Intelligent Enterprise https://www.silvon.com/blog/ Business Insights for Manufacturers and Distributors Fri, 09 Feb 2024 21:01:35 +0000 en-US hourly 1 How to Successfully Onboard a New Business Intelligence & Reporting Solution https://www.silvon.com/blog/how-to-successfully-onboard-a-new-business-intelligence-reporting-solution/ Tue, 09 Jan 2024 16:48:54 +0000 https://www.silvon.com/blog/?p=2495 The right business intelligence and reporting software can significantly enhance business outcomes by giving decision makers greater visibility and insight into sales...

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The right business intelligence and reporting software can significantly enhance business outcomes by giving decision makers greater visibility and insight into sales and operational performance. But getting your whole team psyched up to use and get the most value out of a new data analysis (or, business intelligence) application may not always be easy. New software onboarding helps you succeed in that.

 

What Onboarding Is …

Onboarding is the phase that you as a customer go through between making the decision to use a new reporting tool and being a fully set up user of this software, knowing exactly how to extract the most value from it.

What are the benefits of a structured approach to onboarding a new business analytics and reporting application?

There are many reasons why a business would want to structure and optimize their onboarding processes:

  • To ensure high data quality. Otherwise, the application won’t be used.
  • To train and engage users.
  • To vet your current business data.
  • To create momentum with the new reporting solution, garnering high usage once the onboarding is complete.

How Onboarding Works …

With business analytics and reporting software, modern onboarding starts with understanding you as a customer – your current situation, current setup, your priorities, what you want to achieve with the new software, and your definition of success.

Having measurable success criteria is ideal and should be achievable during the onboarding process. Some of the first questions to ask yourself either before you make your software selection or begin your onboarding process are:

  • Why are we doing this? Is it to improve visibility to business performance? To have the ability to analyze and report on information across the enterprise? To give analysts and others self-service access to business data with minimum IT intervention? Or to improve the accuracy of data used for your business reporting?
  • How are we going to validate the data? Using our current reporting system? Manually? With Excel?
  • What are we looking to achieve? A system that’s trustworthy to use to help manage part or all of the business? To replace your current business analysis and reporting system? To reduce data manipulation in Excel for reporting? Or to leverage totally vetted data in your Power BI visualizations?
  • Who will make data corrections and set up new users once it’s live? Your IT team? Your vendor?

Based on that information, the vendor’s software onboarding team should customize a project plan to guide you through the migration and implementation phase. As the software offering evolves and changes over time, and as new features are released, good onboarding should also make sure that these features get used and that clients benefit from them.

An Iterative Approach to the Success of a New Reporting Solution

The onboarding process for a data analysis and reporting solution should employ an iterative approach that can be easily replicated whenever new data is made available to the application, when new features are added by the vendor to the application itself, or when new users in your business are introduced to the solution.

In working with more than 2,000 businesses over the years, we’ve found the following steps to be most beneficial in helping our clients organize a successful onboarding initiative using this approach.

  • Identify the Onboarding Team – This includes individuals from your business and from the vendor’s organization who will be involved in defining and orchestrating the onboarding program.
  • Define the Data Scope of the Onboarding Project – Once the scope of onboarding has been defined and communicated with the vendor, the vendor should create a prototype of their solution for you, mapping in a subset of your data for initial testing and actual use.
  • Schedule a Kickoff Meeting – A kickoff meeting between the Customer and Vendor teams will help to ensure that both sides are on the same page relative to the scope of the onboarding program.
  • Make Sure You Have All the Data You Need – In this stage, you’ll determine if you have the right data to feed the data model of your vendor’s solution to support your current and/or desired reports.
  • Configure & Integrate the New Reporting Application w/Existing Systems & Data Sources – This typically includes the remote installation of the reporting software on your hardware or in the cloud, as well as integrating the reporting solution to your ERP’s current and historical Sales or other business data previously defined in the data scope.
  • Validate The Data – There are certain strategies you can use in validating your data for the reporting solution. Your vendor should provide guidance to you during this step.
  • Final Steps Before “Go Live” – As you’re getting ready to go-live, various final steps will need to be addressed, including setting up your security measures, defining users who will have access to the application, and conducting user training.
  • Success – As experience has shown, this stage isn’t always an immediate success. Look at this last implementation phase as the time for smoothing out the rough corners and fixing any issues that might come up.

For additional details regarding the steps above, get Silvon’s complete guide
to successfully onboarding a business intelligence and reporting solution.


Monitoring & Support Both During & Following the Onboarding Program

While your team becomes acquainted with using the software and after the onboarding program has come to an end, it’s important to provide ongoing monitoring and support of the reporting application to ensure that users embrace it with good momentum and that it continues to meet your defined scope as your business evolves.

The vendor’s support team and automated support platform should be the leading point of contact for help, questions and issues all the while – supported by the vendor onboarding team, client services group and customer success manager. Be sure to ask your vendor, too, about regular communications programs they may have to help you, such as weekly status meetings, quarterly executive reviews to learn about new features, new release notifications, and educational newsletters.

Once the onboarding is over, see if your vendor provides a methodology for helping you make changes to your onboarded data and other files – even to help you add new data if there are gaps you need to fill.

In Summary

A well-managed onboarding initiative can eliminate so many of the gotcha’s typically experienced by companies as they bring a new reporting solution on board. By using an iterative approach, you’ll be prepared to handle new features, the addition of new users and the handling of new data from both current and new sources with ease. Plus, having a vendor that not only understands your industry, but the business software you use and the unique features of the vendor’s own reporting solution, can help guide you swiftly and effectively versus leaving the entire onus of onboarding on you.

