MASTERS OF MACHINES II. Conquering complexity with operational intelligence

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1 MASTERS OF MACHINES II Conquering complexity with operational intelligence

2 2 Quocirca and Splunk Report 2015

3 CONTENTS MASTERS OF MACHINES II 4 EXECUTIVE SUMMARY 5 INTRODUCTION STRATEGIC CHANGE FOR IT MANAGEMENT 6 BIG DATA DRIVERS 8 PROCESSING MACHINE DATA 13 TOOLS OF THE TRADE 15 THE BENEFITS OF OPERATIONAL INTELLIGENCE 16 CONCLUSIONS 25 APPENDIX 1 RESEARCH NOTES AND CALCULATIONS 26 APPENDIX 2 REFERENCES 28 APPENDIX 3 DEMOGRAPHICS 28 ABOUT SPLUNK 31 ABOUT QUOCIRCA 32 3 Quocirca and Splunk Report 2015

4 MASTERS OF MACHINES II CONQUERING COMPLEXITY WITH OPERATIONAL INTELLIGENCE JUNE 2015 Many European businesses have been freed from the budgetary constraints that reigned following the financial crisis. For IT management teams this is leading to a strategic renaissance, enabling more focus on delivering better services and improving the customer experience. New research presented in this report shows how those in the vanguard are turning to operational intelligence to unlock the value buried in the many gigabytes or terabytes of machine data generated by their systems each day. Those organisations that make supporting investments are better able to cope with the inevitable increases in IT complexity and more intensive security measures that are needed to deliver improved services and the desired cross-channel experience for customers. Bob Tarzey Quocirca Ltd Tel: Clive Longbottom Quocirca Ltd Tel: Quocirca and Splunk Report 2015

5 EXECUTIVE SUMMARY CONQUERING COMPLEXITY WITH OPERATIONAL INTELLIGENCE New research shows how European IT management teams are using operational intelligence derived from machine data to better manage IT complexity and the cross-channel customer experience. This has to be achieved in the face of increasing security threats; concern about which has increased dramatically. CONCLUSIONS Cost concerns give way to other IT management issues Much value is locked up in big data Deep insight from machine data New research conducted in early 2015 shows that the top IT management concern is security and this has increased considerably since similar research was conducted in Other high and rising priorities for IT managers include avoiding downtime, keeping up with IT innovation and avoiding data chaos as overall volumes rise. The areas of concern that have fallen the most are all cost related; overpaying for software, underutilisation of hardware, and regulatory fines. Machine data, generated in huge volumes by core IT infrastructure, user devices, applications, and security products, can contribute to overall data chaos if unmanaged. The alternative is to use such data in real time to derive operational intelligence and provide management insight. This report focuses on three areas; IT complexity, reliance on the cross-channel experience and IT security. The research shows a clear correlation between the ability to collect and process machine data and effective operational intelligence. In turn, this reduces concerns in many areas. It provides the visibility needed to deal with IT complexity, in particular the hybridised delivery of public cloud and on-premise infrastructure and the agility to manage the cross-channel customer experience. There is a strategic shift in IT management enabled by the loosening of budgetary constraints in the postcrisis era. Many IT teams have shifted their focus to the customer experience as channels of communication become more complex, as do the supporting infrastructure and security requirements. Those best positioned to deal with this shift are gaining improved insight through operational intelligence derived from the huge volumes of machine data generated by their core infrastructure, user end points, and security products. Operational intelligence unlocks machine data The benefits of operational intelligence are manifold OI is a real eyeopener to security threats The ability to process machine data is the starting point; however, to unlock as much value as possible requires products designed to maximise the benefits of operational intelligence. Those who make the necessary investment collect the most machine data and see the greatest benefits. The delivery of effective operational intelligence is a true big data opportunity. As with the earlier 2013 research, Quocirca uses an index to measure operational intelligence capability and gauge its effectiveness. There are many clear positive correlations, including the ability to exploit and manage IT complexity, understand the business impact of IT issues, reduce system downtime, enable the cross-channel experience and understand user behaviour. In contrast to these positive effects, increased operational intelligence capability leads to higher concerns about IT security. The explanation for this is that those with insight into the threats faced by their organisation are alarmed by what they see. In other words, they are less complacent than those who lack such insight. 5 Quocirca and Splunk Report 2015

