Seven reasons to choose over building your own solution

1. Speed to value

Building a solution that meets minimum reporting needs can take 18+ months and multiple FTEs You can get up and running with in weeks
These projects require custom data connections, complex harmonization engines and develop custom dashboards. Inhouse solutions inherently divert limited resources away from other business critical projects in your development pipeline. Set up, training and use case adoption do not require any internal development from your IT team. Some retailers can be implemented in days, and full implementation rarely takes more than twelve weeks. We start to train and engage your user communities on day one.

2. Unlocking the art of the possible for your user communities

From the C-suite to analysts, your internal teams often don’t know what to ask for from IT Alloy’s deep expertise in retail and supply chain data applications opens new use cases
Business intelligence projects frequently focus on reporting only. Innovative workflows and predictive analytics don’t get built because business users just don’t know what’s possible. They can only ask for what they know is possible. We’ve developed best-in-class predictive metrics, end-to-end workflows and proprietary forecasting models. Our consultative customer success team shows your user communities how to apply them to tackle their most painful challenges, quickly driving adoption.

3. Workflow integration

Analytics tools should help users sense, as well as prioritize, diagnose and solve problems Combining flexibility and best practices, is designed to support workflows from start to finish
Power BI, Tableau and Looker aren’t equipped to support all the steps in these workflows. Users have to turn to Excel or other tools for more granular, exception-management and collaboration. Constant tool toggling frustrates and slows down non-technical doers. A variety of user communities can not only see issues within the application, but work together to resolve them, too. is commonly used by sales, marketing, merchandising, planning, inventory management and customer supply chain to name just a few teams.

4. Delivering insights to partners in their language

Retailers often trust their automated replenishment algorithms and forecasts over their suppliers helps brands point out the issues, like lost sales, unproductive inventory and trade spend waste
However, those algorithms can get it wrong. To fix the problem, your team needs to use the same KPIs, metrics, calendar and product or location codes as each partner when delivering insights. This requirement adds significant complexity to your plate when trying to build internally. Our harmonization model allows users to seamlessly toggle between individual retailer calendars and metrics as well as your internal preferences. That way, the recommendations you make are backed by insights that make sense to your partner.

5. Total cost of ownership

Big development projects tend to run over budget and cause ongoing maintenance headaches is a cloud-based Software as a Service with no hidden costs
You may also have to hire expensive professional services to implement new processes and train your users. Even if you nail all that, complex analytics tools require a lot of developer maintenance, particularly on retail data feeds that frequently change. Your subscription includes continuous innovation, internal and external data pipeline maintenance, user training and dedicated customer support. There’s no need for expensive third party professional services and your IT team can focus on other critical projects.

6. Open and extensible architecture

Simply building and maintaining data pipelines across all your trading partners is a tall order can be a design partner for your organization’s digital transformation
To make this data usable for all the types of analyses your business teams need, you must also harmonize and visualize it. Even when all of this architecture is stood up, most companies struggle to move past traditional reporting, missing out on predictive opportunities. Your internal developers can leverage the Data Platform to pipe harmonized data, predictive metrics, forecasts and more into other systems. Examples include planning, retail execution and trade promotion management solutions.

7. Integrated, scalable platform

Even the best retail analytics point solutions reinforce functional silos is a central nervous system for your finished goods supply chain
They aren’t designed to scalably meet the needs of teams like marketing, supply chain and planning in addition to sales. They also fail to integrate with planning software, doing nothing to address the gap between planning and execution While most customers start by bringing in retailer POS and inventory data for retail analytics, they get compounding value by adding ERP data (sales orders, inventory, purchase orders and transfers) and forecasts (internal, retailer) to their subscription over time. breaks down silos and brings unmatched agility to consumer goods companies.