Understanding the Current C-level is not Data-Knowledgeable
If you thought to yourself:
Hmm – isn't the CIO the top data job?
Then you are exactly the person we are trying to reach. The short answer is:
Not in today's IT shop!
Before launching into what some have already viewed as a critique of the CIO function, it is important we state that CIOs have accomplished astounding feats, developed excellent organizational skill sets, and delivered tangible business value. In the process, we've learned a great deal about using technology to obtain a strategic advantage. CIOs have our tremendous respect for the amazing results delivered by the organizations they oversee, the differing approaches to IT management, and reward systems (Wailgum 2009). As a group, they have proven themselves astoundingly capable and quite adept at addressing organizational challenges – sometimes by incorporating new technologies (clouds, analytics, service architectures, etc.) into complex environments. With rapid technology advancement, slow learners quickly fall behind and those who survive as successful CIOs have achieved extraordinary success. But those who are successful as still largely unknowledgeable of the foundational role data plays in IT. Most organizations suffer from poor DM and a small but measureable number (less than 10%) thinks the approach we have outlined below is just common sense. An early reviewer of this book stated:
I have worked with very senior, very talented CIOs. These folks fundamentally understand data – the complexity, multi-dimensional behavior and systemic flow of data. They understand the consequences of not delivering data to key operations. They understand the importance of data around operational risk and risk reporting. So it’s not a knowledge issue – I believe it’s a focus and attention issue.
We have to respectfully disagree with the reviewer. Our combined 80 + year experiences with more than 500 organizational DM practices indicate that 90 (+) percent of CIOs are data-unknowledgeable. When discussing with the data-knowledgeable 10%, they are inevitably surprised to learn they comprise such a small minority. CIOs are successful at what they do – it is what they have not accomplished that concerns us – CIOs have not managed to:
Manage data as an organizational asset in an attempt to obtain a strategic data advantage!
Data are assets that deserve to be managed as professionally and aggressively as other company assets. Objective measurements show that few organizations achieve DM success and are able to exploit a strategic data advantage (see Section 2.7). In the face of the ongoing "data explosion," this leaves most organizations unprepared to leverage their data assets.
The redress goes beyond having the CIO appoint a subordinate, chief data officer (more in Chapter 5) and assigning this vital, lacking function to its rightful owner, the business. While transformation may require some organizational discomfort, this move will achieve improved organizational IT performance faster and cheaper than ERPs, Six Sigma, or any other silver bullet proposed to date.
Returning to our title …
If the CIO isn't the top organizational data job then what is?
CIOs/IT leaders and knowledge workers in general have little education/training in, and thus do not possess the requisite KSAs to make decisions about organizational data. Being data-unknowledgeable, collectively they don't know what they don't know. What knowledge they have has been acquired on the job and, since data can occupy only a fraction of their focus, not much OJT has taken place.
Data are an organization's sole non-depletable, non-degrading, durable, strategic asset. You can't use it up. If properly maintained, it cannot degrade over time or from use. It is by accounting definitions, durable – persisting beyond the one-year yardstick. Combined these make data unique as assets in the organizational repertoire. Yet, this fails to acknowledge data's primary value – factual information, fit for use, describing the organization's operations/environment and facilitating better decision making.
Data has a clear value that increases as it evolves along the value chain. From business predications, it becomes transactions, and ultimately the basis for future predications. DM requires specialized knowledge, dedicated resources, and sustained organizational commitment. These components have been missing from virtually all organizations because they don't know these requirements exist. (It also requires a specific, critical momentum; DM has a tipping point – paying off according to a step function.) Quality DM depends on leverage and leverage requires an understanding of architecture/ engineering concepts – concepts missing from virtually all-education/training and thus, they are not part of any conversation. As a result, organizations attempting to obtain a data advantage ultimately fail in their attempts.
Next we describe the nature of CIO function. To understand the facing challenge, it is important to understand leadership and symbolism requirements accruing to chief officer positions, indicate a needed focus on technology management, and highlight the varied backgrounds brought to these positions.