 

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How To Move Your Business Data To a New ERP System In a Risk-Free Way https://www.silvon.com/blog/how-to-move-your-business-data-to-a-new-erp-system-in-a-risk-free-way/ Thu, 09 Nov 2023 14:39:47 +0000 https://www.silvon.com/blog/?p=2482 Thinking about replacing your current ERP system with a new, on-premise or cloud-based solution? It’s a significant endeavor, and it comes with...

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Thinking about replacing your current ERP system with a new, on-premise or cloud-based solution? It’s a significant endeavor, and it comes with its fair share of challenges. You have to deal with issues like time constraints, data quality, stakeholder support, potential regulatory concerns, and the expense of it all. But here’s the silver lining: this process also presents a golden opportunity to clean up your data and improve your reporting and analysis at the same time.

How? By embracing a data hub-based information management and reporting solution that can deliver value to your business both prior to and long after your new ERP system’s in place.


The Data Challenges of a New ERP Implementation

There are a number of data-related challenges when moving to a new ERP, especially to a cloud-based ERP because there is no easy way to get historical information into it.  This is further compounded if you’re moving from multiple ERP systems to a single ERP instance.  Just think about all the data you’d need to deal with. It can be mind-blowing.

If you haven’t thought about an approach for moving your data into a data hub beforehand, you really should.  You need the ability to analyze and report on all of your current and historical data as the implementation takes place in order to keep your business performing in an optimum way.

As you’re making the transition, you can use a data hub to store and manage historical data, like your accounts payable and receivable, purchase history, and sales history. The magic of having a data hub in the mix is that it can significantly reduce the amount of data you need to transfer to your new ERP system. Plus, while all this is happening, your business analysts and others can keep running their analyses and generating reports without a hitch using the hub’s built-in analytics and reporting tool.

In this discussion, we’ll dive into the benefits of using a data hub-based reporting platform during an ERP installation or cloud migration.

Let’s start with data conversion.

When you’re moving from your old ERP to the new one, you’ve got to consider both your master data and your transactional data. The trustworthiness of your new system’s reports depends on the quality of this data.

When it comes to your master data, it’s generally not an easy task to map all the data you have in place to the new ERP.  Even worse, some of your company’s reporting may rely on master data that only exists in spreadsheets.  And if you’re moving to a cloud-based solution, many times you’ll need to change product or customer numbers for the new ERP system.  Data hubs can facilitate data mapping and transformation by giving you the ability to cross reference the data structures and formats between your current and new system, significantly reducing the complexity of the actual data migration as a result.

Now, let’s talk about transactional data. With a data hub platform, you can leave your legacy transaction data in the hub, eliminating the need to migrate it to the new ERP. The data hub will automatically support the reporting of your historical data; and once the conversion is complete, you can bid farewell to the old ERP system and the costs that come with maintaining it.

What about report conversion?

Over time, businesses accumulate volumes of reports in their ERP system, some of which might be outdated or redundant. Instead of blindly transferring all of them, it’s smarter to evaluate which reports are essential.

Prior to or while the ERP or cloud migration is taking place, you can load the data needed to fuel your reports into the data hub alongside your legacy data. This creates a rich dataset that can be used for any report, without worrying about the data source. It’s a game-changer in terms of reporting flexibility. Plus, you can include data from various sources like Excel, your CRM, MES and other systems and data sources, enriching the value of your reports even further.

And let’s not forget the shift from static printouts to dynamic, interactive reporting. With a data hub-driven BI solution, users are empowered to view and analyze their data from a variety of angles and in a variety of advanced graphs and charts in their favorite reporting tool.

Finally, let’s talk about the overall benefits that a data hub can provide during an ERP upgrade or migration to the cloud:

  • Say goodbye to siloed data: Multiple departments may store their own copies of information about the same customers or products in an ERP system, but their data may not be identical. For example, customer names and addresses may be stored in different formats or with varying addresses for the same customer.  And for multiple ERP instances, different customer or product numbers for the same customers and products may exist.  The list goes on!  If you simply import every record from each business unit into the ERP database, you could end up with tons of duplications and inaccuracies.  A migration strategy that includes a data hub for consolidating and storing this historical data can help overcome such redundancy and integrity obstacles.
  • Reduced downtime: Data hubs can help minimize downtime during the ERP implementation process by providing a layer of abstraction between data sources and the ERP system. This is particularly crucial when you don’t go totally live on the new ERP system at once.  For example, you may opt to roll it out by location or by a departmental area.  By putting a data hub in place beforehand, analysts and others can continue their reporting tasks while the system is being rolled out.
  • Flexibility: Data hubs can adapt to changes in data sources and formats, making it easier to accommodate changes in the ERP system or to integrate with other systems in the future.
  • Cost Savings: The entire cost of bringing a data hub-based reporting platform onboard prior to starting an ERP implementation or cloud migration can be less that what you would ultimately pay to convert your transactional data to the new system.  Not only that, once you have it in place, the additional cost savings and benefits that its data management, analysis and reporting capabilities can yield for your business can be invaluable to your organization’s ongoing growth and success.

In a nutshell, a data hub-based data management and reporting platform can be your biggest ally during a new ERP installation or cloud migration. It streamlines data management, fosters interactive analysis and reporting of your ERP and other data even while the upgrade occurs, reduces costs, and ensures a smooth transition, helping you make the most of this transformational process.

 

Silvon Stratum: The Data Hub Solution Trusted By More than 2,000 Mid-Market Manufacturing & Distribution Businesses Worldwide

Selecting the right data hub platform is critical not only to the success of an organization’s ERP strategy, but to the success of its business reporting strategy as well. The Stratum data management and reporting platform by Silvon has been a proven solution for more than 2000 businesses over the years – enabling these businesses to rapidly implement, deploy, and maintain the hub and to expertly retrieve, transform and convert data during new ERP implementations while fostering a continued reporting environment for analysts and others in a low-cost, low-risk manner.

