managing remote offices tracking of key metrics

ISSUE PAPER Managing Remote Offices Best Practices and Outcomes By John E. Burke, Principal Research Analyst, Cisco Research Executive Summary Managing delivery of services to, and support of users in remote offices is a critical issue facing IT, especially as the number of branches IT supports continues to grow by nearly 9% per year. Pursuing best practices aimed at directly assessing the performance of enterprise applications or setting network performance targets for remote sites are not sufficient to ensure success, and in fact tends to make enterprises assess their efforts as less successful when compared to sites that follow these practices. This does not indicate more effective delivery of services at the sites without direct measurement of performance against specific goals, but rather illustrates the lack of information there about actual performance. Making the best choices about support models and sourcing affects critical success factors such as the amount of time it takes to handle problems, and requires tracking of key metrics such as the amount of central IT staff time required to support remote users. Placing staff on- site in remote locations can reduce central staff time investment and minimizes overall time spent moving from report to resolution of problems. The Issue Managing branch offices is one of the largest challenges IT faces today, for several reasons, chief among them distance and growth. First and foremost, there is the simple fact of distance – managing a remote site is always more difficult. Even sites that have their own IT support staffs can’t have the breadth or depth of support of main locations. As soon as staff have to be sent out from a central to a remote location, travel expenses, time lost to travel, and the difficulty of dropping IT staff into a problem situation are all along for the ride, and they constitute the main objection to using a fully centralized model for support. Adding to the inherent difficulties of supporting a site distant from core staff and prime resources is the steady growth in the number of remote sites needing support. Cisco’ research shows that, on average, the number of branch offices is growing by 8.9% annually. Industries expecting growth well above that average include energy (18%), financial services (16%), and healthcare (13%). Other sectors are expanding more slowly than the average, including manufacturing (7%), education (7%), and pharmaceuticals (6%). Some few are even expecting zero or negative growth, including state/local government, non-profit organizations, and transportation. To complicate the picture further, in some cases organizations are reducing the number of small branch offices they run but replacing them with telecommuter sites. This results in a large net gain in locations to which enterprise resources must be available and from which performance must be acceptable – but which have no IT support staff nor any possible. Businesses are branching out this way for several compelling reasons: ? Reducing facilities costs. By locating branch-offices in suburban or rural areas, businesses reduce lease, rental, and property purchase outlays as well as taxes of all sorts. The typical facilities cost for supporting an employee goes down by 50% or more in the move from a major metropolitan area to a suburban or rural location, and approaches zero for home workers. ? Reducing personnel costs associated with turnover or relocation. By allowing people to stay in one place even if offices close or move, they remove the need for staff to choose between moving to keep a job or staying put to keep a home and community. By creating a virtual workplace, with organizational structure detached from geography, these businesses also save themselves the $40,000 to $55,000 average cost of replacing or relocating an employee. ? Attracting the right people. By eliminating the “location” barrier, employers can hire the right person for the job, which provides a competitive advantage when it comes to recruiting and retaining personnel. One large healthcare organization with which Cisco works closely found its ability to attract nurses—skilled professionals in high demand—increased dramatically when it moved to a virtual worker model. ? Closing the gaps. Placing or keeping staff in closer proximity to customers and partners improves customer services and maintains or improves a company’s local “presence.” So, business is in a dispersive mode and the problems of managing and supporting remote offices are becoming steadily more significant. The issue, then, is what IT can do to improve its chances of meeting or exceeding customer requirements for application availability and performance. What Seems to be the Problem? End-users view the world of IT largely in term of the applications they use, or the services that the company data center(s) provide. They might say “the network is down”, or “Outlook is causing trouble”, but when pressed are really saying something about whether or not they are receiving email – something which might have nothing to do with either the network or Outlook. When Cisco asked research participants recently what the actual root causes of problems in remote sites were, the answers were applications and servers 50% of the time, networks 36% of the time, and “human error,” as in someone kicking a plug out of a wall, the remaining 14%. In fact, we expect that service issues tied to network problems will increase as voice/data convergence projects continue. When companies put more, and more demanding, applications on a network, those applications necessarily compete for the network’s prime, shared resource—bandwidth. Setting targets In research for the benchmark study Delivering the Enterprise: Service Delivery and Management, Cisco discussed with participants whether they set performance targets for remote locations according to what kind of location they were (including size, location, and WAN connectivity), and their business criticality. Setting such targets is generally considered a best practice, as it carefully matches resources to needs and allows for the tracking of performance against promised service level. We expected that the practice would be widespread and that it would be associated with higher rates of successful service delivery and management. Both expectations were incorrect. In fact, fewer than 1 in 3 participants had such targets in place. (Please see Figure 