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The Digital Evolution of a Lean Manufacturing Ecosystem: The Turnaround from Waste to Profit

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The Digital Evolution of a Lean Manufacturing Ecosystem: The Turnaround from Waste to Profit

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As leaders in the tech space, we owe it to our respective industries to revolutionize every component in our process not only to maximize profit but also to minimize waste. As the fundamentals of business and our own experiences have taught us, controlling waste often leads to profits and the pursuit of profits requires curtailing waste, giving the entire equation a dual purpose that every leader pursues to maximize profits.

Using the Digital Bridge to Close the Lean Gap

In manufacturing, the risk of waste threatens to drag down a business through multiple trajectories. Whether it is defective parts or overstocked items, every lost prospect to save and optimize results is a waste of time, resources, or opportunities. In numbers, this amounts to around 30% of manufacturing costs, but when you list the hidden costs ranging from the loss of market share and competitive mileage to the deterioration of business health, the risks are too severe to ignore.

This is where introducing Lean Manufacturing’s philosophy and methodology to your business makes all the difference. But this is only the beginning. As a tech leader committed to providing clients with the value and rewards of inculcating this philosophy into their digital structure, I use this space to discuss how efficiency and profitability are natural derivatives of a manufacturing unit dedicated to the tenets of Lean. More importantly, I also demonstrate how harnessing the power of digital technology remains a crucial move that unlocks its full potential.

Core Principles of Lean Manufacturing: The Fundamentals of Operational Brilliance

Lean manufacturing is a lot more than just a set of tools put to work to eliminate waste and maximize profits. It is a way of doing business and setting up processes so that every working component and stakeholder of your company adheres to its five principles.

Identifying Value: The rapid evolution of customer needs makes it imperative that manufacturing leaders and important stakeholders in a business give customers the right reasons to assign value to their products. Once these elements are defined, the next step is to dive deep into process structures to identify the components that do not contribute to this value or even take value away from it.

Mapping the Value Stream: From the raw material to the finished product that reaches the customer, this entire journey represents the value stream of the product lifecycle, and mapping the value stream requires visualizing every step and identifying the entire flow. Next comes identifying the seven wastes of lean, and ensuring that these wastes (overproduction, waiting, transportation, over-processing, inventory, motion, and defects) do not eat into your resources and dent efficiency.

Creating Flow: Ensuring a seamless flow throughout the production process, identifying bottlenecks to introduce measures ranging from process streamlining to layout optimization to improve output time, and setting up a pull system where reducing inventory and minimizing waste are prioritized are goals to pursue and meet.

Pull System: When it’s the customer who creates demand, why should a production schedule follow any other system? A pull system is customer-driven. It reduces arbitrary production and enables manufacturing lines to quickly respond to customer demand without the need for overstocking or the risk of stockouts.

Continuous Improvement: Lean is a journey that requires a culture of improvement and empowerment so that every employee is an informed and willing participant. This induces a work structure where incremental changes keep pouring in from various quarters, experimentation remains key in an organizational will to move forward consistently, and even small wins are treated as big ones because every win contributes to the goal of Lean.

How Digital Transformation Amplifies Lean Manufacturing Impact

While Lean principles have for long been proven impactful, the advent and evolution of digital tools have given them a powerful set of tools to further amplify this impact. In harnessing new technologies, this impact can be even more pronounced in terms of agility, efficiency, innovation.

Real-Time Data Visibility: While traditional Lean relies on manual collection, verification, and analysis of data, digital tools help eliminate the problems of reactive decision-making and delayed insights. With sensors feeding constant data on performance parameters, even the slightest anomalies can be detected immediately, thus making tools like IoT sensors, data analytics platforms, and ERP systems your door to real-time insights.

Predictive Analytics and AI: While traditional Lean focuses on reacting to inefficiencies and anomalies, AI and predictive analytics put you ahead of these delays and help you move to a proactive environment where you can anticipate issues and prevent them in time. Machine learning algorithms identify issues by analyzing historical data on production patterns, prevalent disruptions, sales trends, market data, and even social media trends to prepare you in advance.

Automation and Robotics: As human-driven tasks become repetitive, they are more prone to error due to fatigue. Automation and robotics take over such tasks and build processes where error-free efficiency is easier to accomplish. Robotics delicately handle precise assembly lines and components, while automation solutions handle material supply and inventory management. This also relieves human teams from monotonous processes, giving them the time to use their creativity and focus on more valuable tasks such as innovation, quality control, and system improvements.

Collaborative Platforms: Lean manufacturing provides optimal results when collaboration and communication systems between departments and stakeholders are equally robust. Digital tools like specialized project management platforms facilitate real-time collaboration and information-sharing, in turn accelerating problem-solving and improvements. Now, quality issues can be resolved on the go and real-time data and collaborations can minimize disruptions and reduce adverse impact on production.

At Parallel Minds, We Know Your Teams Deserve a Digital Lean Manufacturing Ecosystem

Eyes and Ears on the Manufacturing Floor: Sensors, AI algorithms, and even the products are all potential data-rich components in your manufacturing ecosystem. A digital upgrade will give your employees the advantage of predictive maintenance, bottleneck identification, and promote optimal asset utilization. All these factors will reduce exhaustion due to downtime and cut down on workforce fatigue brought on by manual analysis and adjustments.