LEARN MORE ABOUT IT

 

 

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4 Factors Fueling the Growth of Modern Data Hubs for Business Reporting https://www.silvon.com/blog/4-factors-fueling-modern-data-hubs-for-business-reporting/ Thu, 28 Sep 2023 18:39:24 +0000 https://www.silvon.com/blog/?p=2466 As the volume of data and requirements for gaining access to it continue to skyrocket, it is becoming vital for organizations to...

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As the volume of data and requirements for gaining access to it continue to skyrocket, it is becoming vital for organizations to find ways to aggregate their business information and quickly understand it. And that involves putting the ability to analyze data into the hands of more analysts, data scientists and other stakeholders and decision makers than ever before without requiring them to spend crazy amounts of time preparing the data.

Today’s modern data hub facilitates this … and here’s how.

Why Consider a Data Hub?

Silvon has noticed over the past several years that a shift towards a modern data hub architecture to support enterprise analytics and reporting has been driven by a number of key business drivers. The following four drivers consistently top the list for the companies we work with:

  1. To facilitate the analysis of data from multiple data sources and applications
  2. To support the move to self-service reporting
  3. To provide greater responsiveness to line-of-business (LOB) users and analysts
  4. To enable enterprise reporting both within and beyond an organization’s four walls
A modern data hub is a gateway to information no matter where it’s coming from.

A modern data hub collects, integrates and manages data from multiple disparate systems and external data sources (like market research and point-of-sale systems), regardless of whether the data is on-premise or in the cloud.  Once integrated, the data is made “analytics ready” and securely available to users.

A key benefit of this approach is that users don’t need to know how the data is stored to access and view it. In addition, their views of data reflect the exact same names and structures that are appropriate to their business areas and technical abilities. Plus, it ensures that everyone across the business is analyzing the exact same data – supporting truly accurate reporting across the enterprise.

The architecture of a modern data hub is also designed to readily support new data sources and applications as they become available. And for many organizations that upgrade, change or migrate their internal ERP and other systems to the cloud, a data hub offers a convenient way for them to manage and provide ongoing, secure access to their core operational data for reporting purposes during the transition.

A modern data hub supports self-service reporting.

A modern data hub unites optimal operational and analytical features that address the self-service needs of business analysts and citizen data scientists (rather than IT). Once most of an organization’s data is visible from a single hub, both business and technical people can see what “the big picture” is in terms of the information they are securely authorized to view and work with and to leverage that information for business advantage.

As an example of this, the data scientists and business analysts at several of our customer accounts regularly import their own budgets and forecasts from spreadsheet applications like Excel into their Silvon data hub for planning purposes, which leads to additional data sharing and data-driven collaboration.  Many of our clients also use Power BI for creating visual scorecards, dashboards and reports while relying on Silvon’s hub to confidently pull information that’s both vetted and trustworthy into those visuals and reports.

A modern data hub offers greater responsiveness to line-of-business users.

The modern data hub provides views that make data look simpler and more unified than it really is. This way, unique views for diverse business functions – from sales and marketing to purchasing, production, shipping, customer service (and everything else in between) – can be created quickly without disrupting business processes and user productivity. Users can access, analyze and share information in terms and structures they understand … and, again, without having to know how the data is stored. This gives them a leg up in their ability to assess and respond more quickly to deviations in business performance based on the data.

A modern data hub has enterprise scope – endless reach.

The integrated analytics and data management aspects of a modern data hub can accommodate all of an organization’s critical information in order to glean insights that are based on the analysis of diverse data from distributed sources. This generally isn’t possible with older hubs that are data silos limited to a single operational data store, like customer orders derived from an ERP system.

Also, with older data repositories, the data comes in for analysis by a short list of users and rarely comes out to be shared and reused elsewhere. A modern data hub, on the other hand, enables data that’s collected to be immediately shared with many users both inside and external to the organization.  Today’s data hubs accomplish this information sharing in a number of different ways – for example, via customizable data views, interactive dashboards, automated email reports and other data delivery means.

 

If your business is challenged by multiple data silos and inaccurate numbers between them, increased demand by internal and external stakeholders for greater visibility to your business data, or an impending application migration where you need continued access to your data both during and after the transition, it would serve you well to consider a modern data hub to support your financial and operational reporting requirements. To learn more about Silvon’s packaged data hub and reporting solution, we invite you to check out our Stratum Data Hub webpage.

 

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Cascading KPIs To Drive Business Performance https://www.silvon.com/blog/cascading-kpis-to-drive-business-performance/ Tue, 26 Sep 2023 15:54:33 +0000 https://www.silvon.com/blog/?p=2428 The practice of “cascading” KPIs aligns strategic objectives with business unit targets and performance measurements to drive positive results. This involves linking...

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The practice of “cascading” KPIs aligns strategic objectives with business unit targets and performance measurements to drive positive results. This involves linking high-level objectives with departmental objectives and KPIs to create a clear line of sight from the top down.

In this 3-minute post, we examine some key business objectives and cascading KPIs that can be used to analyze performance to the objectives.  While many of the KPI examples focus on performance management for manufacturing and distribution businesses, they also apply to numerous other industries with similar operational structures.

For additional KPI concepts and best practices, we welcome you to download Silvon’s Definitive Guide to KPIs.

