Chief analytics officer

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The Chief Analytics Officer—A Heads-Up Display for the CEO

Fighter pilots traveling at supersonic speeds rely heavily on their displays and gauges. Split-second decisions need to be made in real time. Their data-monitoring needs are intensive: from weapons systems to power plant to radar images to navigation systems. Basing decisions on the wrong data can prove fatal.

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Chief Executives also require data and input from their organization. They need to make critical decisions based on this data. Basing decisions on incomplete or faulty data can prove to be devastating for the organization and the CEO’s career.

Just as the fighter pilot relies on a heads-up display, the CEO’s needs are similar. But, since the data the CEO needs to make decisions is disparate in both a business context and with regard to technical systems, it is not as simple as adding a heads-up display. Technology currently exists to provide CEO-level dashboards, but the real heads-up display is an emerging role in organizations, the chief performance officer (CAO).

The CAO acts as the heads-up display for the CEO. And similar to the fighter pilot, actions are taken based on indications from that display. Since much of the data required for decisions is business specific, the CAO must be specialized enough to provide a relevant context to the required data.

In many organizations, multiple individuals are actually playing the CAO role. Chief financial officers (CFO) provide the much needed input from a financial perspective such as revenue, margin, EBIT, etc. Supply chain executives provide needed input from vendors and give perspective, including lead times, turn around, etc. Research & development, customer support and human resources have their own measurements, as well.

In reality, though, the CEO ends up being the integrator and interpreter of the information. The CEO must take in information from various reports, graphs, and presentations and correlate this information to make informed decisions. There are two major problems with this scenario. First, the CEO may not have intimate enough knowledge of the data to perform adequate correlation of disjoint business data. Second, and more important, the CEO does not have the time for these tasks. In the fighter jet, the jet pilot does not use wind gauges, compasses, dipsticks, and voltmeters to gather the information while flying at Mach 2. The pilot is presented with the most relevant data required to make the decision at that exact moment. CEOs need this type of heads-up functionality for their business.

Chief analytics officer (CAO) is a job title for the senior manager responsible for the analysis of data within an organization, such as a listed company or an educational institution. The CAO often reports to the chief executive officer.

Not many companies currently have the role of Chief Analytics Officer (CAO) defined within their existing c-suite. However this is a fast emerging position that would be pivotal in massive transformation - in the way companies take their business decisions. CAOs not only bring strong data science backed actionable insights to the table, but also own the resulting 'ROI'/'Impact' on both top line and bottom line numbers. [1]

This position, along with that of chief information officer has risen to prominence due to the rise in information technology and data acquisition. The two positions are similar in that both deal with information, but the CIO focuses on the infrastructure required for maintaining and communicating information while the CAO focuses on the infrastructure required for generating and analyzing information. A similar position is that of the chief data officer (CDO); while the CDO focuses on data processing and maintenance, the CAO focuses on providing input into operational decisions on the basis of the analysis. As such, the CAO requires experience in statistical analysis and marketing, finance, or operations. The CAO may be a member of the board of directors of the organization, but this is dependent on the type of organization.

No specific qualification is typical of CAOs in general. Many have advanced degrees in mathematics, statistics, economics, or econometrics but this is by no means universal. Many were analysts in the past.

The CAO: Business Executive, Technologist, Interpreter

The CAO is faced with the unique challenge of being part business executive, part technologist, and part interpreter.

First, business expertise and business experience are paramount for the CAO. A thorough and complete understanding of the strategy of the business is required. The CAO must have expertise that can help him to understand not just what is happening in the organization, but why. Through this expertise, the CAO can identify and make relevant disjointed observations from the business data. The CAO also needs real business experience. This is not a role for fresh-out-of-college hires. There are certain intangible business skills that are only gained through experience. As part of the expertise, the CAO must have analytical tools such as forecasting, strategic planning, return-on-investment models, and governance compliance. These raw tools are most likely being used by various parts of the organization, and the CAO will need a certain understanding of all of them.

Second, the CAO is part technologist. A successful CAO has technical knowledge, but is not burdened with technical implementation details. Unlike a chief technology officer (CTO) or chief information officer (CIO) who may implement programs for ‘technical glory,’ the CAO is interested in technical pragmatism. The CAO must be aware of the existing technology used by management such as budgeting systems, data warehouses, and intranets. Detailed technical knowledge of the inner workings in not necessary, though, since the CAO is ultimately interested in the output, or data, drawn from these systems. The CAO must also understand emerging trends in technology. Of particular interest are areas such as business intelligence, which concentrates on collecting and disseminating analytical business data, and collaborative systems, which allow automated sharing of information throughout the organization through Web-based technologies.

It is also important for the CAO to understand the importance of introducing technology incrementally. Too many information technology project sponsors underestimate the impact of ‘technical saturation.’ To a pure technologist, the latest Java-based, Web-enabled, thinclient application may be the best answer, but to the actual business user of the system, an extension to their existing spreadsheet might accomplish the same end. The CAO ultimately represents the business, and cannot be lured into the trap of looking for ‘technical glory.’