Transforming Data into Actionable Intelligence: Your team deserves a robust analytics platform to depend on for aggregated data from various sources to enable the uncovering of hidden insights, predictive patterns, and correlated risks and opportunities. Advanced analytics and AI can deliver to them the information they need to improve quality, delivery, efficiency, and affordability, giving them the tools they need to do justice to their roles as primary stakeholders driving business success.

Giving Your Business a Digital Backbone: Your inventory, production, sales, finance, and other essential departmental components can now be offered on a cloud-based ERP system that your employees and managers can access promptly to track key metrics and arrive at data-inspired conclusions. The scalability factor can further enhance innovation through experimentation, giving your workforce the chance to pursue continuous improvement.

Precision and Efficiency: In the digital age, your workforce is looking to move beyond repetitive, mundane tasks that leave them physically exhausted and mentally fatigued. As leaders, we need to ensure their physical and mental health by automating hazardous, monotonous tasks and moving them on to more value-driven duties such as innovation and problem-solving. Robotics and automation solutions can drive this change in your organization.

Team Connectivity: Workers thrive on effective communication and real-time collaboration that enables different departments to work as a single unit, delivering results and solutions while working towards the common goals of transparency, improvement, and success. A collaborative workforce is an empowered workforce. As leaders, we owe our employees a work atmosphere where digital tools and project management platforms enable the free flow of information and insights.

Integrating the right mix of digital tools to align with Lean principles empowers your workforce, gives your manufacturing ecosystem tools and insights to innovate and improve, and introduces your business to a new age of efficiency and agility.

Get in touch with the Parallel Minds today to know how we can build for you a competitive manufacturing landscape driven by digital tools and solutions.

AI’s potential to reshape the manufacturing landscape through the optimization of every operational component makes it a potent business solutions partner. At Parallel Minds, we recognize every element in an impressive lineup and provide our manufacturing clients with every AI advantage to propel their business forward. .

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About the author

Parag,-CEO-Parallel-Minds

Parag Bihade, Founder and CEO of Parallel Minds, and co-founder of DATASMITH AI led by Kirti Bihade, brings 25 years of extensive experience in software programming and a passion for data and digital transformation.

Parag leads a team dedicated to empowering mid-sized manufacturers with innovative tech solutions. @Kirti Bihade – Team Parallel Minds is pursuing her Ph.D in AI and has extensive experience in Data Science, Machine Learning, and Data Visualization.

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Manufacturing Intelligence with Azure AI and Microsoft Fabric: Your Parallel Minds Partnership

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Manufacturing Intelligence with Azure AI and Microsoft Fabric: Your Parallel Minds Partnership

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The transformative power of AI is poised to take on the world. Already, no industry goes untouched by this driving force that navigates every business and industrial landscape to provide brands with intelligent solutions to every development, management, and operational problem.

In manufacturing, AI has created new pathways to business intelligence, optimizing processes both on and off the shop floor, identifying and even helping in creating opportunities, and assisting the leadership with real-time data to make informed decisions that increase revenue and market share.
Harnessing this power and leveraging every advantage on the list, however, requires some expertise and experience, and this article will explore just how Parallel Minds can be your partner in deploying AI solutions to help your manufacturing business add efficiency, innovation, and growth, with Azure AI and Microsoft Fabric forming the backbone of this digital augmentation.

Azure AI: A Gateway to Intelligent Manufacturing

A comprehensive set of evolving tools and services to help the manufacturing sector, Azure AI is a formidable platform that helps build, deploy, and manage breakthrough AI solutions.

End-to-End AI Abilities

Comprehensive Solutions: From preparing data to modeling and deployment to management, Azure AI gives you a comprehensive lineup to begin your AI-assisted journey.

Flexibility and Scalability: From small manufacturers to large enterprises, Azure AI works for all sizes of manufacturing businesses and is adjustable in terms of pricing and resources.

Security and Compliance: Azure AI is built on Microsoft’s cloud infrastructure, and its high security and compliance standards ensure absolute protection of data.

Leveraging Data

Machine Learning: Azure Machine Learning gives your team the ability to build, train, and deploy customized models customized to meet the needs of your business. From predictive maintenance to demand forecasting, its flexibility enables the creation of specific models to meet specific needs.

Cognitive Services: Azure AI is capable of extracting data, information, and insights from a range of channels and file types including images and videos as well as natural language processing. In turn, it can also deliver these insights and information through chatbots.

Bots and Virtual Assistants: Intelligent virtual assistants and peppy chatbots can now handle your customer service, provide support to employees, and reply to queries with the information it has access to. Your employees can now give up these mundane functions and move towards more valuable tasks in the business.

Manufacturing Use Cases

Predictive Maintenance: Analyzing sensor data in your machines gives Azure AI insights into any anomalies or upcoming maintenance requirements. This information assists proactive maintenance and cuts down on downtime, thus optimizing production.

Quality Control: Azure’s computer vision systems, thanks to its cognitive services, can monitor your production and inspect your products, highlighting defects with speed and accuracy. This improves product quality, reduces scrap rates, and keeps defective products from reaching the market.

Supply Chain Optimization:The thorough analysis of supply chain data helps in demand forecasts, the identification of bottlenecks, and optimal inventory. This improves overall efficiency, reduces waste and overstocking, and increases resource mileage.

Customer Service: The Azure Bot Service helps set up chatbots and virtual assistants to answer queries, resolve issues, provide information from available data, and even process orders.