[The definition for chief is: "the head or leader of an organized body of people; the person highest in authority: the chief of police.] dictionary.com
Organizations have recognized the need for individuals to be knowledgeable and accountable for important organizational assets and functions. Figure 3 is a list (largely from Wikipedia) of 58 commonly used organizational titles beginning with the word "chief."
Chief Accounting Officer, Chief Administrative Officer, Chief Analytics Officer, Chief Audit Officer, Chief Brand Officer, Chief Business Officer, Chief Channel Officer, Chief Commercial Officer, Chief Communications Officer, Chief Compliance Officer, Chief Creative Officer, Chief Data Officer, Chief Executive Officer, Chief Financial Officer, Chief Human Resources Officer, Chief Information Officer, Chief Information Security Officer, Chief Innovation Officer, Chief Investment Officer, Chief Immigration Officer, Chief Geospatial Information Officer, Chief Knowledge Officer, Chief Leadership Officer, Chief Learning Officer, Chief Legal Officer, Chief Marketing Officer, Chief Marketing Information Officer, Chief Medical Officer, Chief Merchandising Officer, Chief Networking Officer, Chief Operating Officer, Chief Process Officer, Chief Procurement Officer, Chief Product Officer, Chief Research Information Officer, Chief Risk Officer, Chief Science Officer, Chief Stores Officer, Chief Strategy Officer, Chief Technology Officer, Chief Visionary Officer, Chief Web Officer
Figure 3: Fifty-eight, commonly used chief officer titles (more exist)
The organizational expectation is that the individual holding the title is the most knowledgeable executive in the organization and is responsible for the organizational asset referenced by their title. The Chief Financial Officer (CFO) is the individual possessing the KSAs to be both the final authority and decision-maker in organizational financial matters. The Chief Risk Officer (CRO) is the individual possessing the KSAs makes decisions and implements risk management. The Chief Medical Officer (CMO) is responsible for organizational medical matters. (The list continues … ) The organization, and the public, has similar expectations for any of chief officer.
The Broad Technology Focus of the CIO Function
The first uses for computing technology were to automate existing manual processing. This made existing processes faster. As well articulated below:
Fifty years ago, data management was simple. Data processing meant running millions of punched cards through banks of sorting, collating and tabulating machines, with the results being printed on paper or punched onto still more cards. And data management meant physically storing and hauling around all those punched cards (Hayes 2002).
Tasks such as check signing, calculating, and machine control were implemented to provide support for departmental-based processing. Early on, there was no industry-wide approach to development of these data processing systems. Instead, they were the product of the creative minds and spirited individuals within business departments (i.e., Personnel, Payroll, Inventory, Manufacturing, etc.). Consequently, each functional unit of the organization developed its own siloed data processing systems and data (see Figure 4).
These siloed systems worked well in isolation but requests for integrated data require significant additional development to accomplish the integration and large quantities of additional processing to achieve it. The description of the upward theoretical complexity required to integrate N siloed systems is:
( N * ( N – 1 ) ) / 2
Figure 5 graphs this function to illustrate the steep rate of increase in the quantity of
integration-only based systems that need to be created. To completely integrate the six systems shown in Figure 4, 15 different data interface systems need to be created to connect everything to everything using point-to-point interface solutions. The red X on Figure 5 signifies the complexity point a large bank calculated as it managed 5,000 interfaces among 200 major function-based siloes. These numbers and complexity levels pervade all types of organizations and have held steady across decades.
Each data interface becomes a data processing system in its own right (ETL, for example, comprises a major category of small systems). If you start with six silo-based systems, and add the 15 data interface systems, you end up with 22 systems required to provide point-to-point connections among six siloes.
As you can see from Figure 6 more than a few interfaces and the costs of point-to-point connectivity among siloes far outweigh their primary advantage – the solution implementation speed. When managing too much complexity, an organization's IT (and general) productivity decelerates. The more programmatically data interfaces can be managed, the lower IT’s costs become.