1, "Performance Targets," p. 4.). Moreover, when we compared the success of enterprise application delivery management (as rated by the participants1) to whether those enterprises set such targets we get another surprise: on average, those without targets rate themselves “successful” while those with targets only muster a “somewhat successful” evaluation. (Please see Figure 2, "Success and Use of Performance Targets," p. 4.) Should we be surprised? Probably not. Setting and tracking performance targets forces an IT shop to really understand what is going on, how good the services they provide truly are, and it is this greater and more accurate knowledge that lies at the root of their lower ratings for success. These shops have removed a certain level of optimism and ignorance from their operations, but have a somewhat less flattering perception of the performance as a result. (Certainly it is possible that setting such targets does in some way affect an organizations ability to execute, perhaps by laying on too much overhead, but it seems unlikely and we saw no evidence of it.) 1 Participants rated their efforts in delivering enterprise services, with one being “unsuccessful,” two meaning “of limited success,”, three meaning “somewhat successful,” four meaning “successful,” and five meaning “highly successful.” Figure 1: Performance Targets Figure 2: Success and Use of Performance Targets If we take the participant pool apart by size (as measured in annual revenues) we do uncover one stratum on which the expected relationship holds: for very large companies, with annual revenues above $6.5 billion. At that level, those who use performance targets are slightly more successful (3.3 mean success score) than those who do not (mean of 3). Setting Baselines Participant responses showed a similar pattern on the question of whether they performed regular baseline assessments of application performance over their networks and how successful baseline-setting organizations are. Although still a minority practice among participants, a solid plurality (43.6%) said yes, they do perform regular baseline assessments. (Please see Figure 3, "Baseline Application Performance," p. 6.) A further 23.1% said they did baselines, but not regularly. A full third, though, said they never did such baselines. When these responses are compared with success ratings, we see that those who do not do such baselines rate themselves as “successful” while those who do the assessments rate themselves as only “somewhat successful.” (Please see Figure 4, "Baseline-setting and Success," p. 6.) Again, we see this is as a reflection of the more accurate information. Lack of the very information that such baselines can provide allows the organizations not doing them to rate themselves as more successful. Those who do only occasional benchmarks seem to get the worst of both worlds: incomplete information and a lower rate of success. Splitting the participants by size again, the expected relationship does emerge in the smallest companies (up to $300M in revenues), where those who do regular baselines are more successful (mean score 4.5) than those who only sometimes do so (3.7) and those who don’t ever (mean of 4). In the large companies, with revenues above $6.5 billion, those who only sometimes do baseline-setting come out on top, with a mean success score of 4 as compared to those who regularly baseline (score 3) and those who don’t (score 3.5). Irregular baseline-setting is also the best strategy for the medium to large companies, with revenues between $1.8 billion and $6.5 billion, although only barely. In that size range, IT departments following that plan scored themselves at 4, those with regular assessments at 3.8, and those doing no baseline-setting at 3.5. Figure 3: Baseline Application Performance Figure 4: Baseline-setting and Success Assessing the User Experience of Performance Setting performance targets for sites and doing baselines for application performance are aimed at indirectly guaranteeing that users will have adequate performance on critical IT applications and services. With the user’s experience of IT services as the primary yardstick by which those users (and ultimately the corporation, in many cases) measure how well IT is doing, how often do IT organizations directly assess that experience? Cisco has found that almost two-thirds (64%) do not directly assess it at all! (Please see Figure 5, "Assess Performance from User Perspective," p. 8.) For 41%, indirect assessment via surveys, occasional meetings with business line folks, and/or help-ticket follow-up questionnaires suffices instead. Another 17.9% do no assessment of any sort, and 5.1% watch the infrastructure at the edges of the network instead of peeking at desktops or application performance on them. Most of the participants in this 64% did express a wish to do such testing, but said their IT organizations either were not ready to do it, lacked the tools, or faced too complex an environment to make such monitoring practical. The 35.9% of companies that do directly assess performance at the desktop are split between those who do it regularly (20.5%) and those who do it but not at regular intervals (15.4%). These shops used a variety of types of tools, from built-in or other agent reporting on performance factors on the desktop to synthetic transactions played across the network by appliances placed at the network’s edge to simulate a user’s activities. And how does direct assessment of performance at the desktop line up with success in application delivery? As before, the strategy that provides the most information leads to lower estimates of overall success – regular, direct assessment of performance at the user level and from the user perspective is associated with only “somewhat successful” outcomes (3.3 out of 5). (Please see Figure 6, "Success and Desktop Performance Assessment," p. 8.) And, as before, Cisco thinks this is more a reflection of having that very information in hand, of knowing rather than guessing at actual performance, than it is an indication that these shops are, over all, not delivering services as well as those that do not monitor more closely. Far more successful (in the estimation of the participants) was intermittent collection of such data, which scored a “successful” 4.2 out of 5 rating, as did the leading strategy of doing indirect assessments. Surprisingly, the folks who watched only the infrastructure had the bleakest picture of their success