Bridging the gap between raw data and helpful insights, Azure AI is a testimony to the amalgamation of AI innovation and business intelligence.

Microsoft Fabric: A Unified Data Foundation

End-to-End Analytics

Breaking Down Silos: Microsoft Fabric creates a cohesive environment with the integration of data, engineering, warehousing and analytics in a single space that does not require multiple tools. This simplifies the tech stack and reduces spending.

Data Lakes, Warehouses, and Lakehouses: Flexible storage tiers allows for diverse data types and structures. Fabric can seamlessly handle structured and unstructured data, making it ideal for the entire range of systems from ERP to IoT.

Real-Time Analytics: Data streaming and real-time processing support helps your team get their hands on live insights and make decisions on the go, making for a more agile work environment.

Seamless Data Flow

Simplified Data Feeding: From in-house databases to SaaS apps, Fabric offers effortless connections to a wide range of data sources so your AI models have access to the most updated information.

Intuitive Data Transformation: Cleaning, transforming, and enriching your data is easier and more impactful with Fabric. This analysis-ready data reduces the need for coding, saving effort, time, and resources.

Data Governance and Security: Compliance and data security are an integral part of Fabric’s protective abilities, giving you a robust governance and security platform.

Collaboration and Insights

Shared Workspaces: Fabric enables seamless collaboration by creating a highly engaging workspace for employees to analyze data, share insights, and make decisions as a team.

Intuitive Dashboards and Reports: Teams across various departments can track KPIs, visualize insights, and forecast trends with the help of custom dashboards and intuitive reports.

Self-Service Analytics: With Fabric on board, the IT team can breathe easy, thanks to the integration of self-service tools that help business users access data and develop insights without burdening the IT team with their requests.

The Microsoft Fabric Advantage of AI in Manufacturing

Accelerated AI Development: Data streaming, robust analytics, and a collaborative and integrated environment leads to accelerated development, deployment, and maintenance of AI models.

Improved Data Quality: Clean, enriched data ensures that the data your AI models work on is potent. This leads to valuable insights and accurate forecasts.

Enhanced Collaboration: Cross-functional, interdepartmental teamwork is easier with Fabric, thanks to the seamless collaborative platform it provides stakeholders across the organization.

Microsoft Fabric offers a solid foundation upon which you can build a highly impactful AI-powered manufacturing business, and we at Parallel Minds comprehensively harness the platform’s end-to-end solutions to deploy the transformative abilities of AI.

Parallel Minds: Empowering Your Manufacturing Business with the Power of AI

AI’s potential to reshape the manufacturing landscape through the optimization of every operational component makes it a potent business solutions partner. At Parallel Minds, we recognize every element in an impressive lineup and provide our manufacturing clients with every AI advantage to propel their business forward. .

Predictive Maintenance: The analysis of data provided by sensors in your machinery predicts potential anomalies and prepares your operations for downtimes. This eliminates surprises, introduces advanced maintenance schedules, and prevents costly downtimes, all due to AI algorithms.

Quality Control: AI-enabled computer vision tools can inspect components and finished products with a lot more accuracy and speed than human quality control personnel. This helps speed up the QC process while leveling up on accuracy. More importantly, collected data is generated and stored automatically for future access.

Supply Chain Optimization: With AI in your arsenal, you can use demand forecasting to anticipate demand fluctuations and optimize inventory to ensure that you never run out of the right products and overstock the wrong ones.

Process Optimization: AI, with the help of the power of analytics and large amounts of data, can zero in on bottlenecks and identify risks and opportunities to increase throughput and resource mileage.

Innovation Specialist

Product Development: AI uses insights gathered from customer data, market trends, competitive breakthroughs, and social media influence to identify new needs and streamline plans for product development.

Personalized Customer Experience: AI’s personalization capabilities, emerging from the analysis of customer behavior and individual preferences, assist offerings such as personalized recommendations and tailored experiences, thus instilling loyalty and boosting sales.

Data-Driven Decision Making: Leaders can put to use insights and recommendations powered by AI to make strategic decisions based on predictions emerging from real data.

Partnering with Parallel Minds

As an experienced tech services provider with expert teams leading every transformation, Parallel Minds is at the forefront of understanding the power of AI deployments, bridging the gap between business needs and manufacturing tech upgrades to offer workable, efficient, and cost-effective solutions.

Parallel Minds with a center of excellence in Microsoft Fabric, Data Science, and Generative AI is an ideal partner for data transformation journey. Reach out to our team to book a discovery call today!

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Star and Snowflake: Performance Optimization in Data Warehousing

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Star and Snowflake: Performance Optimization in Data Warehousing

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Performance optimization is a crucial and integral part of data warehousing. Organization of the data in relation to its schema is a critical aspect that cannot be overlooked. We’re talking about a massive amount of data that needs to be analyzed and effectively presented at a tremendous speed to help you deliver business results.

Hayley, a seasoned data analyst, is running a complex query that has been spinning against her company’s massive data warehouse for what seems like forever. She faces a deadline, and the loop traps all the insights her leadership requires to make critical decisions.

This scenario is a common one for analysts and businesses navigating growing volumes of data in situations where every piece of insight matters. The problem behind these dead ends and delayed insights could very well be the structure of your data warehouse and how efficient or inefficient it is at extracting insights.