Third, the CAO is part interpreter. The CAO must be able to communicate in both business and technical terms. Concurrently, he or she must be able to speak at different levels of detail, whether at a management, executive, or board level. The CAO must have the vocabulary and interpretive knowledge to bring the information to the recipient’s level. It does little or no good to present middle-management level project statistics at a board of directors meeting. Conversely, middle management may not understand or be privy to board-level aggregated performance data. As interpreter, the CAO must quickly be able to adjust the level and context of what is being presented

The 4 C’ S: The Roles of the CAO

The roles of the CAO can be classified into four categories: collector, consolidator, condenser, and communicator. In performing each of these roles, the CAO can provide significant value to an organization.

Collector

The CAO plays the role of collector. He or she collects performance measurements and metrics from all parts of the organization. These measurements may be in automated systems on various technical platforms. It takes significant business expertise to understand what is important to collect, and what can remain within the department. As part of the collection process, certain technologies such as databases and corporate networks need to be understood and leveraged. In the end, all the performance data will be in one place—the CAO needs to begin with this end in mind.

Consolidator

In the role of consolidator, the CAO must take the disjointed performance data and consolidate it into one view. This usually takes the form of a single system or database. This consolidation role will also require significant business knowledge. In particular, expertise in how the measures are used in combination is key. Business expertise and experience will help the CAO decide which data must be homogenized and which can remain distinct. Many parts of the organization will use financial performance measures, but most likely, the measures from the finance organization will serve as the ‘data of record.’

One requirement of consolidating performance data is the process of technical consolidation. There are many technical tools and techniques one can use that can assist with technical consolidation such as data warehouses, online analytic processing (OLAP), and data cleansing tools. Ultimately, these systems must remain relevant to the business rules and not just perform technical consolidation of the raw data. This is another area where the risk of chasing ‘technical glory’ is high. Many technologists will apply pressure to implement more highly automated and highly complex systems than are pragmatically possible, when simple consolidation, using existing technology, is often all that is needed.

The CAO must know when the consolidation can be helped by technology and when the process can be hindered by technology. Since the ultimate goal is to provide a heads-up display for the CEO, pragmatism must rule.

As important a decision as what to consolidate is what not to consolidate. The CAO must use business knowledge and experience to exclude data that should not be consolidated. For example, it may not make sense to consolidate older customer information or long-time discontinued products and their actual order line items. Instead, the CAO may choose to consolidate information about discontinued customers and products to avoid the overhead of processing through thousands of irrelevant line items.

Condenser

The CAO must also play the role of condenser. Even after the performance data has been consolidated, it needs to be condensed into a concentrated form that is usable by executives. The collection and consolidation process may limit, or even filter, some of the data being collected, but in the role of condenser, the CAO must now present the most relevant data. Much of the data collected and consolidated will have too much detail to be usable by the CEO. For example, during collection and consolidation, product level (SKU) information may be used. The CEO, though, will require division level performance data. This not to say that this condensed data should be the only data available, but as condenser of the data, the CAO must present the highest level of data to support the decisions of the CEO. If further data is needed to prove out the higher-level data, that data should be made available as well. As a condenser, the CAO must keep the most relevant data easily accessible without flooding the CEO with unneeded details.

Communicator

The role of communicator is the most important for the CAO. What good is it to have collected, consolidated and condensed the data to only have it locked up in a computer system? Or, worse yet, if it requires an army of dedicated programs to produce ‘management reports?’ This is actually the downfall of many business intelligence and executive information systems. The CAO must be prepared to communicate the data to the recipient in the most accessible way possible. One size does not fit all. Some executives will only require a Power Point briefing of the most relevant facts supported by some graphs and tables. Others will want a digital dashboard approach of an executive information system, where the executive is able to drill into more detail interactively using a computer system. Others may require detailed briefing books that present an executive summary with supporting analysis results and industry references.

The CAO needs to understand what the executive needs and wants for his or her own version of a heads-up display. Based on these needs, the CAO will need to prepare and present the performance data. As a communicator, the CAO needs to be prepared for two-way communications. The performance data he or she presents will most likely cause the CEO or other executives to take corrective actions. The CAO must be able to understand the actions required and be prepared to explain the results of such an action in terms of performance, while still speaking in executive terms.

Beyond the executive level, the CAO must be able to communicate to upper and middle management their specific interpretation of the performance data. This is not to say that the CAO individually briefs all middle managers. Instead, through his or her technological background, the CAO selects an appropriate delivery mechanism of upper and middle management performance data. This could once again be in the form of briefing books or executive information systems, but it will most likely be in the form of reports and online applications.

In understanding his or her role as communicator, the CAO must be able to apply the proper business filters to the data. Mid-level managers will not be privy to the same data available to the CEO. The CAO communicates at the appropriate level of detail and is always governed by confidentiality parameters set by executive management.

