IT Assignment

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d o i : 1 0 . 1 1 4 5 / 1 7 3 5 2 2 3 . 1 7 3 5 2 5 3

by Paul P. tallon

O v e r t h e pa s t d e c a d e , t h e m O u n ta i n s O f d a ta

accumulating within firms – expanding at an annual rate of 30-50% and fueled in part by recent legislation such as SEC Rule 17a-4 mandating the retention of electronic communications (for example, email and instant messaging) in financial services firms for periods of up to three years – has forced information technology (IT) executives to ask how should this data deluge be managed. Intel, whose data warehouse is currently estimated at over 30 petabytes has increased its data storage by an average of 35% annually with the expectation that, if current trends continue, its data center could expand to 165 petabytes by 2014. Yet even as data volumes climb, causing data centers to double in size every other year, an innovation-led drop in annual per-gigabyte storage costs of between 35- 45% (see Figure 1) has failed to halt the rise in storage spending.2,8

With organizing and utilizing data now seen as one of the most critical issues facing firms worldwide,3 IT ex- ecutives note that non-discretionary IT spending – 25% of which covers infor- mation management costs and storage infrastructure, in particular – has now reached a point where strategic IT ini- tiatives are at risk.2 Hence, CIOs have a pressing need to understand the dy- namics of information management costs and their ability to control these costs through carefully chosen policies governing data collection and reten- tion. Knowing how these costs behave, CIOs can continue to support the data needs of their firms without limiting their IT goals.

To begin this process, we examine a tiered information framework that, by considering the value of information, allows CIOs to comprehend the inter- play of market forces that shape infor- mation costs.7,12 Lastly, we review sever- al challenges posed by our framework that future academic research can help to resolve.

information management costs Of the six cost categories seen in Table 1, information management costs are primarily shaped by two opposing forc- es – namely, better, faster, and cheaper technology which exerts downward pressure on costs, coupled with a ten- dency among firms to collect data on every facet of their business which leads to increased demand for storage capacity and an associated increase in costs. Since firms are unlikely to rip and replace their storage infrastructure each time a new technology innovation enters the marketplace, the dominant force behind the sudden rise in infor- mation management costs is the near- exponential growth in the volume of data that is being collected and held by firms. The problem is not simply the cost of storage infrastructure (disk arrays, device management software) but the labor and overhead costs asso- ciated with backup, recovery, and stor- age administration. The reality today is that the collection and retention of

understanding the dynamics of information management costs

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dynamic information Value A further complicating factor in firms’ efforts to manage information costs is the fact that not all data are created equal. For example, while a financial services firm could easily survive with- out access to its employee payroll data for 24 hours, the loss of key customer account data for any length of time could prove financially catastrophic. In such circumstances, an IT manager is less likely to favor a simple cost-min- imization approach to ongoing data management, fearing that the impact of delayed access or systems failure could outweigh any promised cost sav- ings from pursuing a low-cost infra- structure. Instead, service level param-

data is expanding at a faster rate than the ability of new technology innova- tion to neutralize or compensate for any demand-driven increase in storage costs. Firms are literally choking on their own data.

Even as firms struggle to accommo- date new data, there remains the ques- tion of how to deal with existing data that are stored on legacy systems. In an analogous sense, just as car drivers are reluctant to replace their cars each year simply because of new airbag or safety technology, better fuel economy, or a nicer interior, there is nevertheless a point at which the high cost of main- taining a long-since depreciated car exceeds the capital depreciation costs on a new car. Consequently, IT manag- ers need to recognize that information management costs arise not merely because of new data but also because of existing data and that in the lat- ter case especially, there may come a time when migrating this data to new, better, faster and cheaper storage in- frastructure becomes an increasingly attractive proposition. Knowing this, vendors have started to price new stor- age hardware so as to match the main- tenance costs of older hardware. Firms may mistakenly see this as having a neutralizing effect on overall storage spending but this is not the case.

eters such as reliability, availability, security, redundancy, response times, maintainability and scalability are more likely to influence infrastructure utilization decisions, even if this higher service level should cause an increase in information management costs. If IT managers are required to maintain high service levels for data that must be readily accessible, the fear that “you get what you pay for” will force them to mi- grate data to newer and more reliable storage infrastructure sooner rather than later, even if the capital costs of the existing storage infrastructure are not yet fully depreciated.