Cascading KPIs for Sales

Strategic Corporate Objective:

    • Increase Revenue

Departmental Objectives:

    • Increase Sales Volume
    • Improve Sales Productivity

KPIs:

    • Sales Volume:
      • Number of Units Sold, Revenue Generated
    • Sales Productivity:
      • Number of Sales Calls Made, Average Time to Close a Sale

 

Cascading KPIs for Inventory

Strategic Corporate Objective:

    • Optimize Inventory

Departmental Objectives:

    • Improve Inventory Accuracy
    • Reduce Inventory Holding Costs
    • Increase Inventory Turnover

KPIs:

    • Inventory Accuracy:
      • Cycle Count Accuracy, Shrinkage Rate, Stock-Out Rate
    • Inventory Holding Costs:
      • Carrying Cost of Inventory, Obsolete Inventory, Stock Turnover Ratio
    • Inventory Turnover:
      • Inventory Turnover Ratio, Gross Margin Return on Investment (GMROI), Days Inventory Outstanding (DIO)

 

Cascading KPIs for Purchasing

Strategic Corporate Objective:

    • Reduce Costs and Improve Supplier Performance

Departmental Objectives:

    • Reduce Purchase Costs
    • Improve Supplier Performance

KPIs:

    • Purchase Costs:
      • Cost Savings, Cost Avoidance, Cost Per Unit
    • Supplier Performance:
      • On-time Delivery, Quality Performance, Lead Time

 

Cascading KPIs for Production

Strategic Corporate Objective:

    • Improve Production Efficiency

Departmental Objectives:

    • Increase Equipment Uptime
    • Reduce Waste
    • Increase Throughput

KPIs:

    • Equipment Uptime:
      • Mean Time Between Failures (MTBF), Mean Time to Repair (MTTR)
    • Waste Reduction:
      • Scrap Percentage, Reject Percentage, Rework Percentage
    • Throughput Improvement:
      • Units Produced, Cycle Time, First Pass Yield

 

Cascading KPIs for Customer Relationship Management

Strategic Corporate Objective:

    • Increase Customer Satisfaction and Retention

Departmental Objectives:

    • Improve Customer Service Quality
    • Increase Customer Engagement
    • Enhance Customer Loyalty

KPIs:

    • Customer Service Quality:
      • Response Time, First Contact Resolution (FCR), Average Handling Time (AHT)
    • Customer Engagement:
      • Number of Interactions, Frequency of Interactions, Engagement Rate
    • Customer Loyalty:
      • Net Promoter Score (NPS), Customer Churn Rate, Customer Lifetime Value (CLV)

 

Cascading KPIs for Finance

Strategic Corporate Objective:

    • Increase Profitability and Financial Stability

Departmental Objectives:

    • Improve Revenue Growth
    • Control Costs
    • Optimize Cash Flow

KPIs:

    • Revenue Growth:
      • Sales Growth, Market Share, Customer Acquisition Cost
    • Cost Control:
      • Operating Expense Ratio, Cost per Unit, Procurement Savings
    • Cash Flow Optimization:
      • Days Sales Outstanding (DSO), Days Payable Outstanding (DPO), Cash Conversion Cycle

 

Cascading KPIs for Trade / Promotional Marketing

In this final example, here are some potential cascading KPIs for a trade marketing department:

Strategic Corporate Objective:

    • Increase Sales Volume and Market Share

Departmental Objectives:

    • Improve In-store Product Visibility
    • Increase Trade Promotion Effectiveness
    • Enhance Channel Partner Engagement

KPIs:

    • In-store Product Visibility:
      • Share of Shelf (SOS), Out of Stock (OOS) Rate, On-Shelf Availability (OSA)
    • Trade Promotion Effectiveness:
      • Promotion Sales Lift, Promotion ROI, Sell-through Rate
    • Channel Partner Engagement:
      • Joint Business Planning (JBP), Distributor Scorecard, Customer Satisfaction (CSAT)

 

The Bottom Line

Enterprise-level alignment using a waterfall / cascading model like the one above is very effective for driving business performance because it provides a clear distinction between tasks, generates synergy between organizational business units, and can facilitate effective communication at all levels. Employees also have a clear picture of their contribution to organizational performance which often leads to higher levels of engagement.

Fortunately, modern analytic tools like Silvon’s Stratum solution offer pre-defined metrics and data visualization capabilities to simplify the process of creating and sharing KPI dashboards and reports to management and departmental teams throughout the business.

For additional concepts and best practices related to KPIs, feel free download Silvon’s Definitive Guide to KPIs.

 

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Empowering SMBs with Reporting and Analytics https://www.silvon.com/blog/empowering-smbs-with-reporting-and-analytics/ Wed, 09 Aug 2023 20:24:01 +0000 https://www.silvon.com/blog/?p=2414 Small and medium-sized businesses (SMBs) have traditionally been slow to adopt analytics and reporting strategies — with SMB leaders often expressing frustration...

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Small and medium-sized businesses (SMBs) have traditionally been slow to adopt analytics and reporting strategies — with SMB leaders often expressing frustration over their limited access to data and insights compared to larger competitors.

There are a number of reasons why many SMBs have not fully embraced data analytics (or business intelligence – BI).  For one, they may lack a scalable technology infrastructure or skilled workforce. The quality and availability of their data may be low because information is stored in various systems and formats. The cost of implementing BI may be perceived to be too high compared to its benefits … and much more.

 

The BI Market – Closing the Gap Between Big Business & SMBs

According to some analysts, the global BI market is projected to reach $43 billion by 2028, compared to $24 billion in 2021. However, the adoption rate of BI in SMBs remains low at just 26%, in contrast to 80% in companies with over 5,000 employees. These findings clearly highlight the significant gap in BI usage between larger corporations and SMBs.

So, how does one close the gap? While mindset can be a difficult obstacle to overcome, technology and budget constraints are much more manageable these days. Most business functions now rely on Software as a Service (SaaS) solutions where software vendors actually operate and manage the software for their customers.  This levels the playing field for SMBs and enables them to automate core business processes like processing orders, managing inventory, tracking suppliers, and so much more without additional hardware and human resource investments.