In this article, we will explore the two prevalent schema types, Star and Snowflake, and present a case showcasing how each schema contributes to noteworthy performance optimizations.

The Critical Role of Data Warehousing Schemas

The simplest way to explain this is to compare a data warehouse with a library and think of how those vast amounts of information in a well-stocked library would prove useless without a well-functioning catalog system that helps anyone walking into the building find the book they need. The library is your data warehouse, the catalog system is the schema, and the book is the specific data you need.

In data warehousing, choosing the right schema is a strategic technical decision.

  • Schema defines how data is stored, organized, and retrieved.
  • Bridges the gap between complex raw data and action-friendly insights and visual reports.
  • Ensures accessible data, efficient query runs, and quick and accurate insights.

Without an efficient schema in place, a host of problems arise.

  • Scattered data results in slow queries where even simple results could get lost in a cascade of joins and calculations.
  • Redundancy is a possible data hazard too, with data duplication that bloats the database and derails performance.

Your choice of schema impacts efficiency, performance, and the very value you can derive from your hard-earned data.

Understanding Star Schema

Key Characteristics of Star Schema

  • A central fact table holds the measurable or quantitative data.
  • Dimension tables provide the descriptions or context for these facts.
  • The intentional denormalization of dimension tables, i.e., redundant data, to simplify queries.
  • Simple relationships between the fact table and dimension tables accommodate straightforward queries and simple understandings.

Strengths of Star Schema

  • The simple structure of star schema means it is easy to design, implement, and understand, enabling even non-technical users to get on board and write basic queries.
  • Denormalized queries mean fewer joins and, therefore, quicker query executions. In dashboards where speed is crucial, star schema structures deliver great results.
  • When the relationship between facts and dimensions is clear and simple, a star schema data model works efficiently.

Weaknesses of Star Schema

  • Denormalized dimension tables lead to data redundancy, and this duplication increases storage costs, particularly for large data warehouses.
  • Updating data in a denormalized dimension table requires changes across multiple rows, which is confusing, time-consuming, and error-prone.
  • The simplicity of the star schema prevents it from supporting complex and nuanced analytical queries that require granular relationships with dimension tables.

So, while Star Schema’s simple structure is a great starting point for data warehouses, as volumes grow and analytical needs grow more complex, it falls short due to inflexibility and data redundancy.

Understanding Snowflake Schema

Weaknesses of Star Schema

  • The fact table serves as the core and stores the relevant quantitative measurements or metrics.
  • As a key difference, the dimension tables in this schema are normalized and broken down into multiple related tables.
  • Normalization leads to a parent-child relationship between tables with the creation of a hierarchical structure within dimensions.
  • The normalization process assists in complex relationships between the fact table and dimension tables, and even within the dimension tables.

Strengths of Snowflake Schema

  • The elimination of redundant data means large data warehouses now spend significantly less on storage, a financial advantage for data-intensive businesses.
  • Normalization leads to easy updates and modifications, where only one place requires changes that are then reflected across the structure.
  • Granular relationships support complex queries and ad hoc analysis, a feature that is valuable in industries where in-depth analysis is crucial for optimization and decision-making.

Weaknesses of Snowflake Schema

  • Normalization leads to complex queries that require multiple joins, a scenario that can be challenging for users unaccustomed to complex query designs.
  • Slower query performance is a risk associated with normalization, and only elaborate optimization solutions like materialized views and strategic indexing can resolve this.
  • The design and implementation of this schema are fairly challenging due to its complexities and require a thorough understanding of the data model and its relationships.

Focused on normalization and data integrity, the Snowflake Schema offers advantages in efficiency and analytic abilities. Query complexities and the resultant impact on performance, however, are factors to consider.

Star-vs-Snowflake-Parallel-Minds

Choosing the Right Schema for Your Business

Bringing to data warehousing processes unique sets of advantages, both Star and Snowflake schemas align with specific data and analytical needs, offering performance, speed, and complex abilities on different levels.

Star Schema: Simplicity+Speed

  • A denormalized structure without the need for complex joins; delivers simpler, quicker results.
  • Indexing and partitioning to improve query performance for frequently accessed data.
  • Prioritizing ease of use to empower non-technical users by optimizing smaller data volumes.

Snowflake Schema: Storage Efficiency+Flexibility

  • Storage savings for cloud-based environments and large data warehouses.
  • Tier management for “hot” and “cold” data.
  • Materialized views and efficient handling of complex hierarchical data structures.

At Parallel Minds, we leverage the advantages of each schema and optimize them to deliver maximum efficiency based on your unique organizational needs.

Partnering with Parallel Minds

At Parallel Minds, we understand just how crucial the decision to choose the right schema is for a business. Our Data Engineers and Scientists are committed to helping you extract maximum value from your data in the most efficient and cost-effective way possible.

Get in touch to learn how the Parallel Minds team can help you introduce performance optimization to your data warehousing journey.

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ERP Data Chaos: Industry-Specific Solutions (Part 2 of 2)

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ERP Data Chaos: Industry-Specific Solutions (Part 2 of 2)

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In Part 1, we introduced you to the signs, causes, and business impact of ERP data chaos. In this part, let’s dive into the solutions to combat the data monster, introduce you to collaborations that will help you streamline and maintain ERP systems, and take action to address your business-specific needs across industries.