In contrast, low-cost rather than service-level criteria are more likely

table 1. components of information management costs1

cost categories description

Storage Infrastructure

Includes standalone purchase cost of storage devices, media, and data center infrastructure for San (storage area networks), naS (network attached storage) and iSCSI [6], and related software costs for storage capacity provisioning, configuration, and monitoring.

Maintenance Scheduled and unscheduled maintenance costs, and system upgrades.

Backup and recovery Costs associated with backing up information and recovering from an outage back to the initial point of failure.

Administration Data center management, training and staffing costs.

Environmentals Disaster-proofing, humidity and temperature monitoring.

Downtime Potentially the most significant cost category if a loss of data leads to business disruption, penalties, and damaged reputation. These costs can be inversely related to other cost components. For example, inadequate maintenance can precipitate extended periods of downtime.

figure 1. information Growth and storage costs

Source: Information growth is compiled from prior studies by the University of California Berkeley9 and IDC (http://www.emc.com/about/destination/ digital_universe/) and reflects the total amount of new data generated and retained annually. Storage costs are compiled from Gartner Group, IBM, and IDC estimates.

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to influence the management of non- critical data. For example, in the case of archival data where retention is mandated by SEC rules or other areas of legislation, service levels that allow for real-time access or synchronous offsite backup will drive up costs with- out enhancing the competitiveness or performance of the firm. Therefore, in the case of non-critical data, an IT manager may be able to compromise on service levels (up to a point) in pur- suit of cost savings. This could entail migrating data to cheaper storage me- dia (for example, tape rather than disk despite the higher risk of media failure and limited data access) or postponing a purchasing decision until the cost savings from new storage infrastruc- ture exceed the operating costs of the existing storage infrastructure.

Therefore, information manage- ment costs are not only impacted by the growing volumes of new and exist- ing data, but by the value to the firm of the information distilled from these data. As information value rises, it will become increasingly difficult to con- tain information management costs since a sizeable proportion of that cost constitutes a quasi insurance premium against data loss or corruption. The fact that next generation storage infra- structure is better, faster, and cheaper does not automatically cost-justify the replacement of existing infrastructure unless an improvement in infrastruc- ture reliability and quality helps to ex- pand the firm’s service level offerings. As information value falls, there is less need to maintain high service levels that would only increase information man- agement costs and so there may be op-

portunities to migrate or transfer data to cheaper media or to otherwise lower costs through reduced service levels. In this way, information management costs reflect different service levels that in turn reflect differences in the value of the underlying information.12

Once we know the value of infor- mation by, for example, determining how much additional profit or market share a firm could gain from using the information or how much could be lost in legal penalties or foregone profits if information is inaccessible,7 we can define an appropriate service level. However, as reported in the informa- tion life cycle management (ILM) lit- erature, valuing information is a non- trivial exercise since information value can change over time.4 For example, an airline passenger manifest is highly valuable when an aircraft is in flight but that value declines to zero (or close to zero) at the precise moment that the aircraft lands safely. Meanwhile, in the pharmaceutical industry, data from clinical trials can increase in value as a drug moves through successive stages of FDA approval. The cost to the firm of data loss increases exponentially as the expected market value of the drug climbs as each stage in the drug approvals process is successfully tra- versed, even though the data itself re- mains unchanged.

ILM, therefore, adds a further layer of complexity to the management of information costs in that non-critical or low-value information at a point in time could become critical or high-val- ue at a later time, or vice versa. Accord- ingly, firms need to evaluate informa- tion value on an ongoing basis, not just

for new data flowing into the firm but for data already held in data marts and archives or scattered on hard drives, thumb drives, CDs, and other media. As the value of information is assessed, there is a need to identify if the storage infrastructure is providing a sufficient level of service, minimizing costs but without elevating the risk of data loss or corruption to extreme levels.12 In some instances, the extent of storage spending could be reduced if risk is negligible. Not all data are equally valu- able and so it is economically unwise to treat all data with the same degree of care and attention. This does not mean, however, that low-value data should be deleted for as legal e-discovery events have shown, low-value data could still increase in value.

tiered information framework One way to limit this complexity, and so begin to understand the dynamic nature of information management costs, is to consider a tiered informa- tion framework that reflects an order- ing of information value throughout the firm. New data can flow directly into a tier or existing data can migrate to other tiers to reflect a change in its un- derlying information value. As shown in Figure 2, we illustrate this approach using a three-tier structure, where tier 1 contains high-value or critical data, tier 2 contains medium-value data, and tier 3 contains low-value or non-critical data. In reality, while the number of tiers and the ranges of information val- ues that separate each tier are uniquely defined by each firm’s business re- quirements,5 archiving practices mean that the demand for storage capacity will be greatest in lower tiers than in higher tiers. For example, under Sar- banes-Oxley and SEC rules, publicly traded firms are now required to retain electronic records of financial transac- tions for up to seven years.11 For many firms, this entails a significant archival undertaking and a substantial amount of investment in storage capacity.