6 INTRODUCTION STRATEGIC CHANGE FOR IT MANAGEMENT In January 2014 Quocirca published a research report, Masters of Machines 1, which looked at the capability of European organisations to capture the machine data generated by their IT infrastructure, applications and security systems, use it to derive operational intelligence and provide insight into their commercial operations. The research was conducted in the second half of Figure 1: Average rating of top five IT management concerns SECURITY DOWNTIME 2.58 KEEPING UP WITH INNOVATION In 2015, some 18 months on, Quocirca has researched the area again, providing some new insights into the benefits of operational intelligence and looking at how views and capabilities have changed. The new results are included in this report along with some relevant comparisons with the 2013 research. DATA CHAOS OVER INVESTMENT OVERPRICED SOFTWARE An aspect of the research, not reported in Master of Machines, was the main concerns with regard to IT management. 18 months may not seem that long, however, it is clear that there has been a positive change in the strategic priorities of IT managers (Figure 1). OUR INNOVATION TO SLOW REGULATORY FINES POOR CUSTOMER EXPERIENCE Quocirca and Splunk Report Respondents were asked to select their top 5 out of 11 concerns in order. See Appendix 1 UNDERUTILISED HARDWARE INFLEXIBLE IT MONITORING

7 Concern about finance related issues has dropped away (Figure 2) including; overpaying for software licences, underutilisation of hardware assets and regulatory fines incurred through IT-related compliance failure. This reflects the fact that budgets are not as tight as they were due to continued improvement in the economic conditions in Europe. The result is a renaissance for IT managers as, less constrained by cost, they find themselves freer to focus on delivering value to the business. In particular, this includes the ability to support increasingly complex business processes and communications and manage the supporting hybrid infrastructure and additional security. Figure 2: Change in average rating of top five IT management concerns between 2013 and 2015 SECURITY INFLEXIBLE IT MONITORING DATA CHAOS POOR CUSTOMER EXPERIENCE OVER INVESTMENT DOWNTIME CONCERN INCREASED SINCE 2013 This report will focus on these three areas of strategic focus for IT management; IT complexity, the cross channel customer experience and IT security. It will look at how these relate to overall changing IT management priorities and how operational intelligence derived from machine data helps reduce concerns or, in the case of IT security, throws worrying light on the issue. CONCERN DECREASED SINCE OUR INNOVATION TO SLOW KEEPING UP WITH INNOVATION REGULATORY FINES UNDERUTILISED HARDWARE OVERPRICED SOFTWARE 7 Quocirca and Splunk Report 2015

8 BIG DATA DRIVERS The three areas focussed on in this report, which can benefit from operational intelligence derived from machine data IT complexity, the cross channel customer experience and IT security can all be considered big data drivers. That is, they all lead to increased volumes of machine data, with many differing formats. More IT complexity means more systems generating more data. More channels of communication mean more devices, more networks and more data. The changing threat landscape means more security products that also generate more data. Obviously all this may just contribute to growing concerns about data chaos. However, all this machine data is also a big data opportunity waiting to be exploited. The research presented in this report will show where the opportunity lies and the benefits gained by those that have the foresight to seize the opportunity. IT COMPLEXITY growing complexity of IT systems as organisations struggle to keep pace with IT innovation, which remains high on the list even though it has dropped a little. This includes the cloud, big data, the internet-of-things (IoT), DevOps (software development and operations) and mobility. In particular, the increasing use of cloud services adds to IT infrastructure complexity as systems are becoming more hybridised and organisations struggle to get equal insight Figure 3: Changing methods of EITHER PRIMARY OR IT deployment SECONDARY MEANS OF DEPLOYMENT PAAS AND/OR IAAS IN-HOUSE DATA CENTRE 90.3% 85.5% 77.6% into both on-premise and cloudbased infrastructure. In individual organisations, public cloud services are usually introduced gradually, so they need managing alongside legacy infrastructure (often re-provisioned as private cloud to facilitate integration). Just 5% report having no data centres at all, presumably relying completely on cloud services, up from 4% in Overall, the use of infrastructure and/ or platform-as-a-service (IaaS/PaaS) is up 10% since 2013 and there has been 66.6% 8 Quocirca and Splunk Report 2015 The downtime of IT systems remains the second greatest concern after IT security for IT managers. IT security failures contribute to this, for example due to the increasing occurrence and size of denial of service attacks. Another contributory issue is the SAAS CO-LOCATION DATA CENTRE 73.2% 74.5% 76.1% 63.9%

