This article, by Justin Lokitz – a thought leader in big data, provides an excellent overview of three distinct business models using big data. Any one of which, or a hybrid, can be incorporated in a CPG category manager’s analytics process. The article is worth a separate read but the main points are summarized, and applied to CPG, below:
It goes without saying, innovative, sustainable Big Data Business Models are as pervasive and sought after as they are elusive (i.e. “data is the new oil”). For every startup that designs and implements what amounts to a devilishly simple and effective big data business model (see any social network), perhaps changing the entire landscape with it, there are literally hundreds (if not thousands) of larger, more mature companies looking for ways to monetize their own big data in the hope that they can capture new revenue streams (and compete effectively in the future). Of course some of the larger, mature companies have done quite well in this regard. Apple (40 years old) and Amazon (20 years old), for instance, have vastly different business models. Yet, both companies have built solid business models around big data; both use big data to present to consumers products and services that might be relevant to them. Similarly, Netflix and Pandora, 18 and 15 years old respectively, designed brand new big data business models around understanding and creating value for customers in ways that seemed like magic at the time. So, what’s behind these business models? And, are there other business models that might help other (mature) companies create, deliver, and capture value using big data at the core? The answer (to both questions) is simple: it’s all in the value proposition.
He further states in his introduction:
“Fall in Love with the Problem, Not the Solution.” As simple as this quote is it speaks volumes when considering how mature companies tend to think about utilizing their own big data stores to create new business models. That is to say most mature companies first ask, “What big data do we have today?” followed by, “how might we sell this data?” Looking back on my favorite aforementioned quote, you can probably see the discrepancy here: most mature companies believe there is some mythical marketplace where they can simultaneously sell their big data whilst not pissing off their customers. These assumptions are more often than not wrong. Moreover, while there are LOTS of “problems” to fall in love with when it comes to big data business models, in order to provide some focus, this post highlights three categories of big data business models based on their value propositions and customers (e.g. DaaS, IaaS, and AaaS respectively).
DaaS hinges on a value proposition for supplying large amounts of processed data with the idea that the customer’s job-to-be-done is to find answers or develop solutions for their customers.
For CPG companies partnering with large retailers as a trusted supplier – this usually begins with the POS/Inventory data supplied at the vendor level or, where appropriate, the category level.
The granularity of data can be daily or weekly and provide historical data – usually 104 weeks. While the author speaks in general terms about marketing data to monetize it (in fact the entire article has an eye toward this), CPG companies cannot sell retailer supplied data. This does not mean that you, as a CPG category or sales manager cannot monetize the data. For you – monetization occurs when you use analytics to gain insights to share with your buyer(s). The goal of this activity, of course, is to flank your competitors within the category, increasing your brand’s market share within the retailer ecosystem.
Part of the Vortisieze service offering is providing a fast, clean, single source of the truth, aggregated data and the analytics tools to empower you to produce your own insights.
- Information as a Service (IaaS)
IaaS focuses on providing insights based on the analysis of processed data. In this case the customer’s job-to-be-done is more about coming up with their own conclusions or even “selling” an idea based on certain information. Additionally, IaaS customers don’t want to or do not have the resources to process and analyze data. Rather they are willing to exchange value for analysis from trusted parties. Unlike the DaaS business model, which is about aggregation and dissemination of lots of processed data for customers to create their own value propositions from, the IaaS business model is all about turning data into information for customers who need something – and are willing to pay for something – more tailored.
Because we have category manager DNA in our company’s DNA, Vortisieze can meet this need by providing ready-to-use analytics, dashboards such as Business at a Glance (BaaG) for example.
- Answers as a Service (AaaS)
AaaS is focused on providing higher-level answers to specific questions rather than simply the information that can be used to come up with an answer. CPG companies who implement the AaaS business model do so in gain answers to answer specific questions.
This business model, as you might guess, is the top of the pyramid when it comes big data. The key with this business model is that given the CPG company’s ability to create real, trusted value in the answers it provides to buyers, buyers take note and value the insightful answers provided.
When a category manager partners with Vortisieze by asking very specific questions needing answers (remember strategy drives questions), we can provide answers to your most important questions.
Vortisieze technology, unlike rigid DSRs or yesteryear, provides pliable, and rapid, solutions to meet your analytics needs.
Contact us today to discover how.
About the article author:
Justin Lokitz is Strategy Designer & Managing Director at Business Models Inc. San Francisco
Source: Exploring Big Data Business Models & The Winning Value Propositions Behind Them