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Building the Analytic Organization

The evolutionary process of analytics continues to mature. The idea of leveraging analytics to enable the management processes continues to gain momentum, with different organizational models being proposed. However, many organizations still find it difficult to effectively manage their information assets and develop management processes built on analytics. As the amount of data an organization collects grows exponentially, the need to consistently apply this information across the entire enterprise in the decision-making process increases. To address this gap, organizations should consider adopting the role of chief analytic officer (CAO) that oversees the analytic function. This article will explore the idea of a CAO and the analytic function, and the key actions required by both CAO and CIO to support the analytic-focused organization.

The analytic evolution continues. We are heading into the third evolutionary phase of how organizations leverage information to drive results. The organizational value that is realized from turning data into information to create knowledge is forcing the issue to go beyond where we are today. We have come a long way in the last 20 years, but the journey continues.

The first phase of the corporate information evolution addressed an area of need that organizations required to begin leveraging data more effectively. Data warehousing and business intelligence (BI) initiatives have been a heavy focus on getting technical and architectural components in place to support and leverage corporate data assets. The focus was on getting past performance or lagging information into the decision-maker's hands to provide an answer that they probably already knew. It was still a critical step in the evolution and forced many organizations to adopt technology platforms and tools to better equip the knowledge worker. You can refer to this as the "efficiency" stage of the evolution.

The second phase, which we are in today, is looking at analytics as a core competency to differentiate from the competition. How can the organization actively predict outcomes based on scenario-based decisions, such as developing new products, penetrating new markets or providing new services? Creating the enterprise business model, both current and future, is a critical first step in developing the analytic capabilities of the organization. This goes beyond the first stage of evolution and focuses on areas like predictive analytics, business modeling and scenario planning, data mining and root cause analysis. You can refer to this as the "effectiveness" stage of the evolution.

What's next? Increasing the value to the next level by making analytics serve as a function, like finance, sales or marketing, and not just as a competency. Just like the current organizational functions of finance, sales and marketing, this dedicated group of individuals would be responsible for how data, information and knowledge are used to create organizational differentiation from the competition. This concept of an organizational analytic function would be run by a CAO with a dedicated group of functional and technical experts.

So now that the concept is out there, what is the impact? What radical changes need to be considered to develop the analytic-focused organization? Where will accountability lines be drawn within the current organization, specifically, between the CIO and IT?

The Analytic Organization

Let's start by focusing on the description of the analytic function and the strategic shifts that an organization will need to consider.

The analytic function would be run by a CAO who would be directly responsible for the mission of the organization. The function would be a combination of both business and technical expertise in the area of analytics. The CAO would provide analysis capabilities to the other functional areas such as finance, sales and marketing. The ultimate vision for the analytics function would also be responsible for data collection and information through the creation of a robust analytic technology architecture. This would be a radical shift, since this area is developed and managed by the CIO and IT function.

To make this change and develop the formal analytics function, there are a set of organizational shifts that need to take place:

In addition to making some key organization shifts in how the enterprise approaches analytics, there are a set of core actions that need to be executed to establish the analytics function.

1. Form the analytic function.

Make the commitment to analytics. Establish the leadership role and build out a team of individuals with the mission to enable the business to drive analytics as a core competency and differentiator in the market. Identify the individuals out of the different functional areas and backrooms into the forefront of the organization. The team makeup would include cross-functional expertise in both business and technology. Initially, the team would be a grassroots effort, ramping very quickly as the value is recognized within the organization.

2. Develop analytics as a competency.

Analytics is a simple concept, yet requires expertise and competency within the group. This includes understanding the intricacies of the business model and how the core business processes impact the financial, customer, internal process and learning and growth perspectives of the organizational strategy. The focus should be on increasing the organization's "analytic quotient" to make fact-based business decisions. In addition to creating the expertise, analytic concepts should be aggressively applied across the entire organization. It is imperative that the organization fully realizes the value in leveraging information to create knowledge in the decision-making process. It would be the responsibility of the CAO to educate, enable and drive adoption across the enterprise and have it ingrained within the culture of the organization.