Solutions to Tame the Chaotic ERP Data Beast: An Industry-Specific View

Implement Data Governance Policies and Procedures

Impact on a Manufacturing Business: Standardized data ensures that every stakeholder is relying on the same rulebook and speaks the same manufacturing language. Operations-wise, this leads to efficiency via streamlined communication. Cost-wise, it leads to the reduction of costly errors and paperwork-related inaccuracies that lead to resource wastage, reduces bottlenecks, and accelerates production.

Impact on an Oil & Gas Business: Strict data governance is non-negotiable in the oil & gas business, and is required to meet accuracy and timelines. Equal importance is given to asset and maintenance records. In the presence of strict data governance policies, this data can also be put to use as a business growth tool and make strategic business decisions with intelligent data taking the lead.

Impact on a Real Estate Business: With accurate data driving your business components, you can now count on your property listings, business financials, and client information to emerge from a single reliable data source. Your risk mitigation is strengthened too, with airtight contracts, compliant financial reports, and accurate property details helping you avoid legal disputes or win them should they arise.

Standardize Data Structures and Jargon

When every department has a unique data language, ambiguous terminology, and ill-defined formats, these factors contribute to rampant miscommunication. This leads to operational inefficiency and introduces clarity and transparency across the organization. A shared standard vocabulary in a common company dictionary or database ensures that every communique follows the same pattern and adheres to consistency in meanings and formats. Similar terminology reduces confusion, promotes accurate interpretation of data, helps communicate and discuss insights, and accelerates the entire process of making quick business decisions.

Impact on a Manufacturing Business: Collaboration receives a boost with every team across departments understanding one another’s data language, and with better inventory management and supply chain management, your business is now on top of customer demands too.

Impact on an Oil & Gas Business: Since reporting, maintenance, and safety procedures take precedence over everything else in this industry, proper communication ensures that process and equipment data is optimally defined and understood by every stakeholder, empowering them to highlight and address potential hazards proactively.

Impact on a Real Estate Business: On the real estate business front, you can now accelerate deals, empower agents, brokers, and clients with accurate and timely information, and streamline processes and transactions to set up top-notch client service levels, all while reaping the rewards of standardized communication from square footage to the number of rooms.

Conduct Regular Data Assessments and Cleansing

Data quality tends to take a hit over time, with its quality depreciating and its volumes inundated with duplicated and outdated inputs and information. Regular audits double up as quality inspections and highlight flaws and red flags in data before they negatively influence the quality of decisions. Proactive and automated data cleansing cycles safeguard data quality by deleting duplicates and addressing inconsistencies too, thus improving the accuracy, consistency, and reliability quotient of crucial business data.

Impact on a Manufacturing Business: Accurate inventory data helps manufacturing units avoid costly downtimes, fulfill the promise of timely deliveries, and avoid overstocking or stockouts. Marketing teams can target a cleaner audience database with personalized campaigns and aim for higher engagement. When the aim is to capture a larger market share and find the edge to beat the competition, reliable data always helps.

Impact on an Oil & Gas Business: Reliable and accurate data sets drive safe operations, ensuring timely maintenance, preventing downtimes and breakdowns, and prolonging the lifespan of costly equipment. The power of data also inspires operational excellence, adheres to safety and environmental compliances, and helps a business steer clear of fines and legal hassles.

Impact on a Real Estate Business: In a business where accurate property and client data empower agents to provide competitive service and close deals promptly, regular data assessments and cleansing routines offer a strategic advantage.

Invest in Robust Integration and User Training

Your ERP relies heavily on seamless interconnectivity and the key to this is robust integration with critical systems across the board such as CRM, supply chain, and finance. Proper integration influences healthy data connections between every department and team in the ecosystem, allowing them transparency and visibility and driving coordination and business continuity. In turn, when employees receive comprehensive and customized training to empower them as data champions, they guarantee a data-driven business environment where data entry best practices are followed proactively and every advantage is being leveraged effectively.

Impact of Robust ERP Integration on a Manufacturing Business: Smooth dataflows between your CRM and ERP systems in real-time help drive on-target sales forecasts, streamline production schedules, allow adjustments to accommodate market fluctuations, and set up a highly efficient and responsive production environment. Ultimately, this results in optimal customer fulfillment and increased revenue.

Impact of Robust ERP Integration on an Oil & Gas Business: Proper integration of ERP and field data collection systems enables live visibility, immediate identification of anomalies, and real-time assessment of potential risks. Acting as more than just an early warning system, ERP-provided insights also drive optimization maneuvers such as improving well performance and production rates, planned downtimes, and proactive maintenance.

Impact of Robust Integration on a Real Estate Business: ERP integration with property listing platforms provides accurate listing information to potential buyers, amplifies lead generation efforts, and empowers agents to close promising deals with transparency and efficiency well before the competition can contemplate a move.

Impact of ERP User Training Across Industries: Well-trained users are your best line of defense against data chaos and the perfect shield to combat and even avoid data disorder. From the initial steps of data entry and data sourcing to the continued maintenance of the ERP system, empowered and knowledgeable employees secure the quality of your ERP system as a dependable source of information.

Leverage Data Engineering and Data Science

Data engineering and data science provide an outcome-oriented approach where raw data is transformed into actionable intelligence, empowering a business to drive itself forward with accurate, timely, and impactful data-driven decisions. While data engineering teams build robust, scalable, and efficient pipelines to deliver high-quality, clean data flow, data scientists use the power of analytics to extract key insights and build predictive models to further unlock an ERP system’s potential.