9 a commensurate decrease in the use of dedicated data centres (Figure 3). The drop in the use of co-location services is probably due to a net move from third party data centres to third party infrastructure services. In other words, many of the applications on which businesses rely still run in co-located data centres but, increasingly, this is on IaaS or PaaS platforms provided by cloud services providers (many of which also use colocation services) rather than an organisation s own hardware. The use of cloud services provides Figure 4: IT infrastructure complexity flexibility, efficiency and economy almost 88% are saying they are now using SaaS and/or IaaS/PaaS, up from 82% in Those who find themselves managing an in-house data centre and a remote co-location facility alongside use of both IaaS/PaaS and SaaS deployments have a complex overall environment to monitor. Whereas an organisation that still does everything in its own in-house data centre or one that has moved SECTORS 2015 everything to the platform of a single IT infrastructure provider has a relatively simple environment to monitor. On this basis a crude measure of IT operating complexity can be used, scoring an organisation from 1 to 4 depending on how many of the following they have to manage: in-house data centre, colocation facility, IaaS/PaaS and SaaS (see Appendix 1). Figure 4 shows where organisations lie on this scale overall in 2015 compared to 2013 and by industry in IT INFRASTRUCTURE COMPLEXITY Use of one or more of: In-house data centre Co-location facility IaaS/PaaS and/or SaaS OVERALL TELCO GAMING RDT 9% 10% 8% 20% 20% 20% 30% 5% FINANCE 6% 16% MANUFACTURING 14% 21% COMMERCIAL 11% 27% Number of IT deployment types ONE TWO 31% 25% 28% 36% 28% 32% 9 Quocirca and Splunk Report 2015 THREE FOUR 40% 60% 50% 44% 42% 36% 31%

10 THE CROSS-CHANNEL CUSTOMER EXPERIENCE With the lessening of budgetary constraints many IT management teams have chosen to shift their strategic focus to better supporting customers. In many cases this involves improving the cross-channel customer experience (sometimes called the omni-channel). More complex communication channels also increases the amount of machine data generated. This, alongside IT complexity, if poorly managed, contributes to data chaos (the inability to make operational use of data in real time) and rising concerns about a poor customer experience. This area was not investigated in 2013; however, other sources 2 show how smartphones and social media have now become core channels for interacting with outsiders. Figure 5 shows social media to be almost as important as face-to-face communications as a medium for interaction. In some cases, users are not directly involved or not involved at all. Sensorbased devices may be the least used channel, but their importance rises in certain industries (Figure 6). This is most notable in manufacturing where much of this will be monitoring plant equipment. Second on the list is RDT (retail, distribution and transport) where sensors may be used in areas such as the counting of passenger movements. Figure 5: How important are the following ways of transacting with external users? Figure 6: Importance of sensor-based devices SECTOR WEB SITE VIA PC/TABLET VOICE/ TELEPHONE WEB SITE VIA SMARTPHONE MOBILE APPS FACE-TO-FACE SOCIAL MEDIA SENSOR-BASED DEVICES OVERALL MANUFACTURING RDT TELCO GAMING COMMERCIAL FINANCE Labels for Figure 5 and Figure 6 NOT IMPORTANT AT ALL NOT THAT IMPORTANT QUITE IMPORTANT VERY IMPORTANT 6% 8% 33% 53% 7% 18% 39% 5% 23% 42% 7% 26% 46% 14% 24% 33% 12% 29% 38% 18% 27% 32% 23% 32% 27% 14% 26% 28% 25% 28% 31% 20% 35% 30% 20% 35% 30% 24% 33% 27% 32% 39% 10 Quocirca and Splunk Report % 30% 21% 29% 20% 23% 18% 32% 16% 15% 15% 16% 22% 7%

