April 16, 2009
JTTP: Global TPM Practices Study Finds That We Talk Better Than We Act
By Bob Houk and
Michael Forhexz
Through a special arrangement,
presented here for discussion is an excerpt of a current article from The
Journal of Trading Partner Practices (JTPP), the official online publication
of the Vendor Compliance Federation (VCF), the Trade Promotion Management
Associates (TPMA), and the Federation of Credit and Financial Professionals
(FCFP).
The results of a study on trade promotion
management (TPM) implementation practices on a global basis, compiled by
Trade Promotion Management Associates and Infosys Corp., finds that some
much-discussed topics, such as predictive analytics and promotion optimization,
are not being implemented as quickly as the talk might indicate.
The study, which will be released in more
complete form this summer, was conducted over several months in late 2008,
and includes responses from mostly larger companies, and mostly consumer
packaged goods suppliers.
The objectives of the study were to identify
the current maturity level of global trade promotion management practices,
to identify best practices and benchmarks in use of analytics for TPM,
to assess process and technology sophistication, and to identify challenges
and opportunities in TPM initiatives and implementations.
Respondents said that TPM is important to
their companies, with a median rating of eight on a ten-point scale. But
when asked about things that were stopping or slowing implementation:
- Seventy-seven percent said they had problems with
data availability, quality, and harmonization - Sixty-seven percent have problems with lack of
standardization in processes - Fifty percent cite lack of alignment of goals among
marketing, finance, and sales
These are substantial barriers, all of which
are familiar to everyone in trade promotion. The nature of such barriers
is further proof, if needed, of the importance of having senior management
champions for TPM implementations.
As a result of the barriers, only 13 percent
of respondents are using predictive modeling software, and a similar number
are using pricing optimization tools. Considering how much talk there has
been about these topics over the past several years, it is a bit surprising
that only one-eighth of large CPG marketers have actually implemented such
tools. Most respondents are using only the promotion planning and funds
management modules of their TPM systems, with smaller percentages using
modules for data management, post-event analysis, and execution.
The metrics used to track effectiveness of
trade spending are another indicator that we may not have moved as far
as we might think. When asked what metrics they used, respondents replied:
- Seventy-three percent: Actual spend to budget
- Seventy-three percent: Net incremental sales
- Fifty-seven percent: ROI (based on consumption
or shipment) - Forty percent: Incremental spend per incremental
case - Thirty-three percent: ROI (variable and fixed margin)
- Thirteen percent: Other
The survey suggests that the biggest challenges
continue to be the most familiar: data availability and reliability, lack
of system and process standardization, and a lack of clear goal alignment
within the enterprise. While we have long known about these problems, practitioners
are still struggling to overcome them.
Bob Houk is the executive director of the Trade Promotion Management
Associates. Michael Forhez is a senior principle
at Infosys Corp.
Discussion Questions: What’s slowing the
adoption of analytics in trade promotion management practices? What metrics
should be used to track the effectiveness of trade spending? How can
companies better align the goals of marketing, sales and finance to create
a coherent TPM strategy?
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In addition to these issues, I recently wrote a commentary and published it through AMR that outlined the key issues with Promotion Optimization and why retailers have not implemented this solution in greater numbers.
Consider the fact that most retailers realize up to 70% of their sales through promotions. One would expect that this would be an area that would be addressed from every angle. Plan it better, determine items and prices better, and execute it better. The real challenge is that the activities required to make this occur are really difficult and require significant workflow, insights, and optimization to accomplish a reasonable software solution.
Today most vendors have delivered an automated version of what retailers attempt to do manually. This is not good enough. Interested in knowing more, I’ll share my article with you.
A significant part of the challenge isn’t so much process alignment as it is process scalability. Whether you’re one retailer dealing with multiple vendors on multiple products, or you’re one manufacturer dealing with multiple retailers, the process HAS to be fairly automated or it just won’t be sustainable. But in order to get processes to be more automated, the data has to be clean and timely, and the language that everyone speaks about how a process works has to be aligned. Without that, TPM won’t get anywhere.
It never ceases to amaze me how little coordination there is among divisions of large CPG companies. Trade marketing and promotion is one of the largest expenditures in a brand budget, and reaches consumers as they are at the point of purchase, yet few companies adequately measure the results and key departments within the companies don’t collaborate to gather and share data. This is not a problem with data. It’s a problem in the companies.
Not to oversimplify but my experience in working with retailers is that analytics are not utilized mostly for three reasons:
a) Lack of time
b) Lack of analytics training and education
c) Lack of interest
There has been an explosion of data and analytical tools for promotion planning and evaluation and yet the implementation has lagged behind.
Much of this seems due to unclear strategies and unaligned structures rather than a lack of capability. What is it we are truly trying to achieve? Who determines the goals? What are the metrics?
