As my previous post discussed, we were able to deliver immediate impactful data through enterprise APIs for our clients’ to integrate into their solutions. This proved powerful and relatively simple for solutions made from scratch.
Some of the biggest demand for our capabilities here at FoodEssentials comes from the manufacturers side of the industry. Many might think manufacturers actually make a point to omit product data from their products but in fact, there is a growing trend of transparency from this group.
Raw product data quality strives to reach a said percentage of accuracy for each individually entered “raw” data field, such as each individual nutrient, their units of measurement, the ingredients, the brand and manufacturer and size and weight (to name a few). Efforts are focused on measuring, and then improving, the accuracy percentage of each raw data field. We measure accuracy using sampling and statistical distribution for each field.
In this post we explore some of the different use cases for the data and the specific data needs and how the data differs between use cases. When looking at use cases for CFPD it’s important to consider both internal and external use cases to clearly understand the dramatic variety in product data requirements and the consequent need for a holistic approach.
We often get asked why our job is so hard and why more people aren’t doing it or haven't done it yet. Product Data analysis and food labeling can’t be that hard, can it? Our best customers are those who’ve tried our job but quickly realize it’s more challenging than they thought.
At the center of nearly every conversation I have with our customers and other leaders in the industry is the topic of Product Data Initiatives, specifically Consumer Facing Product Data (CFPD). As we have discussed in a previous blog post discussing the driving forces of Why the Demand, taking a holistic approach with CFPD can lead to the transparency and personalization the industry is craving. In this introductory video...
At FoodEssentials, we espouse making it as easy as we can for our clients to retrieve our data. As per much of the internet revolution, the exchange of data is of paramount importance with many previous forms of data exchange existing. XML was revolutionary in standardizing data, and lent itself well to sharing data across disparate platforms. In this day and age, JSON is the defacto standard.
For this week's Food Leaders Summit Speaker Spotlight, Ronak Sheth and Anton Xavier, CPO and CEO, respectively, of FoodEssentials, took a moment to discuss the future of the food industry, the Food Leaders Summit, and their session, The Business Case for a Holistic Approach to Retail Product Data Platforms and Transparency, with the Food Leaders. Mr. Sheth has over ten years of experience in software applications, technology, sales, and more, and has helped drive strategic, global initiatives for companies such as Heinz, Johnson & Johnson, and Clorox, just to name a few. Mr. Xavier, co-founder of Food Essentials, helped move Food Essentials from Australia to the US, where it has established itself as a leader in the niche industry.
The Food Leaders: What role does FoodEssentials play in the food industry?
Ronak Sheth: FoodEssentials aims to transform the food industry by connecting manufacturers and retailers around a live view of the grocery marketplace.
Anton Xavier: We call it LabelINSIGHT. It works by supporting retailers and CPG companies with collection and management of consumer facing product data. Basically it allows them access to a transparent view into the data for the entire organization.
FLS: What’s so challenging about consumer facing product data? And why should a CPG company care?
Sheth: The challenge with Consumer Facing Product Data (CFPD) is not so much in capturing the data than it is the infinite and ever evolving way it can be interpreted. The interpretation is not limited to what is written on a package, but also extends to what is not there, such as whether 2 grams of sodium is a low, medium or high quantity given the serving size. While this "meta data" is vast and highly complex, it is a critical component in understanding the latest consumer perceptions and tastes .
Xavier: So we have evolving combinations: regulatory attributes, industry standard attributes, and consumer demand attributes that make the process of collecting and maintaining Consumer Facing Product Data (CFPD) almost unattainable for most suppliers. However, the insights it can provide are well worth the effort to acquire it. Retailers and CPG companies realize the importance of having accurate, up-to-date, and comprehensive data and are pursuing viable solutions with urgency.
FLS: What do you mean by “Package Data?” Inferred Attributes? Regulated Attributes?
Xavier: Package data relates to the product title, brand, nutrients, ingredients, marketing claims, certifications, warnings, and other product details displayed on any packaged good. Sheth: However, when an organization moves towards delivering this “raw” package data for various use cases challenges start to arise. Package data is designed for the single use case of displaying attributes about a product when it is on the shelf, or in someone’s hand. Simply transferring package data to use cases powered by technology does not work. It requires a reworking of the fundamental data structure to take into consideration inferred cpg data attributes. We can help with that.
Sheth: Inferred data attributes reflect the need to standardize product attributes across a range of products. For example, searching for a gluten free product across a category requires a standardized definition of Gluten Free - is it judged by marketing claims, ingredients, warnings, certifications, or all of the above? In isolation this is not a difficult challenge, and one can safely assume that for popular use cases such as ‘gluten free’ suppliers can provide the attribute for all their products. However, when one considers all of the potential use cases, including lesser known emerging trends, the true size of the challenge begins to take shape.