11 Third are telecoms companies (telcos), where device-to-device communications may be being logged. The use of millions of sensors and a wide range of other devices is the basis of the internet-of-things (IoT). Machines are not slowed down by keyboards, touchscreens and mice and can chatter away to each other at very high speeds, generating huge volumes of machine data with the capability to provide deeper and more pervasive insight into IT and business operations. Figure 7: Reliance on the cross-channel experience by industry SECTOR This proliferation of devices also vastly increases the attack surface of any organisation s IT infrastructure, which adds to security concerns. Managing the cross-channel experience has become a necessity for effective online engagement. Organisations can be categorised as having a high, medium, or low reliance on the cross-channel experience (Figure 7). This reliance raises concerns in other areas; for example, those with a high score are almost twice as likely to be concerned about regulatory fines incurred through IT-related compliance failure. However, the more channels of communication a given organisation embraces, the more online commercial transactions its IT infrastructure drives (Figure 8). These daily volumes scale up to tens of millions of online commercial transactions per year for many companies. Each transaction generates many other data records, not least machine data. Figure 8: Transaction volumes by reliance on the cross-channel experience Calculated based on the number of channels a given organisation uses to communicate with outsiders (See Appendix 1) LOW MEDIUM HIGH RDT = RETAIL, DISTRIBUTION AND TRANSPORT 11 Quocirca and Splunk Report 2015 OVERALL 33% 31% 37% TELCO 25% 30% 45% FINANCE 31% 25% 45% MANUFACTURING 36% 21% 42% RDT 29% 38% 33% COMMERCIAL 38% 35% 27% GAMING 30% 45% 25% RELIANCE ON CROSS-CHANNEL EXPERIENCE LOW 24,520 MEDIUM 32,534 HIGH 40,658 40,000 30,000 20,000 10,000 0 AVERAGE DAILY ONLINE TRANSACTION VOLUMES

12 IT SECURITY The biggest IT management concern in both 2013 and 2015, and the one that increased the most in the intervening period by almost 25% was security threats through compromise of IT systems. The rise is driven by an increase both in the number selecting security as an increasing concern and the number selecting it as their top concern (Figure 9). IT complexity and high reliance on the cross-channel experience are both contributory factors to this and both can be impacted by security failures. Attacks are becoming more ingenious; more software vulnerabilities are being found and exploited; more access credentials are being compromised, including high value ones with privilege, which allow hackers to pose as legitimate users. Concern about the accidental and malicious actions of insiders is also rising. Traditional approaches to security are not good enough as another Quocirca research report has shown 2. That the rise in concern about security is so large, whilst the concern about regulatory fines has fallen, suggests that, even in Europe, with tougher data protection laws imminent, the worry is more about the security threat itself than regulatory compliance. Data chaos, the 4th biggest concern and 3rd biggest riser, makes data breaches more likely and, at the same time, less likely to be noticed. Security products themselves are big generators of machine data, the management of which has seen the growth of a whole industry around security information and event management (SIEM). However, all data is relevant to security; effective SIEM needs to use a broader range of sources beyond just security products to provide effective contextaware security, for example logs from applications provide a rich source of information regarding legitimate and illegitimate user activity. Figure 9: Change in rating of concern about: security threats through compromise of IT systems Labels for Figure 9 TOP CONCERN % 14% 12% 9% 9% 28% 2ND 3RD 4TH % 14% 12% 6% 4% 44% 5TH NOT SELECTED 12 Quocirca and Splunk Report 2015