On the flipside, though, the data generated by these SaaS-supported processes can be overwhelming, complex, and expensive to collect. This is where modern analytics and reporting platforms come into play. SMBs that have undergone digital transformation are already generating data related to their business operations. With the right BI platform, they can extract valuable insights that align with their business objectives.  Even better, the right BI platform may be available as a SaaS solution, further reducing the need by SMBs to invest in additional resources to support their analysis and reporting efforts.

 

Reporting & Analytics – Capabilities That Matter for SMBs and Others

The core capabilities of a reporting and analytics platform that both SMBs and large enterprises alike can benefit from include features like …

  1. Data Integration: BI applications gather data from various sources, such as databases, spreadsheets, cloud services, and other data repositories. This process involves data extraction, transformation, and loading (ETL) to consolidate and standardize data for analysis.
  2. Data Storage: Today’s modern analytics and reporting platforms use a data hub to store, align and manage large volumes of both structured and unstructured data. This allows for optimized querying and reporting, enabling faster access to information.
  3. Reporting and Analytics: BI applications provide robust reporting and analytical capabilities. Users can create ad-hoc reports and build customized views of data to analyze trends, track key performance indicators (KPIs), and monitor business performance. Some industry-focused vendors like Silvon even provide pre-built templates and reports to facilitate business analysis and reporting for their SMB clients.
  4. Self-Service BI: Many modern analytics and reporting applications offer self-service features, allowing business users to explore data, create their reports, and conduct analyses without relying on IT or data experts. This empowers business users to derive insights independently.
  5. Data Mining and Predictive Analytics: BI applications with advanced capabilities enable data mining and predictive analytics. These features use statistical algorithms and machine learning to discover patterns and forecast future outcomes based on historical data.
  6. Data Governance and Security: BI applications often include features for data governance, ensuring data accuracy, consistency, and compliance with data policies. Additionally, they implement security measures to control data access and protect sensitive information.
  7. Collaboration and Sharing: Today’s analytics and reporting platforms facilitate collaboration among users by allowing them to share reports, insights, and dashboards. This promotes knowledge sharing and improves decision-making across departments.
  8. Real-Time Analytics: Some analytics and reporting platforms also provide real-time data processing and analytics capabilities. This allows businesses to monitor live data streams and respond quickly to changing conditions or emerging opportunities.

While the capabilities of BI tools may vary, it is essential to understand how to leverage BI to one’s advantage. Small- to mid-sized business owners can utilize BI to perform tasks that are typically associated with larger enterprises, such as analyzing consumer behavior, predicting market trends, forecasting sales, and enhancing customer experience.

By embracing business reporting and analytics, SMBs can be in a better position to identify growth opportunities, enhance operational resilience, stay competitive, and foster innovation – all while closing the gap on BI adoption with their larger competitors.

 

 

 

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Supporting S&OP with Stakeholder & Supply Chain KPIs https://www.silvon.com/blog/supporting-sop-with-stakeholder-supply-chain-kpis/ Thu, 01 Jun 2023 19:32:55 +0000 https://www.silvon.com/blog/?p=2383 KPIs are essential in S&OP as they provide a quantitative framework for gaining visibility, aligning efforts, supporting decision-making, and driving continuous improvement...

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KPIs are essential in S&OP as they provide a quantitative framework for gaining visibility, aligning efforts, supporting decision-making, and driving continuous improvement across the business. But how do you know if you are using the right KPIs, including both stakeholder and supply chain performance measures?

It All Comes Down to Balance & Alignment

Unfortunately there is no easy answer to the question of whether or not you’re using the right KPIs for S&OP. Each organization is unique and requires different KPIs based on their specific needs. Ideally, your S&OP KPIs should consist of a mix of strategic, tactical, and operational metrics. Striking the right balance is essential, as an excess or deficiency in any one area can result in overlooking what truly matters.

At times, finding the right metrics can feel incredibly challenging, and there might be a tendency to measure things for the sake of measurement. Remember that you can update your KPI selection at any time, so remain open to replacing ineffective metrics.

The most important aspect to remember is that KPIs should align with your business strategy. They need to be meaningful and relevant to the business. Also, keep in mind that aligning your S&OP KPIs with business strategy is an iterative process. It requires ongoing evaluation, refinement, and adaptation to ensure that the chosen metrics remain relevant and effective in measuring progress towards strategic objectives.

What Should You Base Your KPIs On?

Stakeholder-Focused KPIs

By basing KPIs on stakeholders, you demonstrate a commitment to meeting their needs and expectations, which can lead to stronger relationships, increased trust, and improved overall performance. When working with stakeholder-focused KPIs and metrics, the following can help:

  • Set targets and measurement criteria: Establish specific targets and measurement criteria for each KPI. The targets should be realistic and reflect the desired outcomes from the stakeholder perspective. For example, if one of your KPIs is customer satisfaction, you might set an on-time delivery goal or focus your attention on customer return rates.
  • Monitor and report on stakeholder-focused KPIs: Regularly monitor the performance of stakeholder-focused KPIs and report the results to all relevant stakeholders. Use appropriate reporting mechanisms such as dashboards, scorecards, or periodic performance reports. Transparently communicate the progress and performance of your organization in meeting stakeholder expectations.
  • Continuously engage with stakeholders: Maintain an ongoing dialogue with your stakeholders to keep them informed about your performance and solicit their feedback. Regularly review and update your stakeholder-focused KPIs based on changing stakeholder needs or emerging trends. Actively seek input from stakeholders to ensure that the KPIs remain relevant and meaningful.

Supply Chain-Focused KPIs

Beyond stakeholder-focused KPIs, many companies focus on “flow of materials” to help evaluate the efficiency, effectiveness, and performance of the end-to-end supply chain operations. The KPIs here highlight procurement, production, logistics, and customer fulfillment.

