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ABCs of Evaluating Your Advanced Analytics Initiative

Evaluating your advanced analytics initiatives can be as easy as checking their ABCs.

A recent survey of over 1,500 global executives by Forbes and Ernst and Young found that 70 percent of top performers have used advanced analytics to overhaul business strategies and update how they compete in their respective markets. CIOs across all industries are investigating how advanced analytics initiatives can make their organizations into top performers.

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Your goal is to determine which advanced analytics initiatives will have the desired impact on your organization. To get started, evaluate the ABCs of each initiative.

A is for Alignment

First and foremost, you must assess the alignment and fit within your business strategy. Where does your senior leadership envision your organization in 3-5 years? Is this future state transformational from where you are today? Does your analytics initiative fit within that vision and act as a catalyst for that transformation? If so, you are on the right path. If not, your initiative might not be an appropriate use of your limited resources.

One method for evaluating the alignment of your prospective analytics initiative is to determine how strongly it correlates with and can be measured by the key performance indicators your business uses to measure its overall success. If the success criteria and metrics resonate with your executives, your initiative is likely in line with the company's strategy. If you can only measure its outcomes with traditional IT operational metrics, the initiative might not be as aligned as you desire.

B is for Building Blocks

Advanced analytics initiatives require certain levels of application technology and data management to achieve major business objectives. Evaluate your advanced analytics initiative by assessing what technological building blocks you have available and whether they are the ones you need to succeed. You need to match the technology you have with the technology you need.

When evaluating technology needs, it is easy to assume that your resources will magically be able to adapt to and adopt any tech you acquire. Vendors may also reinforce this idea. Over time, that evolution of talent can occur through training and practice and through natural staff turnover, but this does take time and must be factored into your evaluation.

Three main categories of technology building blocks are critical for your advanced analytics initiative.

  • Data movement and storage. The data your initiative needs is rarely all in the same place, ready for you to start extracting key insights. Data is often found in multiple systems, both internal and external, and exists in multiple formats or states of quality. Your initiative must be able to gather this data into a central location, either physical or logical, from which value can be derived. Do you have the right tools to make sure that the data you need is centralized and accessible?

  • Data processing. Once your data is wrangled in, the next technology you need is the infrastructure to derive meaningful insights from the data. This transformation is often referred to as data science because it involves the scientific experimentation to delve into the data and see what secrets and patterns exist that can provide business value. This process leverages data discovery, application of different algorithms, and assessment of the effectiveness of converting data into information. Do you have access to and experience with technology that can process the data, so it can provide meaningful information to enable your initiative?

  • Data distribution. Once your data has been processed and evaluated, you must place it in the hands of your key stakeholders and decision makers. This is where data distribution comes into play. This includes technology that both allows key stakeholders to pull data on demand and pushes data to them as needed. Do you have a platform that can distribute your insights?

These tech building blocks are critical to the success of your initiative. If your initiative requires real-time data extraction, advanced stochastic calculus, and linear algebra to transform data and you are limited to using manual data entry and Excel spreadsheets as tools, the initiative might not be the right fit for your current maturity level.

C is for Cost/Value

Finally, you need to evaluate the potential economic impact of the initiative on the business. This includes what it will cost and what its expected value will be to your business.

Cost is more easily quantifiable, but alone is an inadequate measure of complete economic impact. A cost evaluation includes the technology expenditures and labor resources needed to get the initiative up and running. Once the initiative is in production, on-going costs include the operational costs for the technology infrastructure as well as the resources needed for performance monitoring and for continual adjustment of the underlying models to ensure promised strategic benefits.

Evaluating the value of an advanced analytics initiative is just as important as evaluating its costs. Some benefits such as potential cost savings, cost avoidance, or additional revenue generation can be quantifiably forecast. The problem is that these metrics alone do not always paint the complete picture of the economic value of your advanced analytics initiative. Benefits, such as increased customer satisfaction, decreased risk profile, or increased business differentiation from competitors can be just as important to your business but are not easily measured. This requires that your economic evaluation encapsulate both quantitative and qualitative measures to assess the total economic benefit that the initiative can provide your business.

A Final Word

As you take steps to become a top performer in your industry, you will likely evaluate multiple advanced analytics initiatives. As you do, apply the ABCs (Alignment, Building Blocks, Cost / Value) and you can more effectively assess whether your proposed advanced analytics initiative is a good fit for your organization.

About the Author

Troy Hiltbrand is the senior vice president of digital product management and analytics at where he is responsible for its enterprise analytics and digital product strategy. You can reach the author via email.

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