13 PROCESSING MACHINE DATA For this survey machine data was defined as: Data from logs, configuration files, clickstream data, change events, alerts, scripts and metrics generated by servers, routers, user end-points, virtual machines, physical security devices, sensors, websites, mobile devices and the internet of things. Machine data is generated by all of the systems and infrastructure that drive a business More complex IT, high reliance on the cross-channel experience and more intensive IT security all increase the volume of machine data generated in a given organisation. The ability to collect, process and analyse such data lies at the heart of effective operational intelligence. The failure to do so is a lost opportunity and simply adds to the data chaos problem. Many organisations now successfully process many terabytes of machine Figure 10: Volumes of machine data gathered from various sources data per day. Such volumes make it a true big data opportunity; the oftencited five Vs can be readily identified: There are large volumes of machine data driven by IT and security infrastructure and the online activity of both users/ customers and devices The machine data comes from a wide variety of sources and in a variety of formats (IT complexity) Machine data arrives, and can be acted on, in real time (velocity) A lot of value can be derived from machine data Effective analysis (operational intelligence) uncovers the truth (veracity) about the state of IT systems, the applications they drive and the commercial health of an organisation Respondents rated their ability to collect machine data from eleven different sources (Figure 10). Not all of USER-OWNED MOBILE DEVICES MOBILE APPS USED BY CUSTOMERS MOBILE NETWORK INFRASTRUCTURE SOFTWARE SENSORS REAL TIME STREAMING WIRE DATA HARDWARE SENSORS HOSTED INFRASTRUCTURE EXTERNAL NETWORK INFRASTRUCTURE COMMERCIAL WEB SITES INTERNAL IT INFRASTRUCTURE APPLICATION LOG DATA Labels for Figure 10 ALL 22% 23% 27% 26% 27% 31% 32% 34% 36% 32% 36% MOST SOME VERY LITTLE NONE 13 Quocirca and Splunk Report % 36% 32% 27% 26% 25% 18% 15% 16% 41% 19% 12% 30% 25% 16% 38% 35% 35% 39% 34% 21% 21% 18% 15% 17% 8% 10% 9% 9% 42% 13%

14 these sources will be relevant to all organisations; however, the more that are involved, the bigger the challenge of collecting it. However, the more data collected, the greater the potential rewards. The overall capability to collect machine data can be quantified. Any organisation that collected all data from all eleven sources would score 100%, any collecting none from any would score 0% (see Appendix 1). By this measure the average organisation collects just under 48% of all the potential machine data available; the range is from a low of 0% to a high of almost 80%. Clearly many organisations are not fully exploiting the potential. Those with the greatest IT complexity collect more (Figure 11). This will be partly because they have more sources to gather it from in the first place, but also because machine data helps to provide the insight that enables them to effectively manage and benefit from hybridised IT infrastructure. The most widely collected types of machine data, from applications, web sites and networks, are also some of the best sources for implementing contextaware security to help take measures against advanced attacks and malicious insiders. Figure 11: IT complexity and the collection of machine data IT INFRASTRUCTURE COMPLEXITY LEVEL ONE 33% LEVEL TWO 42% LEVEL THREE 47% LEVEL FOUR 56% OVERALL 48% 60% 50% 40% 30% 20% 10% PERCENTAGE OF MACHINE DATA COLLECTED 14 Quocirca and Splunk Report %