Supply chain KPIs are crucial for optimizing processes, minimizing costs, improving customer service, and enhancing overall supply chain performance. By tracking these KPIs, companies can identify bottlenecks, streamline operations, strengthen relationships with suppliers and customers, and drive continuous improvement throughout the supply chain.

Here are some steps you can take to base KPIs on your supply chain operations:

  • Map the material flow: Start by mapping out the flow of materials within your organization’s supply chain. Identify the key stages, processes, and touchpoints involved in the movement of materials from suppliers to customers. This includes procurement, production, transportation, warehousing, and distribution.
  • Identify critical material flow metrics: Determine the critical metrics that measure the efficiency, reliability, and effectiveness of the supply chain. These metrics should align with your organization’s objectives and priorities. Some common KPIs for material flow include:
    • Cycle time: Measure the time taken for materials to move through each stage of the supply chain.
    • On-time delivery: Track the percentage of materials delivered on time to customers or internal stakeholders.
    • Order fulfillment rate: Measure the percentage of customer orders or internal requisitions that are fulfilled accurately and promptly.
    • Inventory turnover: Evaluate how quickly materials are moving through the supply chain by measuring the number of inventory turnovers within a given period.
    • Fill rate: Assess the percentage of customer orders or internal requests that are fulfilled completely, without backorders or shortages.
    • Lead time: Measure the time taken from when an order is placed until it is fulfilled and delivered to the customer.
    • Transportation costs: Monitor and control the costs associated with transporting materials across the supply chain.

 

Download Silvon’s KPI Guide – Drive Better Business Performance

 

  • Set targets and benchmarks: Set specific targets or benchmarks for each material flow KPI based on industry standards, historical data, or desired improvements. These targets should be realistic and aligned with your organization’s overall performance goals. Consider factors such as customer expectations, cost considerations, and operational constraints.
  • Establish data collection and monitoring mechanisms: Implement systems and processes to collect the necessary data for tracking the KPIs. This may involve integrating data from various systems, such as enterprise resource planning (ERP), warehouse management, or transportation management systems. To integrate the data for reporting and analysis, consider the use of a data hub so everyone’s working with the same numbers.  Also, establish regular reporting cycles and automated data capture to ensure timely and accurate KPI monitoring.
  • Continuously measure and analyze performance: Monitor your supply chain KPIs regularly to assess performance and identify areas for improvement. Analyze the data to identify trends, bottlenecks, or inefficiencies in the material flow process. Use tools such as data visualization, root cause analysis, and process mapping to gain insights and make data-driven decisions.
  • Implement process improvements: Based on the analysis of the KPIs, identify process improvements or optimization opportunities. This may involve streamlining procedures, eliminating waste, improving supplier collaboration, optimizing transportation routes, or enhancing inventory management practices. Implement these changes systematically to drive better material flow performance.
  • Communicate and collaborate: Share your supply chain KPIs, targets, and progress with relevant stakeholders within your organization, including supply chain teams, operations, and senior management. Foster collaboration and cross-functional engagement to address challenges and align efforts towards optimizing the flow of materials.
  • Continuously refine and adapt: Regularly review and refine your KPIs based on changing business needs, market dynamics, or industry trends. Stay updated with emerging technologies and best practices that can further improve the efficiency and effectiveness of your material flow processes.

A Balanced Approach Works Best

It’s important to note that the importance of stakeholder and supply chain KPIs to support the S&OP process can vary depending on the nature of the business and its strategic priorities. For example, a service-oriented company might prioritize customer satisfaction and employee engagement, while a manufacturing company might focus more on supply chain efficiency and inventory management. Ultimately, both stakeholder and supply chain KPIs are interconnected and contribute to the overall success of a company. You should strive for a balanced approach, considering the needs and expectations of both to achieve sustainable growth and long-term success.

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10 KPIs for Effective Accounts Payable Management https://www.silvon.com/blog/10-kpis-for-effective-accounts-payable-management/ Thu, 25 May 2023 18:36:17 +0000 https://www.silvon.com/blog/?p=2353 In today’s business landscape marked by supplier shortages, demand fluctuations, increased operating costs, and liquidity challenges, the Accounts Payable (AP) department has...

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In today’s business landscape marked by supplier shortages, demand fluctuations, increased operating costs, and liquidity challenges, the Accounts Payable (AP) department has emerged as a central driver of business profitability. And as AP’s significance has continued to grow, it has become crucial for it to focus on optimizing processes and ensuring accountability.

Implementing the right set of Key Performance Indicators (KPI)s can provide a simple and effective means to achieve these objectives. Unfortunately, though, AP decision makers often struggle to identify the appropriate KPIs and lack the necessary tools to track them effectively. Recognizing this challenge, 55% of AP leaders in a recent study have prioritized the improvement of financial reporting and analytics. These metric-tracking tools have become increasingly important as organizations look to the future.

This blog post aims to help AP departments unlock their full potential. It emphasizes that when used correctly, KPIs can be transformative tools in achieving this goal.

 

Quality Over Quantity: Selecting the Right KPIs

While there are countless KPIs that an AP department can track, more is not necessarily better. It is crucial to focus on quality rather than quantity – concentrating on a select group of KPIs that have the most significant impact on your company’s performance.

Given the current business landscape and the impact of the pandemic economy, AP’s strategic value has further increased. As a result, the metrics that were previously tracked may no longer provide an accurate view of AP performance. Therefore, it is necessary to reevaluate the KPIs being measured and ensure they align with the shifting goals and priorities of finance leaders.