in service delivery, a meager “of limited success” (2.0 out of 5) Figure 5: Assess Performance from User Perspective Figure 6: Success and Desktop Performance Assessment Structures of Support The other major facet of supporting remote offices is the organizational structure within which system administrators, application managers, and network engineers work. For remote offices, the most important issue is how to structure support of enterprise applications for remote users. The basic models for extending SDM to support remote users are: ? Central staff support all users; ? Mix of central and on-site staff support remote users; ? Outsourcers or service providers support remote users; ? Combination of outsourced and in-house staff support remote users. As the following charts illustrate, which support model a company builds on can have dramatic effects on the amount of time – and therefore the amount of money – spent on managing performance for and resolving support problems with remote use of enterprise applications. If we look directly at the fraction of their time central staff spend on service delivery and management issues for remote users, for example, we can see the combination of central and on-site staff results in the lowest investment of central staff time, a mere 13.1% on average. (Please see Figure 7, "Percentage of Central Staff Time to Remote User Support," p. 10.) Using central staff alone was next best, resulting in a 22% investment of time, followed closely by adding service provider support to the in-house (23%). Mixing central staff with outsourcers resulted in the highest investment of central staff time, 30.6% -- over twice as great as the mixed/on-site model. Another aspect of service delivery that shows distinct variation across support models is the time it takes to resolve problems, a key factor in both user satisfaction and in the understanding how central staff time is being spent. As the following charts show, in the support structures that involve in-house staff (that is, leaving aside the fully- outsourced remote support solution) once again the mix of on-site and central staff comes out best, with significantly lower times to identify and to resolve problems as they arise. (Please see Figure 8, "MTTI for Different Support Models," and Figure 9, “MTTR for Different Support Models,” both p. 11.) Figure 7: Percentage of Central Staff Time to Remote User Support Figure 8: MTTI for Different Support Models Figure 9: MTTR for Different Support Models Here, though, mixing service providers in has a beneficial effect: the elapsed time to resolve problems is lower when in-house and service provider staff are combined than when in-house staff alone handle problems. The most dramatic differences are between central staff plus service provider versus central staff alone: adding service-provider support reduces overall time to resolve by 40%! Still, the best solution for shops keeping all the work in-house, from the perspective of time to resolve problems, is to combine central and on-site staff, which reduces the time elapsed by 80%. Conclusions and Recommendations In the support of remote offices, the answers companies arrive at to basic structural and operational questions have a strong influence on how successfully they deliver enterprise services to remote users. It is important that IT shops look at fundamental metrics: ? related to service, such as the time it takes to fix problems from report to resolution; ? related to performance, including doing baselines for application performance and monitoring the user experience; and ? related to their costs, such as the amount of staff time devoted to supporting remote users. With solid data to bolster both their choices in structuring and sourcing support and objective data to measure their progress, they should be able to improve services and control costs at the same time. Gathering data about actual performance will in all likelihood make IT’s efforts appear less successful for a time, but offers the only possibility of having a true and accurate picture of what is going on and so must be undertaken. Knowing where you stand, truly, is the only way to make real and quantifiable improvements. Cisco has the following recommendations: For Enterprises: ? Know your structure. How many branches are there, of what sorts, and how interrelated? ? Know your performance. Even though it will probably make your operations look less successful at first, it is the only way to build a factual base for justifying change and verifying improvement. Start with collecting information about performance; with that in hand, set performance targets that are realistic then track delivery against them. ? Know your support outlays. Make sure you can track the fact that particular problems are reported by/resolved at branches, and whose time went into crafting the solution. ? Reassess the mix of central and on-site support in use at your company. Are there ways to place staff on-site at more locations, key locations, or locations with lots of problems? Does the time spent in problem resolution and supporting remote users outweigh the direct cost of placing support staff on-site at least part-time? ? Reassess your outsourcing relationships for remote-site support. If adding out-sourced support at remote sites is cheaper than adding in- house staff there, it will still provide you with improved resolution times and decreased load on central staff when compared to a central- staff-only solution. For Vendors and Service Providers: ? Service providers should track the amount of the clients’ staff time involved in solving problems and work hard to minimize it through process structuring and training. Quantifiably minimizing load on the central staff while improving the time taken to resolve problems will bolster your case for renewing contracts. ? Vendors should consider rolling the collection/reporting of performance data from the client desktops into your application clients; providing IT with an easy way to get objective data about performance without adding layers of software will be a strong selling point. For Investors: ? Look for service providers and outsourcing firms that track, quantify, and build contracts around key metrics relating to client IT staff time and problem resolution. Getting past service provided to improving service will be a key differentiator for IT shops looking to outsource in the future.
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