15 TOOLS OF THE TRADE Those with more complex IT infrastructure are also more likely to have already deployed operational intelligence tools (Figure 12). It is also clear that the ability to collect machine data and the use of operational intelligence tools go hand-in-hand (Figure 13). However, overall deployment levels are still low and it would seem that for many organisations the value of operational intelligence is not being realised. The good news is that barriers to entry are dropping as such tools are becoming available as cloud services and what was considered an enterprise management capability is opening up to smaller businesses. Figure 12: IT complexity and use of operational intelligence tools Deployment of operational intelligence tools ALREADY USE PLANNING TO USE NO PLANS/ DON T KNOW IT INFRASTRUCTURE COMPLEXITY ONE TWO THREE FOUR OVERALL 19% 27% 31% 41% 33% 17% 21% 35% 30% 34% 64% 52% 34% 37% 24% 15 Quocirca and Splunk Report 2015 On-demand tools also make operational intelligence available to the small but growing band of organisations that rely purely on cloud infrastructure and applications. Hybrid approaches to operational intelligence are possible too, with elements of the processing of machine data carried out on-premise and some in the cloud. Figure 13: Volume of machine data collected and the use of operational intelligence tools PERCENTAGE OF MACHINE DATA COLLECTED LESS THAN 30% 25.4% 30% TO 45% 45% TO 55% 30% 27.7% 55% TO 65% 38.4% MORE THAN 65% 47.6% OVERALL 33.2%

16 THE BENEFITS OF OPERATIONAL INTELLIGENCE Operational intelligence, as defined for the survey respondents, is: TABLE 1: THE FOUR STAGES OF OPERATIONAL INTELLIGENCE MATURITY 16 Quocirca and Splunk Report 2015 The ability to harness machine data to gain real-time insights into operations; to assess, tune and improve IT and business processes and to identify security threats, highlight performance issues and see emerging business trends Quocirca has developed an index to help gauge the impact operational intelligence has on all of the IT management concerns and big data drivers that have been outlined earlier; IT complexity, cross-channel experience and IT security. The index is based on 12 operational intelligence capabilities grouped into four areas listed in Table 1. The way machine data is collected and turned into operational intelligence progresses from IT-focussed root cause analysis to real time business insights. Most organisations start at stage one and mature over time through stages 2, 3 and finally 4. The degree to which they achieved this can be thought of as their operational intelligence maturity and is expressed in this report as the operational intelligence index. 1: Search and investigate: 1A Capture, store, and search machine data 1B Search and find the root cause of important events 1C Analyse machine data to find the root cause of important events 2: Proactive monitoring: 2A Analyse machine data to notice and manage exceptions before they impact users or service delivery 2B Use machine data in real time to make decisions about tuning IT systems 2C Use machine data to provide the business insight it would not otherwise have 3: Operational visibility: 3A Use machine data to measure service levels and key performance indicators to better serve the business 3B Use machine data to gain end-to-end visibility of consumer behaviour and business performance 3C Examine machine data for general intelligence about the business, customers etc. that would not otherwise be available 4: Real-time business insights: 4A Correlate machine data with business data to provide real-time insight for tuning business processes 4B Use real-time analytics from machine data to detect patterns, identify trends, and predict outcomes (e.g. for capacity planning and fraud detection) 4C Provide the business views from machine data analysis that drive real-time decision-making and innovation (customer insights, marketing insights, usage insights, product-centric insights)

17 Figure 14 shows the average range of capabilities reported and Figure 15 shows the range of scores and the categories of operational intelligence capability used in the on-going analysis from very low to maximum. The 2013 data was analysed and reported in the same way, allowing comparisons. As with operational intelligence tools, there is a clear link between high index scores and the amount of machine data collected (Figure 16). The use of operational intelligence tools is, unsurprisingly, an even greater differentiator (Figure 17). 75% of those with a maximum index score have such tools in place compared to less than 12% of those with a minimum score (some may have recently deployed and are yet to realise the full potentials of their investment). There is also a clear relationship between the index and areas this report has focussed on; IT infrastructure, customer service and IT security. Figure 14: Please rate your organisation s ability to do the following (see Table 1 for key) 1A 1B 1C 2A 2B 2C 3A 3B 3C 4A 4B 4C NO CAPABILITY POOR CAPABILITY SOME CAPABILITY 3.7% 5.5% 2.9% 17.9% 22.4% 24.7% 8.2% 8.2% 10.3% 22.4% 26.8% 21.3% 6.3% 20.8% 10.0% 9.7% 9.2% 11.1% 9.7% 25.5% 23.4% 29.7% 24.5% 25.3% ALREADY HAVE A STRONG CAPABILITY 41.3% 50.8% 48.7% 45.0% 44.7% 47.1% 47.4% 46.1% 45.0% 42.4% 45.8% 44.5% 17 Quocirca and Splunk Report % 23.2% 21.1% 24.5% 20.3% 21.3% 25.5% 18.4% 21.8% 18.7% 18.7% 20.5%