The following are ten essential KPIs that can drive effective AP management:

Cost to Process a Single Invoice

In today’s cash-conscious environment, AP departments must understand the expenses associated with processing each invoice and develop strategies to mitigate costs. This KPI requires a comprehensive assessment of all AP processing expenses, including routing costs, copying and follow-up expenses, staff salaries, managerial overhead, and IT support. Research indicates that organizations with little automation incur an average cost of $10.95 per invoice, while those with mature automation processes achieve an average cost of $2.25 per invoice.

Time to Process a Single Invoice

Time is a valuable asset, and maximizing AP’s profit-generating potential requires identifying and resolving bottlenecks in the invoice processing workflow. Measuring the time it takes to process a single invoice is a valuable KPI for assessing the value added or wasted by the AP department. Organizations with little automation experience an average processing time of nearly 12 days per invoice, while those with mature automation processes achieve an average processing time of slightly more than 3 days per invoice, representing a 73% increase in efficiency.

Invoices Processed per Day per Full Time Equivalent (FTE)

Measuring staff productivity is a crucial step towards optimizing AP invoicing. By calculating the number of invoices processed per day per AP clerk, organizations can identify areas of improvement within their operations. Although there is no definitive market average for this KPI due to various factors, it provides insights into invoice volume, employee activity, and problematic suppliers.

Invoices Linked to a Purchase Order (PO)

This KPI helps gauge the efficiency of the AP process by tracking the percentage of invoices linked to a purchase order. Invoice validation is a critical step in the approval process, and delays caused by discrepancies with the PO can significantly impact AP efficiency. The market average for the percentage of invoices linked to a PO is 44.3%. However, organizations considered “best-in-class” with high levels of automation achieve an average of 80.2%.

Invoice Exception Rate

Invoice exceptions are a major challenge for AP clerks, consuming significant time and resources. Tracking this KPI helps maintain process efficiency by identifying the causes of exceptions, such as discrepancies in PO and invoice data, missing or incorrect POs, and bottlenecks in the approval workflow.

Straight-Through Invoice Processing

Straight-through or “touchless” processing, where no manual intervention is required, is significantly faster and cheaper than manual methods. Organizations should measure and improve this KPI to maximize margins and efficiency. As a matter of fact, recent studies show that highly automated “best-in-class” organizations achieve a straight-through processing rate of 67.1%, while others achieve only 21.3%.

Suppliers That Submit Invoices Electronically

Encouraging suppliers to submit invoices electronically accelerates processing and streamlines business interactions. The adoption of electronic invoicing has increased by 25% in the past few years, driven by the pandemic’s impact on remote work. On average, organizations without automation receive electronic invoices from only about 40% of their suppliers, while top-performing AP teams receive invoices electronically from 60% of their vendors.

Early Payment Discounts Captured

Optimizing cash flow is crucial for businesses and capturing early payment discounts benefits both the paying company and its suppliers. Recent research shows a 15% increase in the number of businesses that capture early payment discounts, indicating a growing focus on maximizing savings and working capital.

On-Time Payments

Paying invoices on time helps avoid late fees and strengthens relationships with suppliers. Organizations with highly manual AP processes often struggle with on-time payments, requiring additional time and resources. Timely payments are associated with vendor trust and contribute to short-term cash flow and long-term bottom line health.

Days Payable Outstanding (DPO)

DPO is a more complex KPI that demonstrates AP’s value beyond invoice processing and helps justify department costs. It reflects the efficiency of a company’s cash flow strategy and how long it takes to pay suppliers. DPO can impact working capital and influence supplier perceptions of your company. To calculate it, simply divide Average Accounts Payable by Cost of Goods Sold multiplied by the number of days in the accounting period.


AP Transparency Through Real-Time Analytics & Dashboards

By focusing on KPIs like the 10 above, organizations can gain valuable insights into their AP performance, identify areas for improvement, optimize processes, and enhance overall efficiency.

Do keep in mind, though, that knowing what KPIs to measure is just part of the equation.  Businesses also need metric-tracking technology to dig deep into their AP data to bring those KPIs to light. With today’s analytical tools AP cashflow, AP process performance, spend by category/volume/supplier, requests pending approval and numerous other AP functions can be easily assessed. Then pertinent insights from that data can be easily shared with key stakeholders using dashboards, reports and other methods.

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How to Define a Performance Measurement Strategy https://www.silvon.com/blog/how-to-define-a-performance-measurement-strategy/ Tue, 18 Apr 2023 16:11:36 +0000 https://www.silvon.com/blog/?p=2303 While clearly important in today’s constantly changing business environment, so many companies continue to struggle with how to measure and improve their...

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While clearly important in today’s constantly changing business environment, so many companies continue to struggle with how to measure and improve their performance – grappling with questions like:

  • Which metrics really matter?
  • How do we get buy-in around the organization?
  • Can we get the right resources needed to collect data for analysis before it’s too old?
  • How can we overcome the resistance to systemic measurement?

What’s really needed, though, is a cohesive measurement strategy that identifies goals, defines a portfolio of metrics to achieve them, and outlines an implementation plan to make it part of your ongoing business process.  This includes any change management activities that may be required and the technology that will be needed to make it repeatable.

A measurement strategy encompasses three simple steps to performance improvement:

Identify Your Measurement Goals
Define Your Metrics Hierarchy
Implement for Repeatability


Identify Your Measurement Goals

The first step is to clearly define your goals for measuring your business performance because different goals require very different metrics.

  • Is your goal to have metrics that will help you analyze the root cause of problems in your business and apply the appropriate corrective action?
  • Is your goal to provide a view into the financial health of your business?
  • Is your goal to do scenario planning that will help guide ongoing decision-making? For example, the metrics that the CFO needs to get a good picture of the financial health of the supply chain business are quite different than the metrics the VP of supply chain needs to diagnose, correct, and manage supply chain operations. Each requires its own portfolio of metrics. It’s possible, even likely, that there will be overlap between the portfolios, but there are major differences as well. Even where the same metrics are used, there are differences. Consider the example of inventory:
    • The CFO wants to see total inventory as a percentage of revenue.
    • In contrast, the VP of supply chain wants to see inventory days or turns broken down into its components of raw material, work-in-process, and finished goods to pinpoint whether the source of problems is on the supplier, internal production, or customer side of the business.

