Beyond Better Foods - Einstein Analytics Case Study

The Challenges

Beyond Better Foods are enjoying some of the fastest growth in the food & beverage industry, as consumers seek healthier lifestyles. With the additional surge in demand due to the current Covid-19 pandemic, brands, distributors and retailers need to increase efficiency and optimize supply. This presented new challenges; First, besides new products, the market demands a new way of working with retailers: a supply model in tight alignment with market data that operates in real-time. Second, consumers expect a brand that keeps increasing value as they increase their budgets.

The Wish

Beyond Better Food wished to unlock their data and gain fast, actionable insights into their distribution, promotions and margins to optimize efficiencies across the board. This desire was magnified due to the covid pandemic, demanding data-driven responses and their emerging direct to consumer offerings. Beyond Better Foods was looking to reshape their commercial strategy, by tracking profitability differences between product families and trade partners. Their final wish was to empower sales negotiations with distributors through insights and guidance on increasing lot sizes per order, to reduce shipping costs & drive higher sales, ultimately understanding positive or negative factors to use during distribution channel conversations.

The Solution

VRP helped Beyond Better Foods move away from complex, time-consuming spreadsheets and on to Einstein Analytics providing unified data from discrete sources and the ability to manage data through automated workflows to provide detailed insights and predictive analytics capabilities. Business critical data is readily available in reports embedded visualisations and Einstein dashboards enabling them to make key strategic decisions directly from a Salesforce Object as they enter negotiations with their supply chain and distribution channel. Optimising commercial strategies by generation future models through Einstein capabilities enables them to rapidly adapt to market conditions, however unpredictable. Beyond Better Foods were able to rapidly deploy their solution in a matter of weeks, due to close collaboration with the VRP Consulting team.

The Stages VRP worked with Beyond Better Foods to unlock their data using Einstein Analytics in three stages, which was followed by extensive training to enable their team to fully understand and evolve their instance of Einstein Analytics. The project started with the identification of value-creation goals, through interviews with internal stakeholders to untap hidden opportunities and mine existing datasets. The next step involved creating of a proof-of-concept to validate the value of Einstein Analytics from dashboards to predictions in a Salesforce sandbox. The final phase included fine-tuning datasets as Einstein assets were deployed in the production platform.

The starting position was a complex system of Microsoft Excel spreadsheets that collected both point-of-sales data and marketing spend. VRP used Einstein Analytics Data Manager to create a single source of truth. First, adding Salesforce connections to own client’s local and external objects custom related to distributors, categories, and supply chain orders. Second, transforming, grouping and joining the aforementioned sources together into datasets, ready for fast analysis of business metrics, such as distributor sales, sales velocity, using Einstein Dataflows and Recipes.

The final step required VRP to build an interactive multivariate analysis with Einstein Analytics Studio. The Einstein dashboard consisted of SAQL Lenses, obtaining statistical measures from the pricing list and trading terms, and interactive steps that upon selection switched measures and groupings.

The Future Further releases will include a VRP developed AI Story within Einstein Discovery, with the goal of predicting discount levels by lot size and easily explaining the factors behind each prediction. VRP followed a full data science workflow within Einstein Discovery based on the client’s dataset: training, building, validating and deploying an advanced machine learning regression model. VRP deployed the model inside the opportunity object as a prediction field since Beyond Better Food's model showed strong performance in terms of r-squared, residuals and mean square error. Despite the sophistication of the AI workflow, only clicks were needed without code or Jupyter notebooks at all.

The future will also include expanded AI predictive modelling, predictive actions, alerts and triggers as well as geo mapping, location insights, recommendations and remote connections to relational databases for real-time competitive intelligence. stages

The Result

As a result, Beyond Better Foods were able to identify the most effective campaigns, and best scheduling options, based on process velocity and align this data to the performance of their supply chain. They could focus the analysis on profitability, price distribution or discount allocation and assess the potential impact of a specific segment, product item, channel or distributor name in a single dashboard accelerating the transparency and decision making.

Company Profile

Beyond Better Foods is a privately held New York-based food startup, which has been making products to support consumers looking to eat healthier since 2012. Beyond Better Foods is passionate about creating products that make their customers feel as good as the foods they consume. Their products are sold in 10,000+ stores across the USA.