability to compare results across data sources allows IT service managers to see correlations and make observations that are otherwise hidden from them. As an example, one university brings in data related to student enrollment and compares the data against service requests. By doing so, their IT managers can understand how increasing enrollment and implementing new policies such as supporting BYOD, will impact IT service demand. In another case, a company wanted to see total open work across all tasks by staff member. By seeing how loaded individuals are across incidents, changes, service requests, and project tasks, the company can evaluate when staff is overwhelmed with support work and how it impacts their ability to complete their project tasks.

5 Welcome, Brian 3. FUNCTIONAL CAPABILITIES Reporting is typically limited to just a couple of information display capabilities - simple reports and dashboards in a handful of formats like line, bar, or pie charts. By comparison, a comprehensive analytics solution provides a continuous iterative exploration offering the capabilities of reporting and more: Full visual data exploration: Drag-and-drop tools allows data to be sliced and diced as needed to pursue different avenues of analysis. This is called future-proofing analytical needs, where there is the ability to ask the questions that haven t been thought of yet, without having to set up new tables or data extraction routines. With ad-hoc analyses, a new data collection process doesn t need to be set up every time a new question is asked. Mobile Accessibility: The world is increasingly becoming mobile, and tablets and smartphones are perfect devices for information consumption. A rich analytics application can be easily accessed on tablets or smartphones so insights can be pulled up from anywhere. alerts: Instead of IT service managers having to monitor data, alerts deliver snapshots of IT performance as needed based on certain threshold conditions, and are easily shareable with other team members. For example, if the percent SLA met for incidents drops below 90% for any given assignment group, key stakeholders should receive an with all incidents that have breached SLAs, as well as those that are about to breach within the next 24 hours.

6 4. COMPUTATIONAL POWER In operational reporting, data is typically stored on flat tables with data reports only running on that table. By storing simple Key Performance Indicators (KPIs), scorecarding tools provide simple data to be presented. Real-time reporting can provide direct access to an operational system. In both cases, only a small sliver of data, like the data that has been generated in the last 24 to 48 hours. Pulling in any more than just that bit in real time from an operational system can severely impact operational performance. Hence, the need for a robust data warehouse. Robust analytic solutions store data in a specialized data store, such as multi-dimensional data warehouses or in-memory cube, or in the case of extremely high-volume data in a Hadoop or Spark store. The purpose in all cases is the same - to power a range of advanced analytical queries without crippling the underlying operational applications. The architecture of the data storage drives the analyses, similar to how the engine of the car determines the maximum speed, pickup, and overall capacity to carry load. 5. MATHEMATICAL SOPHISTICATION Reporting solutions are usually limited to simple metrics such as sum, average, count, and percent changes for sequential numbers. However, analytics allows performance of advanced calculations such as day-over-day change by weekday, ranking, percentile, forecasts, predictive and text analytics. To give an example, one IT manager wanted to understand the demand for calls in their company s IT call center presented as an average for the day of the week for the past rolling six weeks. So, all Mondays would be averaged, as would all Tuesdays, and so on. This reflection of weekday seasonality was important so that the company could understand how to staff its call center on Mondays at 10 am versus how to staff its call center on Wednesdays at 4 pm.

7 SUMMARY Given the data, mathematical and functional versatility that they provide, it is no wonder that true analytic applications can be far more valuable and insightful than reporting systems. Various business leaders across sales, marketing and finance have already borne the fruit of analytic applications over the last several years. It is now IT s turn to get the same power and stop compromising with reporting or KPI tools. Enterprise IT represents a significant amount of spend within an organization. Likewise, the impact of greater intelligence on the quality and efficiency of the IT services you deliver to your customers is real. When you re playing the stocks with spare cash, a ticker might suffice. But when you re managing a fund on which your entire business depends, it s time to upgrade. VISUALIZATIONS DATA SOURCES METRICS DELIVERY AD HOC Real Analytics RICH & SOPHISTICATED MANY COMPREHENSIVE PRE-BUILT APP AT WILL INQUIRY KPI Tools & Scorecarding SIMPLE SINGLE MEDIUM-RANGE BUILD YOURSELF REQUEST & WAIT Operational Reporting SIMPLE SINGLE BASIC BUILD YOURSELF REQUEST & WAIT For more information about IT Business Analytics, visit numerify.com