Eventually, these system arrangements achieved conditions requiring an individual to be in charge. The original title given was "Data Processing Manager" but that soon evolved to "Chief Information Officer." Wikipedia as defines a CIO as:
· The chief information officer (CIO), or information technology (IT) director, is a job title commonly given to the most senior executive in an organization responsible for the information technology and computer systems that support organization goals (Wikipedia 2012).
According to another definition, the CIO, is:
· The executive officer in charge of information processing in an organization. All systems design, development and datacenter operations fall under CIO jurisdiction (Encyclopedia 2013).
This makes both makes intuitive sense and also simultaneously accounts for much of the misconception. If CIOs manage the information technology, then they must also manage the information – right? Wrong! (See Section 4.5). Studies show that the CIO, accomplishes an astounding array of technological and processing feats and that virtually all of these distract from a primary focus of the Chief's title: Information Officer. Complicating this further, is a lack of uniform CIO qualifications and preparation.
 For a number of years, one of your authors held the title "US Department of Defense Reverse Engineering Program Manager" as head of the DoD team charged with addressing these challenges.
A Word About Uniform Qualifications – CIO preparation
There is a general belief that the average CIO tenure is from 18 months to two years (Marks 2011). A search for "CIO tenure" reveals a more diffuse picture. Recently, unsubstantiatable evidence has been introduced indicating that CIO tenure is approaching 4.5 years. In contrast, the tenure of a CFO appears to have increased to almost 12 years in the year 2010 according to (WEBCPA 2010).
CFOs have uniform prerequisite skills, certifications, and educational accomplishments. Professional organizations and recognized best practices uniformly dictate a non- controversial set of requisite knowledge, skills, and abilities. To achieve this, the Chief Financial Officer (CFO) commonly possesses a Certified Public Accountant (CPA), a Masters degree in Accounting, a Certified Management Accountant (CMA), an MBA, other recognized degrees/certifications, or at least a strong accounting background. The U.S. Sarbanes–Oxley Act of 2002, enacted in the aftermath accounting scandals, requires at least one member of a public company's audit committee to have financial expertise (Congress 2002). These are widely recognized as necessary but insufficient prerequisites/qualifications and all applaud the need for uniform credentialing.
So where do CIOs come from? A strong IT knowledge has been seen to be a big "plus" – with the other "plus" being organizational experience. While the lack of a "Qualifications Section" in Wikipedia is hardly proof, there is very little agreement on what is an appropriate background for a CIO. Popular CIO backgrounds include operations, finance, and sales/marketing (see Figure 7). Wikipedika continues, "recently CIOs' leadership capabilities, business acumen and strategic perspectives have taken precedence over technical skills. It is now quite common for CIOs to be appointed from the business side of the organization, especially if they have project management skills" (Wikipedia 2012).
CIOs come from a variety of backgrounds and are expected to master a wide variety of technologies as well as oversea a variety of technical functions. Despite a lack of formal, comprehensive, certifications and educational accomplishments, the CIO is the business executive upon whom is placed the requirement for the broadest skill set! These often include items from (Curran 2009)'s list:
Hands-on technology background;
Experience in leading large change programs;
Experience in running successful IT infrastructure operations;
Management experience in a non-IT function;
Innovative thinking that can solve relevant industry and business issues; and
The ability to understand how projects and operations impact corporate financials.
Finding these in a single individual has been a challenge. A quote well describing the current situation comes from a former CIO colleague:
Advisors have been pontificating on the evolution of the CIO role towards CPO – Chief Process Officer. So now the CIO would own all technology, all processes and all data. No other organization is experiencing this evolution into other spheres of influence. The CHRO does HR work. The CFO does financial work. The COO does operations work. However, the CIO is expected to be the head of technology, the architect of all business processes and the intelligence behind leveraging data. Most CIO’s today are challenged with being "experts" on technology (infrastructure and application), business process, relationship management and data management). None are successful at all and most have a bent towards only one of those areas, depending upon where they began their career and the path they took to attain their CIO role (Giuffrida 2011).