Our experience is that the data and systems can become easy prey to conflicting opinions and agendas. When the data do not support the agenda, the tool is blamed and the implementation is blocked.
The Global TPM Practices Study is timely considering the current economic chaos gripping our industry. I suppose you could even argue it is a bit late. To be sure, the subject has been discussed numerous times and virtually everyone agrees something should be done by someone.
Several companies have developed software platforms to enhance a company’s capability in trade promotion analysis and management. Unfortunately, the linkage of the value equation to the return on investment into another analytic tool has been lacking. This exists on several levels.
First, it appears every company has similar but different processes in trade promotions – everything from how the monies are accrued, which sku’s drive the funds, and what the resulting mix pays out vs the goal. Secondly, every company bases their success or failure in different ways, if at all. Finally, the majority of companies begin with the best of intentions in measuring their effectiveness, and generally the project drifts into oblivion as the priorities of the company change on a weekly if not daily basis.
The mountains of data which drown the best analysts in useless activities are sufficient to at least begin these analyses. And, much of what could be done with a simple data pull from a database and then analyzed for promotions effectiveness exists today.
All that has to be done is take the first step. It is amazing what could be done to understand promotional effectiveness and ROI on trade investments with a simple beginning.
Then, allow the process to evolve and become part of your culture. And, as the process evolves and the team members are conversant in the measures of their success, the additional data points can be added to further the organization’s understanding of their own efforts.
Counting the percentage of respondents rather than the market share of the minority that is using TPM analytics and optimization is going to make it look like these applications have a lot less traction than they actually have. A plurality of SKU’s and trading pairs are using optimization and automated TPM to some degree. It’s still a Big Boys game.
On the optimization side, the technology rolled out to the retail side well before CPG. The early tech was consumer centric (from a retailer’s point of view) and needed to be reworked to suit CPG. It also works better when there are a lot of purchases to analyze, further reinforcing the skew to the largest users.
It’s also important to understand that the optimization requires the user(s) to set priorities for volume, revenue and margin. One of the drivers of recent CPG adoption is that the outcomes of a retailer’s optimization aren’t necessarily congruent with what’s optimal from the vendor side. The happy medium occurs if both can agree on a consumer centric optimization. CPG users needed to catch up and adapt to the conclusions generated by the retail tech.
From the solution vendors’ side, the concentration on either side favors approaching the largest retailers and vendors first. There’s a certain minimum cost to making a pitch/sale, researching the client’s requirements, installing the solution, training users and then rolling out the solution to trading partners for collaboration. Not uncommonly, this requires an analysis of billions of data points within formulas that employ millions of variables and there are thousands of hands and eyes to please along the way. It’s very heavy lifting.
On the standardization point, the only reason why these applications are as well developed as they are is because the successful solution vendors DIDN’T wait around for some entity to deliver a standard. Instead, they adopted the retail side business requirements as the de facto standard for sales teams working with that retailer.
In general I think the other comments here have it right. It takes time, and training that often is not done. However, I still stick with the fact that goals are not aligned. Many merchants see themselves directly rewarded by bringing in trade promotion dollars. Most vendor sales forces like them, too as an expedient and low maintenance method for satisfying a customer and “buying shelf”. As long as the practices are rewarded in these pockets they will remain entrenched. Right now, most of the players who would be asked to do the input and analysis would get limited benefit (they think) from a lot of work, so they do not do it. This is one of the usual gaps between marketing and sales. In general it is marketing that wants this analysis both to benefit financial results as well as increase movement. However, when the top lines meet goals and sales or merchants keep getting rewarded for this behavior, the gap widens and not much is done. Where finance, marketing and sales are aligned, then the analytics work and work well. So, it is little surprise we see them first in the big boys as noted. Times like these will drive the adoption down the ladder and more broadly when and if companies align on the idea and don’t react to it as more busy work.
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In addition to these issues, I recently wrote a commentary and published it through AMR that outlined the key issues with Promotion Optimization and why retailers have not implemented this solution in greater numbers.
Consider the fact that most retailers realize up to 70% of their sales through promotions. One would expect that this would be an area that would be addressed from every angle. Plan it better, determine items and prices better, and execute it better. The real challenge is that the activities required to make this occur are really difficult and require significant workflow, insights, and optimization to accomplish a reasonable software solution.
Today most vendors have delivered an automated version of what retailers attempt to do manually. This is not good enough. Interested in knowing more, I’ll share my article with you.
A significant part of the challenge isn’t so much process alignment as it is process scalability. Whether you’re one retailer dealing with multiple vendors on multiple products, or you’re one manufacturer dealing with multiple retailers, the process HAS to be fairly automated or it just won’t be sustainable. But in order to get processes to be more automated, the data has to be clean and timely, and the language that everyone speaks about how a process works has to be aligned. Without that, TPM won’t get anywhere.
