Oftentimes, business terminology and data terminology are at odds. What's more, businesses need a way to define various units of measure that aren't tracked in source systems. That's why analytic.li is changing the way manufacturing and distribution companies look at their custom business logic. Custom business logic is the user-defined metadata and unit conversions that defines and translates data into action.
No longer do companies have to conform solely to ERP or WMS system's data fields, with analytic.li they can customize their data to operate exactly how they want. Every company want’s to see their data in the terms they use and they want to transform it into groupings that make the most sense. analytic.li is on a mission to arm leaders to do just that.
User-defined metadata is the ability for end-users to create groupings that don’t inherently exist in their data today. For example, grouping various locations into a region, fiscal year vs calendar year, and/or first day of the week (e.g. Monday-Sunday or Sunday-Monday).
User-defined metadata allows organizations to transform their data to talk about their business in the exact terms they choose and enables groupings to make the data easier to digest. analytic.li makes it easy for users to define their groupings, calendars, and weeks so that the data matches the business.
One key component of how analytic.li enables companies to be more productive, efficient and better deliver for customers is through unit conversion. Similar to user-defined metadata, this is a component of custom business logic that allows a business to define how many units or eaches determine a specific grouping.
For example, let’s talk about this in terms of frozen pizzas.
One Unit = One Pizza
One Case = 12 Pizzas
One Pallet = 24 Cases
When thinking about unit conversions, we take a single unit and transforming that unit into larger groups of how are those units packaged and sold to customers. Most likely, a frozen pizza manufacturer will not sell frozen pizzas individually to Kroger, they will sell them in cases or pallets.
Converting units into larger groupings allows sales and production to speak in the same language. Communication is key to production and monitoring inventory. So it is imperative that sales and production work together cross-functionally to sell and deliver the product effectively. Speaking in the same language is the first step towards successful operations.
So, let’s dig into why custom business logic matters.
Although units are typically sold and priced by the case, units are also priced individually. This is important when it comes to inventory management and cost per unit. The business needs to know how much it costs to make each item individually and what ingredients go into making each item.
Let’s jump back into our frozen pizza example. To make a frozen pizza, we must have the right ingredients: dough, sauce, cheese and pepperoni. To get those ingredients, we have to order them from the supplier at least two weeks before we need them. That’s what we call lead time.
Let’s say that our salesperson Anna, runs up to production and says “Hey, I just sold 1,000 cases of pepperoni pizzas to Kroger and they need them next week. Can we do that?” The operations manager needs to quickly do the math. If we sold 1,000 cases of pepperoni pizzas, then we need 12,000 pizzas by next week.
Next, I have to figure out what I have in available inventory, how many more pizzas I need to produce, and if I have the materials to produce the pizzas that were sold. Typically this process can include many manual processes including, printing out Excel spreadsheets, a lot of highlighting and a lot of scribbled math to determine if we are able to produce the order with the inventory and ingredients on hand.
Siloed systems (e.g. Labor, ERP, WMS, Finance, Budget) often leads to question marks in real-time availability of inventory and materials. While an ERP might track inventory, materials, sales, and lead time, it won’t bridge the gap in these metrics and provide additional insight. For example, an ERP will not tell you how many materials it takes to produce one unit, case, or pallet of inventory. All it’s going to tell you is the total quantity available.
It would be better to be alerted when it’s the right time to order more materials, when to ramp up production, and/or when to bring in additional staff to complete an order.
Tracking Inventory with analytic.li
So, how does analytic.li fit into all of this?
analytic.li is the thread that binds all of the layers together. With analytic.li, businesses are enabled through custom business logic and aggregated data to optimize their operations. There is no second-guessing which materials are on hand and how much inventory is available. It also enables teams to better communicate cross-functionally with unit conversions and custom business logic in place, so everyone is speaking the same language.
Custom business logic is a piece of the thread that makes analytic.li so valuable for manufacturers and distributors. We take out the manual calculations and data wrangling from your business process and take a streamlined approach to ensure all levels of the organization are aware of possible bottlenecks in production.
That's Why We're Here
At analytic.li, we uniquely understand the need for manufacturers and distributors to utilize custom business logic to optimize their operations.
With our first-ever, cross-functional labor efficiency and worker productivity platform we break down data barriers and organizational barriers to set up operations managers for success. This means businesses can arm their leaders with real-time insights to manage productivity, profitability, efficiency and customer delivery by alerting leaders of positive or negative changes throughout the day.
If you’d like to learn more about ways to proactively monitor your income statement or discuss how analytic.li will work for your organization, reach out to us. We’re eager to connect with you. If now is not the time to consider new software but you liked what you read here, subscribe to our blog below.