Behind each tier lies a collection of hardware, software, and networking infrastructure that varies in complex- ity and reliability. In tier 1, for example, high-value data that are accessed on a frequent basis by ERP or CRM ap- plications could be held on high-end storage servers such as EMC Symme-

figure 2. tiered information framework

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This top-down and bottom-up se- quencing of new investment only makes sense in the context of a tiered approach to information management. For firms who have yet to structure their data in this manner – in effect, storing data on similar devices regardless of information value – the prudent ap- proach would be to upgrade their stor- age infrastructure as often as possible in order to protect their highest-value data. However, it is likely that firms in this situation will not have optimized their storage infrastructure and so they will either over-invest in infrastructure and over-insure against threats to in- formation value or under-invest and potentially expose their firm to cata- strophic financial losses from data loss and corruption.12

future challenges While our tiered storage framework can improve data management by unraveling the relationship between information value, service levels, stor- age infrastructure, and information management costs, there are a number of issues that have yet to be resolved and which require further investiga- tion. For example, if information value changes inside a short timeframe, as in our example of an airline passenger manifest, the frequent migration of data between tiers (specifically, from tier 1 to tier 3 in this example) could result in a significant transaction cost and potentially disrupt the dynamics

trix that are connected to application servers and other networks via fiber optic links. Firms cannot afford to al- low tier 1 data to be offline for any pe- riod of time and so it is advisable that tier 1 data be replicated in real-time to backup servers at a hot-site facility and that tier 1 infrastructure be able to seamlessly provision additional storage capacity. Tier 2 contains less valuable data such as payroll records or sales commission schedules – data that while important to the business is unlikely to be accessed on a frequent basis. This data could be held on mid- range systems such as EMC CLARiiON or Sun StorEdge. Lastly, Tier 3 holds non-critical data on low-end devices such as Dell PowerVault on in backup tape libraries. The low value of this data mean that service levels can be lowered subject to the fact that these data may be needed for regulatory or auditing purposes in future. Since infrastruc- ture is only visible upon breakdown, aggressive cost cutting – even within tier 3 – could create an unnecessary level of risk for the firm.

Overall, the primary difference be- tween each tier’s storage infrastructure relates to their service-level abilities. For example, tier 1 infrastructure supports applications that routinely require real-time data access and so connectiv- ity, scalability, speed, redundancy, and fault-tolerance are desirable and neces- sary qualities. As we look to lower tiers in the framework, the need for superior service levels gradually abates since the underlying information value is much lower, at which point cost becomes the dominant concern.

infrastructure Purchasing strategies Once this tiered information frame- work is in place, it becomes easier to identify opportunities for managing information costs. These opportunities could lead to a reduction in costs, but since the intent of the framework is to help IT managers to identify an appro- priate level of cost, it could also signal a need to increase costs to safeguard high-value data. However, what is cer- tain is that future innovation will help to reduce information management costs and so whether managers are coping with the influx of new data or reacting to changes in the value of existing data,

they must still determine how to incor- porate better, faster and cheaper stor- age infrastructure into their organiza- tion. As seen in Figure 3, our framework can help to clarify this issue by showing how new infrastructure fits into the var- ious storage tiers in either a top-down or bottom-up manner, reflecting the relative desirability of improved service levels or cost savings.