Impact Across Industries: In the absence of an intelligent ERP system, decision-making teams may remain oblivious to actionable insights that could transform their business. Data engineering and data science technologies provide seamless data flows to read hidden patterns, identify inefficiencies, forecast trends, uncover potential risks and failures, optimize resource allocation and adjustments, and deliver clear, actionable insights. Across industries, the empowering nature of data engineering and data science helps businesses gain a competitive edge through smarter decisions.

Assess Your ERP Data Health Today

Remember, even if data chaos is a common challenge, you don’t have to let it hold your business back. Invest in data governance, standardization, integration, training, and future-proof technologies to build a robust data-driven business platform.
Take the first step towards taking back control of your ERP and unleashing its true potential by getting in touch with our team of data experts at Parallel Minds and transform your existing ERP system into an invaluable business asset.

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ERP Data Chaos_ Signs, Causes, and Business Impact (Part 1 of 2)

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ERP Data Chaos_ Signs, Causes, and Business Impact (Part 1 of 2)

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Enterprise Resource Planning (ERP) systems streamline processes and are proven catalysts in centralizing data across industries ranging from manufacturing and real estate to oil and gas. In the absence of an optimized and well-managed system, however, misaligned ERPs can also contribute to data chaos, resulting in fragmented, isolated, and conflicting data, insights, and information.

This data chaos goes beyond proving to be a headache for IT teams. It can lead to wayward decision-making and hinder the growth potential of an entire business. Mismatched inventory inputs, lost sales opportunities due to data blind spots, and even compliance fallouts can all lead to costly business consequences and even legal trouble.

Warning Signs Your ERP is Descending into Chaos

For a mid-sized or enterprise-level manufacturing, oil and gas, or real estate company, your ERP system acts as the command center of your business operations. Just as easily, however, this central component of your decision-making process can not only be a major contributor to data chaos but even prove to be the source of disjointed and unreliable information.
Recognizing and acknowledging these red flags can help in re-establishing control and tapping into the full potential of your ERPs.

Interdepartmental Data Discrepancies

Your finance department reports one inventory level, your sales department holds another, and your production department needs to reconcile both. Even while working towards the same goals, your core departmental teams have on their drawing board different sets of data, leading to confusion, delays, and incorrect decisions, all the while adding to company costs. Inconsistent and conflicting numbers lead to missed opportunities. They contribute to production bottlenecks, inaccurate forecasting, and lost sales, all because of the absence of a unified data source.

Reporting Hassles and Blurred Insights

Even compiling an elementary report turns out to be a bottomless digging-in for relevant data. The hours slip away and your team is left collecting information from multiple sources. Even then, the accuracy of the collected data is uncertain, and you are left with a report that isn’t entirely dependable. Decisions grounded on unreliable and inaccurate data are inherently dubious in nature. You still face questions ranging from oversight of critical trends to the ignorance of operational inefficiencies. A turbulent ERP denies you the quality of insights you need to propel business growth.

Spreadsheet Chaos

Your teams turn to spreadsheets and use them as crutches, spending time manually exporting, tweaking, and reconciling data, all because your ERP is failing at delivering on its core functionality and is incapable of providing relevant data and insights. This approach opens the doors to manual errors, duplicity of efforts, and wasted hours. It indicates that your ERP isn’t customized to align with your business workflows, resulting in your team resorting to makeshift measures instead of working towards effective and long-lasting solutions.

Decision Paralysis

When your decision-making team is wary about the quality of data and unsure of whether they can rely on insights, they delay key decisions. Questions about the correctness of inventory figures and the dependability of sales forecasts force them to hesitate. In an industry where business decisions are required to keep pace with the industry, hesitation can lead to disastrous consequences. Missed deadlines, a loss in market share, weakened shareholder trust, and a confused target audience are potential results of indecisive data-driven decisions.

Root Causes of ERP Data Chaos

Lack of Data Governance and Standardization

In the absence of a clear, unified approach to data management via standardized data governance practices, minor inconsistencies quickly build up to create chaotic systems. Independent departments, in line with meeting their operational efficiency, may develop their own shadow IT processes, with different terminologies and naming conventions, data formats, and even unlinked spreadsheets to maintain their data. These divergent formats and information directly lead to misinterpretations, conflicting insights, and gaps in data communication.

Poorly Executed Data Migration Strategies

A flawed data migration strategy or even the poor execution of a robust one can adversely impact your system, failing to connect essential components and even corrupting your new ERP system. Neglecting crucial processes such as data cleansing to avoid duplication and transfer of outdated data, mapping to maintain interdepartmental connectivity and coordination, and validation to ensure business relevance can cost a company dearly. The result is a long list of errors and inaccuracies that are difficult to pinpoint due to their cascading nature.

Improper Integration Protocol

Since your ERP system rarely executes its functions in a vacuum, its smooth coordination with other vital data-oriented systems ranging from CRM to supply chain remains crucial. When these connections are not set up efficiently and break down, departments stay out of sync with one another and influence a disjointed and incomplete view of business operations. These lead to misfired warning signs, poor decisions, and chaotic validations that create a ripple effect of business errors.

