Unlock productivity and efficiency with Manufacturing Insights

The majority of manufacturers today have already done the most apparent changes to streamline their operations with traditional methods to enable as much productivity out of their operations and supply chains as possible. In today’s uncertain and growth-challenged environment, to do even more with less, manufacturers must look at ways to boost the productivity and profitability of their operations.

One significant area that manufacturers have not yet optimized is their own data to maximize value. Manufacturing plants generate enormous volumes of data, but historically manufacturers have lagged behind other industries and failed to make use of this humongous amount of potential intelligence. As the famous saying among manufacturers goes - “Data, Data Everywhere, but Not a Drop of Insight”. With Industry 4.0 / IIoT adoption, the quantity and diversity of manufacturing data have grown exponentially, but the ability to make it beneficial has not. Even today, manufacturers lack a unified system to orchestrate vast amounts of information inflows to ingest, transform, and combine diverse data streams into a detailed matrix-like view.  

With compute power becoming cheaper and rapid advancements in advanced analytics, manufacturers today need data-driven orchestration frameworks that will bring together artificial intelligence (AI), machine learning (ML), and cloud storage to ingest, aggregate, and transform all types and sources of data into a universally usable format. This will unleash the full potential to uncover new ways to optimize manufacturing processes across operations and the supply chain.

Manufacturers who have designed a successful data strategy to succeed have ensured to establish the below measures:

• Strategy is driven from the top - A well-defined data-first strategy and clear transformation roadmap
• Investment in data collection – Consistency in data collection and reusability
• Understanding ROI – Quantifying the financial impact of analytics-led improvement is important

Successful manufacturers have broken the Pilot Purgatory barrier and moved to the next stage, that is, operationalized various analytics models to scale for continual value benefits realization.

To achieve a successful, scaled deployment, we need to establish the processes listed below:

Microland’s Data to Outcomes framework is designed keeping the above-mentioned considerations in mind. Our analytics framework prioritizes achieving the business impact by creating operational data models powered by machine learning and a seamlessly connected data fabric to enable contextualized data-driven decisions.