[IMGCAP(1)]Corporate America is at a tipping point. According to an IDC report, the digital universe is doubling in size every two years and will reach 44 trillion gigabytes by 2020. Simultaneously, according to the Information Economics Assessment Kit published by CGOC (the Compliance, Governance and Oversight Council), while the value of aging data decreases rapidly over time, the cost to manage it remains constant, creating an ever-increasing expense.
Meanwhile, with flat or shrinking budgets, IT is often scrambling to cut operational and capital costs wherever possible. The most effective way to control these costs is controlling the growth of data that requires storage by automatically disposing of “data debris” in a legally defensible way. By putting reliable processes and technology in place to achieve this, companies can set a goal to delete as much old data as is being newly added in order to achieve zero or even negative long-term growth rates.
Toward this end, many organizations are beginning to implement Information Lifecycle Governance, or ILG, programs based on models that have proven effective at eliminating data debris, retiring legacy applications, and modernizing records retention and legal hold programs.
However, starting these corporate-wide initiatives can be hard work. Many organizations struggle to develop business case models that demonstrate meaningful returns on investment. Some ILG programs that start strong falter over time due to a misalignment of program structure and goals with those of the overall organization. It is imperative to the success of any program, large or small, that both the metrics and methods used to measure returns, and the reporting and governance structure of the program, be in alignment with corporate economic and strategic goals.
ILG is not a “one size fits all” proposition. For an individual ILG program to reach its full potential, program developers must consider the organization’s strategic business goals when determining which specific returns to measure and the methodology used to calculate ROI. The key metrics fall into both hard and soft cost savings. Examples of hard cost savings include capital expenses realized from storage and server reduction, eDiscovery cost reduction, elimination of legacy application software license and maintenance fees, and records storage cost reductions.
Examples of soft cost savings include legal and regulatory risk reduction, increased process efficiencies, and increased productivity related to finding information faster. To succeed, ILG program developers must understand the array of potential returns and ensure the business case focuses most heavily on those aligning with corporate strategy and economic goals.
It is also important for program developers to consider the organization’s economic environment when rolling out an ILG program. The company may be heavily impacted by an economic downturn, in a significant growth period, or embroiled in a fight for market dominance with a competitor. Understanding this environment and how it drives decision making at the highest levels can help program developers define a program emphasizing and aligning with corporate objectives. In a time of downturn, the focus may be data cleanup and hard cost savings. In a period of expansion, it may be efficiency, access to information, and risk avoidance.
Another key to the success of an ILG program is ensuring the program’s structure is aligned with the overall corporate governance model. Typical corporate governance archetypes include a business monarchy, where senior business executives make IT decisions affecting the entire enterprise; an IT monarchy, where IT professionals make IT decisions; a feudal structure, where business units, regions or functions act independently; a federal structure, where the interests of both the central organization and business units are equally represented; an IT duopoly, where IT executives and another group (such as a CxO) share decision making; and anarchy.
The governance structure is important to ILG because this is precisely how budgets are developed, savings are calculated, ROI is measured, and returns are redistributed. Programs whose models diverge too far from the corporate governance structure are destined to fail.
By contrast, if a company’s governance structure is particularly immature or lacking in structure, the development of the ILG program may be an opportunity to restructure or improve the overall corporate governance model. Immaturity or lack of structure may actually be what is driving the need for better ILG in the first place. For example, one recent client had a very feudal corporate governance structure. Unsurprisingly, the company struggled to implement a consistent data disposition program. The few employees on the ILG committee, though quite senior, lacked the political power to effect change across other units. The fragmented nature of the corporate structure was a primary driver of the growth of data debris, and it wasn’t until we expanded the committee to better align with the feudal system and made some changes to the feudal model itself that the program had a significant impact with material returns.
A Fortune 100 aerospace and defense client with more than $20 billion in revenue provides a more comprehensive case study. At the inception of the ILG program, the company’s capital and operational expenses for data storage were just over $70 million, with annual growth projected at over 10 percent. The five-year run rate was anticipated to exceed $120 million. IT labor costs were annualized at about $15 million, including a plethora of consultants, and the annual software budget was $15 million, plus $3 million for yearly maintenance fees. Additionally, the legal department was spending almost $20 million on eDiscovery due to government subpoenas and civil actions, and discovery was taking up the majority of their time.
Though in a growth period, the company had an increased focus on cost avoidance associated with redundancy in software and data storage, with increased concern for application optimization. Internally, a goal had been set for a 67 percent improvement in IT processes. When rolled out, the ILG program was structured to support these goals and help the legal department reduce the costs and time spent on discovery. Risk mitigation was highlighted but not a central focus of the program.
By its second year, the program reduced storage costs to $65 million, which provided an internal rate of return on program expenses of over 130 percent. When considered against the five-year run rate, returns were even greater. Return on investment at three years was 345 percent, at four years 453 percent, and at five years 559 percent. The company regularly achieved a reduction of duplicated assets by 75 percent, which lowered infrastructure costs over time by 80 percent and reduced the costs of maintenance and operational support by 75 percent. Finally, the company reduced the time to respond to subpoenas by 75 percent and cut overall discovery costs by 40 percent. Each of these returns was directly in line with corporate economic and strategic objectives at the start of the program, making the program much easier to support and fund, and ensuring long-term returns would also be in line with leadership’s objectives.
Based on the economic environment and corporate governance structure, each organization needs to define what its priorities are, which metrics are most important, and whether they are more heavily weighted toward hard or soft cost savings. Once this is done, ILG program managers are better positioned to align the program with the needs of the organization, demonstrate its effectiveness, expand it holistically across the enterprise, and capture, measure and successfully reinvest the savings.
David J. White is a director in the eDiscovery and Information Governance practice group at AlixPartners and a faculty member of CGOC (Compliance Governance and Oversight Council). His practice focuses on issues regarding information lifecycle governance with a particular focus on electronic discovery and international and domestic data privacy and security.
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