Inadequate User Training Procedures

Human error can play its part in even the most advanced ERP systems. In an environment where data acts as the fuel source, the improper allocation of data sources can lead to underperformance and irrelevant outputs. Despite the operational efficiency of the system, employees may undermine the importance of report generation and data insights. The investment into the system can also be severely undermined when teams in every department fail to identify and correct inter-departmental gaps and, as a result, miss opportunities.

The Domino Effect and Impact of ERP Data Chaos

The ideal vision of an ERP system ensures a smooth-running organization, where every department works efficiently and independently while simultaneously engaging in harmonious collaborations. When you allow chaos to creep in, however, it can quickly spread through the entire business structure, diminishing efficiency and adversely impacting your profitability.

Resource Drain

Visualize your team spending numerous work hours a day manually reconciling inventory discrepancies in data supplied by your finance and sales departments. Or picture your engineers scouring through obsolete spreadsheets to locate the right equipment specs all because their ERP searches are proving ineffective. These situations are more than mere workplace frustrations. They cause a substantial wastage of resources that could be put to use in business-positive components such as innovation and growth.

Customer Service Deficiency

Faulty data leads to incorrect orders, delays in shipments and final deliveries, and of course, an unhappy lot of customers. In the manufacturing business, the direct result is a dissatisfied customer base with loads of complaints as well as a loss of revenue. In the oil and gas business, inaccurate data and ERP shortcomings could lead to serious lapses in safety. In the real estate business, misrepresented data could lead decision-makers to make improper property evaluations, which may further evolve into legal complications.

Untapped Growth Potential

Your ERP holds a stockpile of valuable insights: trends that throw open new markets, changing customer behaviors that inspire product enhancements or shifts, or inefficient turns in the process that require streamlining. When your data is messy, it leads to disorganized insights. All these revelations that hold tremendous growth potential now remain concealed, eventually inhibiting business growth and expansion.

Regulatory Compliance Hurdles

Whether it is safety protocols and compliances in oil rigs, financial reporting and paperwork in real estate, or complicated yet essential supply chain mandates in manufacturing, your business relies heavily on the accuracy and efficient delivery of ERP data. Inconsistent and erroneous data may cause business inefficiency, but that’s only the beginning. On the outside, decisions based on this data could lead to hefty penalties, legal disputes, or even operational shutdowns.

The Bottom Line

The bottom line is that ERP chaos leads to more than just an IT problem; it leads to serious business problems. The adverse effects of this chaos bleed into every department and operation, negatively impacting every component from stakeholder morale to business growth, and eventually undermining every business effort.
Thankfully, the Parallel Minds team also has a ready list of solutions for you, and that’s what’s up ahead in Part 2 of this post!

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About the author

Parag,-CEO-Parallel-Minds

Parag Bihade, Founder and CEO of Parallel Minds, and co-founder of DATASMITH AI led by Kirti Bihade, brings 25 years of extensive experience in software programming and a passion for data and digital transformation.

Parag leads a team dedicated to empowering mid-sized manufacturers with innovative tech solutions. @Kirti Bihade – Team Parallel Minds is pursuing her Ph.D in AI and has extensive experience in Data Science, Machine Learning, and Data Visualization.

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Demand Forecasting Platforms — Amplifying Your Mid-Sized Company’s Growth Strategy

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Demand Forecasting Platforms — Amplifying Your Mid-Sized Company’s Growth Strategy

Table of Contents

Is managing your midsize company’s inventory still a guessing game? If you’ve been preoccupied with managing other aspects of your business, your business may not be able to accurately predict your customers’ requirements. In this case, a demand forecasting platform can be pivotal to your business’s success and growth.

If managing your mid-sized company’s inventory is still a guessing game, you’ve probably been too busy managing other aspects of your business to save your forecasting strategy from the dark ages.

Under the circumstances, your business is far from accurately predicting your customers’ specific requirements, which means some shelves in your warehouses are running empty because they’ve been sold out and others are overflowing with surplus stock.

On the one hand, you have a line of customer orders to be fulfilled with no products to ship. On the other, you have surplus stock that hasn’t moved an inch due to a drastic drop in demand. Your spreadsheets have been of no help, and all you can do is tide over the mess and hope your instincts and your team’s manual forecasts work better the next time.

Well, if this nightmare situation sounds like one you’ve recently faced in your mid-sized company, or if it is one you smartly wish to avoid with careful planning, here we are to tell you why a demand forecasting platform is the answer.

Limitations of Manual Forecasting: A Case Against Spreadsheets

There’s no denying the role spreadsheets have played in business decision-making over the years. Despite their error-prone and time-consuming habits, the announcement of a spreadsheet update was all that was required to sum up a forecasting effort. The list of shortcomings, however, kept getting longer.

Let’s dive into the specifics!

Time

Manual forecasts require teams to chase down data from various departments, update spreadsheets, consolidate reams of data, run calculations and check for anomalies, and redo parts of the entire process until they reach a point where a decision has to be made, irrespective of the quality of data at hand. Understandably, the entire cycle turns out to be a heavy lifting effort than a smart and quick decision-making one.

Human Error

In the highly complex world of manual forecasting where vast datasets are involved, even a minor typo snowballed into a serious inaccuracy. With no way to identify these errors in time, it was often only after decisions went haywire that these often fatigue-induced inaccuracies even came to the fore. Soon enough, it becomes clear that it would be impractical to ignore these costly mistakes and depend on fallible human efforts alone.