It never ceases to amaze me how little coordination there is among divisions of large CPG companies. Trade marketing and promotion is one of the largest expenditures in a brand budget, and reaches consumers as they are at the point of purchase, yet few companies adequately measure the results and key departments within the companies don’t collaborate to gather and share data. This is not a problem with data. It’s a problem in the companies.
Not to oversimplify but my experience in working with retailers is that analytics are not utilized mostly for three reasons:
a) Lack of time
b) Lack of analytics training and education
c) Lack of interest
There has been an explosion of data and analytical tools for promotion planning and evaluation and yet the implementation has lagged behind.
Much of this seems due to unclear strategies and unaligned structures rather than a lack of capability. What is it we are truly trying to achieve? Who determines the goals? What are the metrics?
Our experience is that the data and systems can become easy prey to conflicting opinions and agendas. When the data do not support the agenda, the tool is blamed and the implementation is blocked.
The Global TPM Practices Study is timely considering the current economic chaos gripping our industry. I suppose you could even argue it is a bit late. To be sure, the subject has been discussed numerous times and virtually everyone agrees something should be done by someone.
Several companies have developed software platforms to enhance a company’s capability in trade promotion analysis and management. Unfortunately, the linkage of the value equation to the return on investment into another analytic tool has been lacking. This exists on several levels.
First, it appears every company has similar but different processes in trade promotions – everything from how the monies are accrued, which sku’s drive the funds, and what the resulting mix pays out vs the goal. Secondly, every company bases their success or failure in different ways, if at all. Finally, the majority of companies begin with the best of intentions in measuring their effectiveness, and generally the project drifts into oblivion as the priorities of the company change on a weekly if not daily basis.
The mountains of data which drown the best analysts in useless activities are sufficient to at least begin these analyses. And, much of what could be done with a simple data pull from a database and then analyzed for promotions effectiveness exists today.
All that has to be done is take the first step. It is amazing what could be done to understand promotional effectiveness and ROI on trade investments with a simple beginning.
Then, allow the process to evolve and become part of your culture. And, as the process evolves and the team members are conversant in the measures of their success, the additional data points can be added to further the organization’s understanding of their own efforts.
Counting the percentage of respondents rather than the market share of the minority that is using TPM analytics and optimization is going to make it look like these applications have a lot less traction than they actually have. A plurality of SKU’s and trading pairs are using optimization and automated TPM to some degree. It’s still a Big Boys game.
On the optimization side, the technology rolled out to the retail side well before CPG. The early tech was consumer centric (from a retailer’s point of view) and needed to be reworked to suit CPG. It also works better when there are a lot of purchases to analyze, further reinforcing the skew to the largest users.
It’s also important to understand that the optimization requires the user(s) to set priorities for volume, revenue and margin. One of the drivers of recent CPG adoption is that the outcomes of a retailer’s optimization aren’t necessarily congruent with what’s optimal from the vendor side. The happy medium occurs if both can agree on a consumer centric optimization. CPG users needed to catch up and adapt to the conclusions generated by the retail tech.
From the solution vendors’ side, the concentration on either side favors approaching the largest retailers and vendors first. There’s a certain minimum cost to making a pitch/sale, researching the client’s requirements, installing the solution, training users and then rolling out the solution to trading partners for collaboration. Not uncommonly, this requires an analysis of billions of data points within formulas that employ millions of variables and there are thousands of hands and eyes to please along the way. It’s very heavy lifting.
On the standardization point, the only reason why these applications are as well developed as they are is because the successful solution vendors DIDN’T wait around for some entity to deliver a standard. Instead, they adopted the retail side business requirements as the de facto standard for sales teams working with that retailer.
In general I think the other comments here have it right. It takes time, and training that often is not done. However, I still stick with the fact that goals are not aligned. Many merchants see themselves directly rewarded by bringing in trade promotion dollars. Most vendor sales forces like them, too as an expedient and low maintenance method for satisfying a customer and “buying shelf”. As long as the practices are rewarded in these pockets they will remain entrenched. Right now, most of the players who would be asked to do the input and analysis would get limited benefit (they think) from a lot of work, so they do not do it. This is one of the usual gaps between marketing and sales. In general it is marketing that wants this analysis both to benefit financial results as well as increase movement. However, when the top lines meet goals and sales or merchants keep getting rewarded for this behavior, the gap widens and not much is done. Where finance, marketing and sales are aligned, then the analytics work and work well. So, it is little surprise we see them first in the big boys as noted. Times like these will drive the adoption down the ladder and more broadly when and if companies align on the idea and don’t react to it as more busy work.