18 AVERAGE ACROSS ALL 12 ISSUES IN TABLE 1 WHERE: 3 = STRONG CAPABILITY 2 = SOME CAPABILITY, WOULD LIKE TO IMPROVE Figure 15: Operational intelligence maturity index showing ranges used in analysis 3 RANGE OF VALUES ACROSS ALL 380 ORGANISATIONS SURVEYED 2 MAXIMUM (3) 1 = POOR CAPABILITY 0 = NO CAPABILITY 1 VERY LOW (<1) MEDIUM (1.5 TO 2.2) HIGH (2.2 TO 2.9) LOW (1 TO 1.5) 18 Quocirca and Splunk Report Figure 16: The relationship between collecting machine data and operational intelligence PERCENTAGE OF MACHINE DATA COLLECTED OPERATIONAL INTELLIGENCE INDEX <30% % TO 45% % TO 55% % TO 65% 2.15 >65% OVERALL Figure 17: Operational intelligence index and the use of operational intelligence tools OPERATIONAL INTELLIGENCE INDEX % 1.83 PERCENTAGE USING OPERATIONAL INTELLIGENCE TOOLS 80% 60% 40% 20% VERY LOW 7.7% LOW 19.4% MEDIUM 33.5% HIGH 48.0% MAXIMUM OVERALL 33.2%

19 DEALING WITH IT INFRASTRUCTURE COMPLEXITY The index increases with complexity (Figure 18). In other words, as organisations move to more heterogeneous and complex IT platforms, they are turning to operational intelligence to provide the necessary management insight. GAUGING THE IMPACT OF IT ON THE BUSINESS As all organisations become more reliant on IT, it is necessary to understand the impact performance issues and failures have on business. The research shows that operational intelligence has the greatest impact on improving management capability and insight in the strategic focus area of improving the customer experience. Overall, in more mature areas such as network performance and onpremise services levels (provided by the IT function), organisations report the highest levels of insight, although, overall, the situation looks less than satisfactory (Figure 19). Insight is lowest Labels for Figure 19 NONE AT ALL VERY LITTLE MODERATE IN-DEPTH 19 Quocirca and Splunk Report 2015 Figure 18: IT infrastructure complexity and operational intelligence index COMPLEXITY SCORE OPERATIONAL INTELLIGENCE INDEX ONE TWO 1.46 THREE FOUR 2.16 OVERALL Figure 19: Insight into how technology issues impact business performance Network Performance System Downtime On-Premise Service Levels Troubleshooting /Incident Investigation Online Application Performance Online Customer Experience Website Performance 4% 6% 6% 3% 2% 8% 3% 14% 16% 18% 19% 22% 23% 21% 44% 41% 39% 41% 48% 48% 31% 29% 45% 47% 27% 24% 42% Cloud Service Level 22% 43% 28% 26% Transaction Path Through Infrastructure 9% 12% 26% 39% Mobile App Performance 12% 31% 34% 23% 23%

20 when it comes to bleeding-edge issues like mobile app performance, understanding transaction paths through complex infrastructure and cloud service levels. However, it is at this end of the scale that effective operational intelligence makes the most difference (Figure 20). One issue stands out, system downtime. This was the issue where organisations were most likely to say they had in-depth insight, but also the one where operational intelligence improved insight the most. Figure 20: Insight into business impact of technology and operational intelligence index IN-DEPTH NETWORK PERFORMANCE SYSTEM DOWNTIME TRANSACTION PATHS MOBILE APP PERFORMANCE MODERATE VERY LITTLE NONE OPERATIONAL INTELLIGENCE INDEX Quocirca and Splunk Report 2015

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