Scalability

As a business grows, the data deluge becomes increasingly complicated to handle, making the volumes and complexities of spreadsheet information no less than a nightmare. It is soon clear your spreadsheet strategy is no longer working out. The only option is to begin to choose more important patterns and forecasts, thus leaving you with fewer insights each time. Translating to missed opportunities, slower expansion, and inaccurate decisions, the adverse results are soon obvious.

Missing Pieces

Manual forecasting never presents the complete picture, and missing out on dynamic factors is a serious flaw it has failed to overcome. Since relying on historical sales data is no longer enough, the tunnel vision it offers leaves out essential projections connected to changing market trends, competitor overhauls and shifts, seasonal changes, economic influences, and social media impact. These blind spots translate to incorrect forecasts and missed opportunities, all arising from misinformed decisions.

Decision Delays

In a business environment where agility is key, manual forecasting via spreadsheets no longer offers the insights you need to keep up with real-time shifts and changes. Pivoting quickly is close to impossible with your data still caught up in time-consuming processes, and even keeping up with the competition seems like a lost cause. These result in slow reactions, let alone proactive decisions, and eventually cost the business missed opportunities as well as losses due to lethargy.

With the growing complexities in business, companies relaying on traditional spreadsheets and manual forecasting soon began to realize that no matter how many updates they introduced to these processes, their ability to handle complex data often fell short, and at the cost of speed and accuracy too.

How a Demand Forecasting Platform Transforms a Mid-Sized Business

Demand forecasting offers a mid-sized business strategic advantages that include agility, comprehensive overviews, accuracy, and smarter insights, all contributing to its ability to make data-driven decision that are timely, proactive, and impactful.

Unmatched Precision

Demand forecasting platforms harness a comprehensive array of variables and access hidden patterns and data, even surfing through historical data, market conditions, and sales numbers, before delivering forecasts. They quickly adapt to shifts and changes in real-time, accounting for every influential component while crunching the numbers to accurately predict demand. This mix of continuous learning to offer added precision enables a business to make informed decisions that are based on comprehensive and acute analysis of a holistic list of indicators.

Self-Sustaining Efficiency

Tasks like gathering data on current market conditions, trending social media posts, shifts initiated by the competition, and then crunching these numbers were tedious ones for manual teams. The delays, inaccuracies, and inconsistencies were understandable. Modern demand forecasting platforms take on all these tasks and more, even sustaining its efficiency without the need for human intervention. With inbuilt problem-solving and machine learning abilities driving their functions, these platforms are as autonomous as they are impactful.

Dynamic Machine Learning

Manual forecasting heavily relied on human intervention to introduce improvements and a spreadsheet was simply extensions of the creativity and intelligence of the human mind that managed it. Today’s demand forecasting platforms leverage the power of machine learning to grow more accurate and refined on their own, constantly taking in new data and responding to external shifting patterns with equally swift adaptations. This dynamic approach enables these platforms to stay ahead of the curve at all times, offering the same advantages to a business.

Seamless Integration

Forecasting platforms seamlessly integrate with an existing digital ecosystem, enabling a business to add their CRM, ERP, and other data to the platform and create a unified data landscape that makes the entire decision-making process a lot less complicated. More than just a technological effort, this effortless merging of functionalities into a multipurpose dashboard ensures that every piece of data in your existing ecosystem now finds a place in a sophisticated yet highly efficient forecasting environment.

Deep Data Discoveries

While manual forecasting efforts barely skimmed the surface, demand forecasting platforms dive deep into your data, unearthing hidden trends as well as anomalies, and creating a panoramic view of filled with comprehensive insights and business optimization scenarios. Powerful analytics then enables the projection of correlations and interconnected patterns, creating intrinsic visualizations and compelling narratives based on opportunities as well as gaps.

Scenario Analysis

Going beyond forecasting, these platforms simulate scenarios to enable a business arrive at decisions and strategies with confidence. They can easily model the outcomes of multiple scenarios, showing business just how certain trends will play out in different market conditions. They include both macro and micro influences, do more than just lead you to predictions; they also pave the path to optimal patterns and realistic visualizations while simulating additional scenarios to present a comprehensive overview.

Data-Driven Empowerment

Moving well beyond gut instincts and historical decision-making, businesses can now drive their growth and precision-induced strategies with every data insight and forecasting scenario well accounted for by a highly dependable and accurate tech-driven platform. Mid-sized companies thrive on agile, informed choices, and this data-driven empowerment a demand forecasting platform offers is undeniably a strong and influential catalyst.

Proactive Power

When it’s all about predicting the future, every shift and pattern needs to be analyzed carefully to complete all possible visualizations of potential scenarios while also providing you with the opportunity to stay agile. Demand forecasting platforms accomplish these goals and more, offering businesses the chance to latch on to emerging opportunities while handling huge amounts of data to cover every component from your inventory and marketing to pricing and competition to arrive at decisions that are already ahead of the curve.

The Parallel Minds Strategy

At Parallel Minds, we leverage every advantage of a demand forecasting platform to transform your business into a proactive, agile, and data-driven powerhouse. With us on your side, you no longer depend on aging spreadsheets and critical delays. Our team, while highlighting key advantages of each technology, also build for a customized platform that aligns perfectly with your digital ecosystem and business outlook.

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