Xavier: Not only do suppliers need to infer a gluten free attribute, but they have tens of thousands of attributes for every one of their products and many of them are considerably more complicated than the gluten free use case. Take for instance the regulated FDA attribute low sodium. In order for a product to qualify it must first pass a disclosure filter which scores products against numerous overall health factors such as fat content, cholesterol and sodium levels. Criteria are further specified based on serving size and product category. Only products that pass the disclosure filter can then be considered for the actual FDA low sodium attribute which sets a ceiling for milligrams of sodium per serving.
FLS: How will the content of your session, The Business Case for a Holistic Approach to Retail Product Data Platforms and Transparency, speak to the transformations happening in the food industry?
Xavier: We’re excited what we plan to present at the Summit. It’s a real opportunity to present the best practices we’ve acquired with LabelInsight, and a use case that will really show CPGs what is possible to do with their data. The session will explore CFPD in more depth and to touch on the difficulties of understanding, presenting, and contextualizing package data. We’ll talk about why consumer facing product data is a necessity for modern retailing and how the need for the industry to adapt is being driven by dramatic changes in the consumer landscape.
We’ll also discuss macro trends towards transparency in all aspects of products- ingredients, processing, environmental impact, etc.Included in that is a very interesting trend: a macro trend towards personalization of products and marketing efforts. We aim to leave the audience with a say in which the industry can respond to those trends and the integral role of granular and ever evolving CFPD attribute assignment.
FLS: What are your thoughts on the Clean Label and Understandable Ingredients trend with consumers?
Sheth: Consumers have become keenly aware of the ingredients in the foods they purchase and as a result the demand for clean labeled products has skyrocketed. Not only do consumers want clean labels, but they are also demanding health benefits, value and convenience from their products. CPG companies need to keep up with consumer preferences.and decipher the 200+K ingredients found in U.S foods today. How will they do that? By mapping them into easily decipherable head ingredient groups based on their functional properties (preservative, sweetener, emulsifying agent, etc.) are more valuable than ever. Food Essentials can help with that.
FLS: Is reformulation the answer?
Xavier: There are clearly many things to consider when looking at reformulating. Taking a data based decision making approach and arming yourself with what is taking place in the "live" marketplace can guide a brand to better and more efficient decision making We’re excited to explore the following ways to do this in our session.
FLS: How has the food industry changed in the last year? Five years?
Sheth: There is a broad consumer shift towards healthier lifestyles, led by a number of key trends. First is the continued mainstreaming of natural products which has led to increased competition. This means that more consumer, manufacturers, ingredient suppliers and retailers are finding it worthwhile to invest themselves in this growing niche. With greater levels of engagement and investment the industry is working hard to ensure the accessibility of healthy, nutritious products to an audience beyond the traditional core buyer.
Further fueling growth are an energetic set of entrepreneurs finding opportunity in new funding options and a rapidly expanding industry. These very same opportunities are enticing a new ‘silicon valley’ and ‘food tech’ approach to innovation to keep pace with quickly evolving consumer tastes and drastically shorter product life cycles.
Human stories and mission-based business are connecting strongly with passionate food tribes and values based buyers adding emotion back to an otherwise rational or habitual buying process.
The overall result of these changes is strong future growth potential in this segment of the food industry. Estimates predict it outpacing growth of conventional product sales by three times, and organic food and beverage sales are forecast to represent more than 13.5% of total sales by 2020.
FLS: What do you hope to get out of FLS2015?
Sheth: The 2015 Food Leaders Summit is a great opportunity for FoodEssentials to present to our data findings and deep market insights to other thought leaders in the industry. We plan to bring our unique philosophy to solving Consumer Facing Product Data challenges to the table. We are also looking forward to hearing new market insights and future trends from some super smart people! It’s exciting!
FLS: Anything else you would like to add?
Xavier: FoodEssentials as a company values debate and discussion about the best ways to solve some of the biggest challenges facing the food industry today. We invite anyone interested to contact us with their thoughts and questions, and welcome the hard questions the industry is facing today.
Talk Big Data and more with Ronak Sheth, Anton Xavier, and other speakers at The Food Leaders Summit 2015. Register here to attend!
The deeper the analysis, the greater the data points. The greater the data points, the more extensive the QA must be. In this series of posts, I will really explore this concept and introduce what I believe are the three unique phases necessary to be confident of your quality assurance process: Raw Product Data Quality, Relational Data Quality and Consumer Facing Data Quality.
All failed product data initiatives that we’ve seen have one thing in common; they were designed to solve a specific use case. With the data captured for an original use case it is then repurposed for other use cases, at which point its limitations become clear. This process of capturing data for a single use case, learning it has limitations when applied to other use cases and then recollecting has been responsible for millions in wasted investment. In this post I will dive deeper into the different use cases and explore the data structure nuances with the aim of demonstrating the need to capture product data holistically the first time around.