As mentioned earlier, the manage- ment of the top tiers of the framework is motivated by the need for superior service levels, whereas cost control is more important at lower tiers. As data volumes rise and IT managers are forced to identify what tiers are most deserving of new storage investment, their decision will hinge upon whether there is a need for enhanced service levels within the upper tiers or whether there is a greater need for cost savings within lower tiers. If there is a greater need for improved service levels – an is- sue that is more likely to apply to data of a strategic or competitive nature in tier 1 – faster and more reliability stor- age infrastructure will be applied first to tier 1, and then sequentially to lower tiers. If there is a greater need for cost reduction – something that is more likely to apply to lower tiers given the larger volumes of archival data and the use of older and potentially less reli- ability storage infrastructure in these lower tiers – new storage investment will be first applied to tier 3 and then sequentially to higher tiers.

figure 3. incorporating new storage infrastructure

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of how information is managed. Any attempts to generate cost savings by moving data to a lower-cost storage tier may need to consider not just the potential per-gigabyte cost savings but the added risk of storing the data on a less reliable architecture.

Equally relevant is the question of how information should be valued and how often such value is reassessed. In- formation value is significantly deter- mined by how information is used and could depend on access to complemen- tary resources and skills.10 For exam- ple, a firm could purchase point-of-sales data from a third party and yet not have the internal expertise to take advantage of it. Information value is also driven by compliance and the need to avoid le- gal fees and penalties that could follow from an inability to reproduce data in a timely manner for an SEC or FDA audit. In light of recent accounting scandals, firms do not want to tarnish their repu- tation by taking unnecessary risks with data. Research can help to identify best practices around how firms can factor such complex elements into a storage investment decision.

conclusion What is clear from this discussion is that storage and information manage- ment more broadly, are no longer mere tactical issues that can be addressed at an operational level. If information is critical to the success of the firm, se- nior management must help to design a strategy and a set of policies detailing how information should be managed. Failure to acknowledge differences in information value through a tiered in- formation framework, such as outlined in this article, could needlessly expose firms to significant risks.

A rapid decline in per-gigabyte stor- age costs has fostered a perception among IT practitioners that innova- tion alone can contain information management costs. The fact that non- discretionary spending now consumes 63% of IT budgets and that storage costs are somewhat to blame,2 suggests that firms cannot ignore how data are managed. If firms continue to collect and retain data at present rates amidst demands to contain rising storage ex- penditure, we can expect data man- agement to become more complex. Growing amounts of unstructured data

(email, video, images) will add to that complexity. Treating all data equally, as many firms have done in the past, is no longer suitable when information value varies widely and when the service level output of firms’ storage infrastructure also varies. Using a tiered information framework is key to understanding the dynamics of information management costs, not only as a way to control costs but to highlight areas where additional investment is needed to protect infor- mation value and to ultimately secure the survival of the firm.

References 1. Allen, N. Don’t Waste Your Storage Dollars: What You

Need to Know. Gartner Group Research Report COM- 13-1217, 2001.

2. CIO Insight. Is your IT Budget being spent effectively? (Feb. 2005), 67-75.

3. Computer Sciences Corporation. Critical Issues of Information Systems Management. Cambridge, MA, 2001. http://www.csc.com/features/2001/40.shtml

4. EMC Corporation. Information Lifecycle Management, 2004. http://www.emc.com/ilm/.

5. Ferelli, M. Tiered storage: An idea whose time has come. Computer Technology Review 23, 11 (2003), 1-2.

6. Gibson, G. and Van Meter, R. Network attached storage architecture. Comm. ACM 43, 11, (2000), 37-45.

7. Glazer, R. Measuring the value of information: The information-intensive organization. IBM Systems Journal 32, 1, 1993, 99-110.

8. Gilheany, S. The decline of magnetic disk storage cost over the next 25 years. Berghell Associates, 2004. http://www.berghell.com/whitepapers/Storage%20 Costs.pdf.

9. Lyman, P. and Varian, H. How Much Information? UC, Berkley, School of Information Management and Systems, 2003. http://www.sims.berkeley.edu/ research/projects/how-much-info-2003/.

10. Mata, F., Fuerst, W. and Barney, J. Information technology and sustained competitive advantage: A resource-based analysis. MIS Quarterly 19, 4, (1995), 487-505.

11. Securities & Exchange Commission (SEC). Final rule: Retention of records relevant to audits and reviews. http://www.sec.gov/rules/final/33-8180.htm.

12. Tallon, P. and Scannell, R. Information lifecycle management. Comm. ACM 50, 11, (2007), 65-69.

Paul P. Tallon ([email protected]) is an associate professor of Information Systems and Director of the David D. Lattanze Center for Information Value at the Joseph A. Sellinger, S.J., School of Business and Management, Loyola University, Baltimore, MD.

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