Single Version of Truth

Research analysts agree that on average less than 32 percent of trade promotions today are measured, and of that small number that are measured, a significant percentage are not realizing return. This month, CGT sat down with Russ Hill, Director Consumer Products, Retail, Distribution & WW Industry Marketing for Business Objects, who taps into his industry expertise to touch upon issues surrounding trade promotion analysis and effectiveness, retail profitability and cost-to-serve.

What steps can consumer goods firms take to measure ROI on trade promotions?
Industry trends indicate that one of the primary areas for consumer goods companies to address is trade promotion effectiveness. When forecasting promotional plans, budgets are determined, over time, based on historical premise of what happened in the past with their retail customers. It is essential to ensure operational efficiency within a company and minimize any risk to the successful execution and management of the corporate and divisional objectives. Usually the IT department needs to develop a way to manage enterprise information assets, and in particular, how well information is delivered to end users to achieve their specific business objectives.

The information delivery process is usually characterized by a highly labor intensive, manual assembly approach. When evaluating, the process may require pulling data from a multitude of data sources, providing the raw data to analysts throughout the enterprise, and analysts utilizing one of several tools to collect, review and report upon conclusions. The result of the current information delivery process is costly and inefficient in the following ways:

• Data rich, but lacks information

• Duplication of efforts

• Multiple versions of the truth

• Inaccurate/conflicting data

• Valuable resources working on non-value creating activities

• Loss of focus in some cases

• Lack of accountability

• Lack of speed to insight

Can you expand upon how "Multiple versions of the truth" inhibit the information delivery process?
Simply, the problem of "Multiple versions of the truth" -- and the challenge of understanding the different information silos -- comes down to answering the following questions: What defines a customer? What is the trade "spend"? Who from a functional business role is using trade spend optimally with the customer base? What is the market share (by channel, by segment and by geography)?

Under the current business process, and the systems supporting these processes, the answers to these questions determine what data is utilized to conduct analysis. Different functional roles within a consumer packaged goods company will answer these questions differently, resulting in multiple answers to the same question and hence "multiple versions of the truth".

Do you agree that CG firms are challenged to manage the granularity of promotions to understand which are effective down to the customer and, sometimes even store level?

This goes without saying. Retail operations function and interact differently when collaborating with CPG companies for executing on promotional campaigns, new item introductions and category reviews, to name a few. As mentioned previously, it is advantageous to understand the business processes, identify business questions relative to understanding the impact of trade spend effectiveness and determine key metrics against established parameters for functional business roles. This is the foundation to initiate a plan to gain insight into the many types of promotions that CPG companies will be confronted with; to assess effectiveness of campaigns; for accountability and to determine future plan of action. Promotional campaigns can be monitored and achieved at the store level, however, it is necessary to overcome information hoarding between retailers and CPG companies in order to share vital information that can help evaluate the performance of events to streamline operations and take costs out of the system.

Once this level of promotional analysis is achieved, are companies able to start extracting valuable insight out of their data?
Certainly. As CPG companies become intent on understanding their data, questions become relevant to enable process change. Examples may be:

• Why is share declining? What is happening with trade spend? How effective is my trade spend?

• Brand cost or brand LTV?

• What was the net result of the fluctuation in brand volume?

• Price elasticity. What is the effect of price variance? How does the price change impact margins?

• Promotion tracking. What is the effect of a campaign? Does it drive other products to be purchased or is the company trading dollars?

• Halo and cannibalism effects. Is the company getting more value added products resulting from campaigns?

• Contract compliance. The more you buy, the bigger the discount. This is based on inventory turns regarding volume.

How can CG firms further understand the value that could be derived from this increased level of promotional and data analysis?
Based on the gaps between many current state and desired future capabilities with companies, the following outlines basic process/system requirements that would have to be met to establish an effective trade promotion analysis process:

• The ability to automate the integration of trade spending data (account review), shipments (transactional system), and consumer take-away information (ACNielsen), remaining customer profitability reporting inputs.

• Automated analysis and scorecarding utilizing proven best-practices.

• Accessibility to a common view of promotion results by all process stake-holders, e.g. field sales, marketing, finance, sales leadership, operations, customer marketing, etc. 

• Exception reporting to identify and report promotional occurrences that fall outside of predefined ranges. Content customized by end-user

• The ability to support an automated "alerts" process based on hierarchical reporting relationships, enabling management intervention and best-practice sharing within teams.

• Easily scaleable and reconfigurable to accommodate changes in hierarchical reporting relationships (product, geography, organizational, etc.), as well as defining new metrics.