The management of data as an asset has almost never been seen as a significant CIO skill or job qualification requirement. A typical computer science/information/systems/ computer engineering degree includes just one course focusing on data. That course typically focuses on the how's of building a database using Oracle, MS-Access/SQL Server, or an open source project. Outside of a few isolated programs [see (DAMA-International 2012)], there are not many places that an aspiring IT executive would even encounter DM as topic of study.
The typical CIO (IT/knowledge worker) has not had many opportunities to learn DM. Smart, anxious-to-learn individuals, study, preparing for IT leadership – primarily through graduate curricula. They take classes and learn what we teach them. Since DM is not a formal part of the curricula, they explicitly learn that DM is not part of what IT leaders do. Since DM was not part of their education, it doesn't become part of their IT management purview. This technology focus provides the average IT worker with very little practical knowledge of how to best leverage an organization's data assets in support of strategy. As a result, very few IT or business professionals are data-knowledgeable.
In summary, while some C-level positions benefit from uniformly mandated knowledge, skills and abilities, the CIO function has become data-unknowledgeable. As such they approach the function with a variety of differing perspectives but almost all lack explicit knowledge of how to leverage data assets and they don't know that they don't know it!
What are the CIO Function Challenges as Currently Practiced?
IT has been complicated and organizations find it more effective to concentrate technical skills in fewer specialists instead of teaching all knowledge workers to (for example) manage servers. They create IT leverage, using a few knowledgeable IT specialists to provide services to all. However, unlike most Chief Officers, who have real authority over their function area, e.g., CFO has real authority over finances, CIOs are generally not:
The ultimate authority on informational assets;
Able to devote the required time/attention to manage these assets;
Possessed of the requisite expertise to leveraging data assets; and
(As long as they have a technology/application-centric perspective, they are not) Situated to achieve success organizationally.
Using the above criteria, few current CIOs qualify as data-knowledgeable. Being data-unknowledgeable and using the title, these CIOs are unintentionally misleading their organization in two ways:
They are misleading them into thinking the CIO is focused on leveraging the organization's data assets; and
That the CIO has the requisite KSAs and is capable of making good decisions about data.
Our educational and professional support systems have left this 90% CIO group – data-unknowledgeable. Section 4.7 will show the CIO agenda so packed that to increase the resources devoted to management of data as an asset something else would literally have to be dropped – an impossibility for most. Only a fraction of these busy executives time could be reallocated without hurting other responsibilities. This is a serious structural gap in most organizations and has been the root causes of many IT challenges.
Explaining the current Challenge
It is said that only by asking "Why?" five times, successively, can you delve into a problem deeply enough to understand the ultimate root cause. The current challenge can be explained as:
Why (1): Why do organizations continue to find it difficult to leverage data in support of strategy?
Symptom: Organizational knowledge workers, IT leadership/professionals are data-unknowledgeable – data development is foundational to and precedes technological systems development
Why (2): Why do so many misunderstand data's role in IT?
Symptom: There is little focus on organization-wide data use in education/training system
Why (3): Why is the educational system not addressing this gap?
Symptom: Lack of recognition by the system that it is a problem; curricula are focused on one, narrow aspect of DM – building new databases
Why (4): Why has the educational system not yet been made aware of this deficiency?
Symptom: Lack of understanding at the C-level of these issues – otherwise they would insist on changes
Why (5): Why do they not understand?
Symptom: They know little, if any, about organization-wide data use
Figure 8 presents a complementary analysis showing how inadequate training, unfamiliar methods, over-reliance on technologies, missing measurement systems, and low familiarity with data all contribute to poor data/IT outcomes. The result has been a widespread lack data-knowledgeable decision-making.
We presented the "Chief Officer" function and the surrounding expectations, background, and preparations. We explained why today's CIO is unlikely to be data-knowledgeable due to the lack of organizational DM visibility in educational/professional curricula as well as the reporting hierarchy (see Section 4.5.2). The challenge is deciding what needs to be done to address this deficiency? We begin with an examination of the architecture/engineering basis required for data-knowledgeable decision-making.