For all the CAO’s roles, the performance data is fact-based. Although business experience will guide some of the filtering of data, the CAO can fall into the trap of hunches and intuition. The CAO must remember that he or she is acting as the heads-up display and that the CEO will use their input for making far-reaching decisions. If the CEO solicits an opinion from the CAO, an opinion should be given, but the CAO should never substitute opinion or hunches for facts.

Industry Specific or Industry Neutral

On the surface, the CAO role seems generic, one that can function the same way in any industry. It is true that every organization in every industry needs a CAO. A question arises, though: does a CAO need to be industry specific?

Comparing their role with other executive level positions lends some insight to this question. The CFO, who is responsible for financial operations, needs to have a strong foundation in finances and the techniques involved. Depending if the organization is growing organically or through mergers and acquisitions, different methods, techniques and skill are needed. Within the CFO field there are certain specialties, such as service organizations, publicly versus privately held, and local versus multi-national reach. All of this will determine what specific skills are needed. Generally, though, CFOs are industry neutral and can move between industries when changing companies.

The CIO or CTO, who is ultimately responsible for technology in an organization, must have a strong technological foundation. Again, depending on the strategy of the organization, different techniques and skills may be required. Some CIO/CTOs will be very skilled in service contracts and outsourcing, while others will be very skilled with inhouse development and software package implementations. The CIO/ CTO is very much a product of the organization’s industry, though. Historically, certain organizations have gravitated towards certain technologies. For example, the insurance industry and public sector have used large mainframe systems and been traditionally aligned with IBM-centric architectures. The financial trading industry has traditionally used high availability and fault-tolerant systems, which use a much different architecture. Hospitality and food services have traditionally been very mid-range centric. Each industry will have its own level of affinity with a certain technology or platform.

This is not to say that a CIO from one of these industries will only have experience in a particular set of technologies, but there is a higher chance of an affinity to certain technologies based on the industry.

If we look at the three required backgrounds of the CAO—business expert, technologist, and interpreter—industry experience does have varying levels of importance. Business experience is the most industry specific. The interpreter is closely tied to the business expert. A good interpreter is required to have certain vocabulary specific to their industry. Some individuals demonstrate a chameleon-like ability with business vocabulary and terminology, but generally, real business experience rather than buzzword savvy is required. The technologist experience is probably the most industry-transportable. This is further facilitated by standardization and ubiquitous technology trends such as databases, networks, and the Internet. When assessing an industry move, the CAO must take into account the learning curve which he or she will encounter from all three perspectives: business expert, technologist, and interpreter


Changing role of the Chief Data Officer and growth in the Chief Analytics Office

Research* indicates that First Generation CDOs are typically responsible for the following:

In addition to these key responsibilities, the First Generation CDO is concerned with communicating his/her value to the organisation, evangelising the importance of data and building business processes to ensure efficient workflows.

These are all the critical, foundation-building baby steps that need to be taken before moving into the next phase or generation of CDO-ship. The CDO is producing step-changes within the organisation's data architecture and usage. Change is big but perhaps does not deliver significant business value.

Second Generation CDOs and the shift into a CAO

Our research has uncovered that, in the second phase, there is almost a shift away from being a CDO toward being a Chief Analytics Officer. The ultimate end goal for data in an organisation is to have the ability to use it to make good decisions in real time.

It's based on this that I assess the Second Generation CDO as being increasingly responsible for, and involved with, advanced business analytics. The first phase was all about getting data in shape for it to be utilised accurately across the business.

It's at this point where the CDO is involved in the optimisation and transformation of the business.

Our research has uncovered that, in the second phase, there is almost a shift away from being a CDO toward being a Chief Analytics Officer. The ultimate end goal for data in an organisation is to have the ability to use it to make good decisions in real time.

Innovation through data!

The Second Generation CDO becomes an integral part of eking out the hard-fought percentages of business improvement and profitability. Innovation across the organisation has come to rely on data. Product innovation takes a look at how the product is performing, who buys it, how it is manufactured etc. to evolve it and keep its competitive edge. None of this could be done without access to good quality data in real time - or at least in a short space of time.

A recent study shows an increasing number of CDO's at the forefront of their company's digital transformation, most likely because data and analytics play such a critical role in digitising a business, and so as a result many Chief Data Officers have moved in Chief Digital Officer roles.

What does the Future Look Like?

It's not easy to predict what the next generation will look like and how they'll act. I don't think Facebook anticipated that the current youngest generation would not be big users of the service.

Data Digest points that out by the development of the CDO - and for that matter the CAO and the Chief Digital Officer. Could they all blend into one? Or will they be obsolete in a few years and replaced with a new emerging C-suite?

For now, we'll keep focused on understanding the different needs of the First Generation and Second Generation of CDOs to ensure we can provide relevant information and networks. It is likely that the next generation will only emerge in 4–5 years time.

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References

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