Business Analytics: Six Steps to Getting Results

By John Lucker

Although reams have been written about analytics, and opinions abound about its potential to change how businesses think and behave, analytics in the end is an important and valuable driver in achieving decision-making success.

Discussions on analytic software and tools are certainly useful, but technology is just one piece of the analytics puzzle. To apply analytics effectively, businesses should think beyond technology to consider how an analytical approach affects many aspects of their operations.

This holistic approach to analytics involves six steps that progress from strategy and planning to ongoing performance management. In moving through these steps, businesses may be able to accomplish the following objectives.

·       Define the objectives for constructing an analytics road map.

·       Create the strategy for achieving the objectives and achieving a return on the investment.

·       Do the actual analytics work.

·       Embed analytics inside business operations and processes.

·       Integrate enabling technology.

·       Guide the organization through the inevitable change.

·        Monitor results against the anticipated ROI.

·          Create a continuous improvement process of tuning and enhancement.

Many analytics projects fail because too much time is spent doing what can be done with analytics versus focusing on what, specifically, the business should do with analytics. By focusing on the analytics process—from strategy to results—organizations can replace activity with achievement.

Step 1: Define an analytics strategy that builds in flexibility.

Embedding analytics into strategy and planning can help build a more flexible business with an ongoing ability to anticipate rather than react. Change begins when the organization recognizes the intrinsic and extrinsic value of data in sharpening conclusions and moving to a metrics-driven company culture. As the old saying goes, if it can be measured, it can be managed. 

Leadership should be tasked with evangelizing and operationalizing this vision. Leaders should speak in one voice with a consistent message that reinforces the value of an analytical approach. Business unit leaders should lead by example, demonstrating how analytics-derived facts are informing their decisions in new ways.  In this way, the organization can better articulate its values, the needs of its customers and what its offerings should be.

One specific technique is to design an end-to-end strategic road map composed of short-, medium- and long-term analytic achievement—each with a resulting ROI – where the value generated by prior projects feeds the cost of downstream efforts. Employed effectively, this method can create a self-funding mechanism that allows a company to control its analytic investments with the potential to achieve a significant reward. This road map process is at the core of defining analytic strategy.

Step 2: Perform focused analytics activities.

This step creates the DNA of the end-to-end analytics process. Here, strategy is transformed into tangible analytic results. Data mining, predictive modeling, optimization and demand analysis, customer segmentation, and supply chain and materials movement analytics are a small subset of potential components. The analytic activities involve algorithms and other technical components that should be integrated into technology, business and operational infrastructures in various ways.

During technical development, numerous rules of thumb should be considered. For example, technical perfection for analytic development is rarely necessary to achieve business objectives. Rather, the focus should remain on the end goal of strategic advantage, the affect of diminishing returns of technical development, and the inevitable pressures of time and speed to market. 

A common theme with analytic solutions is that the tangible ROI resulting from the full end-to-end analytic approach is typically quite visible and measurable to business management. Therefore, the focus should remain steadfast on the needs of the business and the requirements of the analytics strategy from Step 1.