The Role of the CIO

The role of the CIO and the IT organization will be greatly impacted by the creation of the analytic function. The CIO has two choices: fight the concept or be the catalyst to get the group off the ground! I won't describe how to handle a fight, but instead focus on how the CIO can further enable the analytic function and become a trusted advisor to the CAO.

Like the CAO, there are a set of initial actions that the CIO must first address to establish the analytic function.

3. Get your data in order and in line with the analytic needs.

The first action the CIO needs to execute is to create the required connection between operational data, performance management information and the creation of knowledge. The lifecycle of data along each of these areas is critical to drive the value from the corporate data assets. The CIO is currently accountable for each of the technology platforms from operational data to knowledge creation.

The CIO's role to this point has been focused on collecting, organizing, aggregating and making meaning out of data. The technology has evolved into leading-edge concepts like virtual data warehousing and real-time analytics. In reality, these concepts just increase cycle time capabilities. They don't necessarily address the "what" associated with data, meaning what data is critical to support the analytic needs. Eric Beinhocker addresses the concept of information and wealth creation in his book "The Origin of Wealth."1 Ordered information creates knowledge, while information on its own is considered worthless. The same concept is true when thinking of corporate data assets. Without this information being put into the context of the business, it can be considered worthless. By providing context to information, organizations have the opportunity to create wealth from their data assets.

4. Evaluate how analytics will be distributed and consumed by the enterprise.

Understanding how to "release" the analytics upon the rest of the organization will facilitate the CIO's ability to develop a vision for the technology platform. A typical gap in this area is that there is not a "one size fits all" solution that addresses the entire organization's needs. The type of analytics that users will consume (static reports, dashboards, scorecards, guided analysis, alerting, and ad hoc analysis) will differ depending on the role of the individual. In addition to how analytics will be consumed, the mode of distribution (paper, PC, smart phone) will differ depending on the audience (executives, line of business owners, analysts, power users).

5. Build the enabling technology platform.

The final action that the CIO must address is developing the technology platform that supports the vision for the analytic function. This is where the CIO will truly become the catalyst of change to create the analytic-focused organization.

It starts with establishing the reference architecture for the technology platform that will enable the analytic function. It has four core focus areas that need to be addressed to close the technology gap.

Reviewing these four focus areas, it is clear that the CIO is directly accountable for each of these areas.

Where to Draw the Line

So where do the lines of accountability get drawn in the organization between the CIO and the CAO? There are unique roles that need to be played between these two areas of responsibility that must be established at the outset.

The CAO is accountable for driving analytics as a differentiator across the enterprise. This includes the formulation of organizational analytic capabilities, including areas like casual analysis, data mining, statistical analysis and predictive modeling. The CAO will be responsible for developing analytics as a core competency within the analytic function and across the entire organization.

The CIO is accountable for the enabling platform to support analytics. This includes the data collection, aggregation, standardization and technologies that will distribute analytics across the enterprise. The CIO will need to develop the core competencies that will enable the IT function to support the technology needs to the Analytic function.

Where do the lines become fuzzy and unclear? It starts with delivery of information. The CAO will need to drive the understanding of the full depth and breadth of the information needs of the business. The CIO will need to pick up how the technology tools available can meet those needs, as discussed. This gray area will require that the CIO and CAO engage closely to support each distinct function of IT and analytics. By forming a partnership with a clear set of responsibilities, the gray areas will not be a factor if the organization is truly became committed to analytics.

References:

  1. Eric Beinhocker. The Origin of Wealth. Cambridge, MA: Harvard Business School Press, 2006.

Peter Graham is the vice president and practice leader of the Information Management at Palladium Group, Inc. Graham is involved in setting the strategic delivery capabilities in information architecture for strategy execution solutions. With more than 10 years experience, Graham is a thought leader and contributor to publications, including CIO Magazine, BI Journal and BI Review. He can be reached at peter.graham@palladiumES.com.

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