 

Define Your Metrics Hierarchy

Because different goals require different metrics, the importance of clearly defining your goals for measuring performance cannot be understated. If your goal is to assess the financial health of the supply chain, for example, you’ll need different metrics than if your goal is to diagnose and correct supply chain issues. The outcome of identifying your goals becomes the input for defining the metrics needed to achieve those goals.

What’s needed is a metrics architecture made up of a network of metrics portfolios, providing a cohesive framework for managing each area of the business and tracking the interdependencies across them.

The Metrics Architecture

While everybody measures in most companies today, the metrics are typically either at too high or too low a level, and they’re disconnected from each other. Consider the following:

  • The CFO knows earnings per share and EBIDTA.
  • Sales knows revenue per salesperson.
  • Customer service knows how long it takes to answer a call.
  • Procurement knows how long it takes to process a purchase order.
  • Supply chain knows on-time shipments.
  • Manufacturing knows its first pass yield.

But what they can’t clearly see is the impact of each on the others. The only place all the metrics come together is in the financial statements, but by the time they get there, they’ve been rolled up, translated, and homogenized so many times they’re barely recognizable. Worse, at this point they cannot be used to truly manage the business.

You need an enterprise metrics architecture that defines the metrics that matter for the different areas of the business. Rather than trying to navigate and distill hundreds of possible metrics to understand how your supply chain is performing, you can hone in on the few metrics that give you the most comprehensive, end-to-end information, allowing you to quickly identify the levers you can use to improve supply chain operations.

A network of metrics hierarchies that cover each area of the business — supply, demand, product, finance, and such — allows a company to:

  • Efficiently track and analyze each area of the business.
  • Clearly see the interdependencies among the different areas of the business. In this way, the metrics architecture can be used not only for analysis of a historical or current situation, but also to do future-facing, what-if analysis and scenario planning.

Case example

Let’s look at a brief example of how a metrics architecture would work. Take the case of a company that creates a high-quality new product that meets customer needs. Marketing launches an initial promotional campaign successfully generates a spike in customer demand for the new product. However, marketing doesn’t communicate this to the supply chain organization. As a result, the company doesn’t have inventory to satisfy the heightened demand, resulting in stockouts and unhappy customers.

How would this situation be reflected in the metrics? We’ll use the graphic below to illustrate.

  • Product— The Product metrics hierarchy on the bottom of the graphic would look great.  As reflected in the first-pass yield numbers, product quality is good, incorporating a high proportion of customer needs, and time to market is short. One problem area that would show up here would be “time to breakeven,” which would be longer than anticipated due to the supply shortage.
  • Demand—The Demand metrics hierarchy on the left side would also look good, and marketing would feel satisfied that its promotional campaign successfully shaped an increase in demand.
  • Supply—The Supply metrics hierarchy on the right would not look so good The inventory days of supply would be great—that is, low—because they didn’t ramp up inventory, but everything else would be showing up “in the red.” Because they had no visibility into the expected increase in demand, they would show poor demand forecast accuracy, and a poor perfect order rating due to the high stockouts.
  • Financial—How does this all flow into the Financial metrics hierarchy at the top? While inventory as a percentage of revenue would be low (which would make the CFO happy), other metrics would suffer: accounts receivable takes a hit, customer satisfaction is hurt due to unmet expectations, allowances and trade promotion adjustments have to be made, and profit

What a metrics architecture allows here is an objective analysis of what went wrong and, therefore, the ability to accurately fix the problem. Rather than everyone pointing the finger of blame at the supply chain organization, the use of a cohesive set of metrics hierarchies would allow a clearer picture to emerge, and thus an enhanced capability to continuously improve the business.

 

Implement for Repeatability

Any measurement of performance at this point would be a baseline set of metrics that can be used for comparative purposes, potentially as a benchmark against peer companies or even different divisions within the same company. But for your measurement strategy to come alive, it should be implemented in technology for repeatability. Only then will it become a real decision support system that will help guide your organization to increasingly better performance.

Fortunately, performance management applications like Silvon’s Stratum solution deliver the built-in data management tools, metrics and analytics needed to measure performance across the enterprise while setting the stage for performance improvement.

Taking the pulse of the business on an ongoing basis through the use of these applications allows you to make course corrections as early as possible to achieve ever-higher levels of performance.

From Performance Measurement to Performance Management

Keep in mind, though, that measurement alone won’t improve performance in the business; it requires an ongoing, repetitive cycle of performance measurement implemented for repeatability through technology.

  • Effective goal-setting—Sticking a flag in the ground as a target gives the organization something to rally around, providing managers and workers guidance on what constitutes success.
  • Consistent monitoring of process and outcomes—Repetitive measurement establishes a history of performance over time—potentially in real time, if desired—and gives process owners feedback on what’s working and what’s not.
  • Performance notification—If something is out of whack, proactively informing the metric owner(s) of the anomaly allows for action to be taken in time to have some effect. This can also cut down on the noise in the system by bringing problem areas to the attention of managers without them having to stumble on the processes that need it.
  • Course correction—Whether slight adjustments are called for to tweak performance, or extensive changes in strategy are necessary to achieve overall performance goals, feedback from the measurement system gives managers the necessary input to make that call and change/adjust business activities.

 

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5 Balanced Scorecards for Manufacturers https://www.silvon.com/blog/5-balanced-scorecards-for-manufacturers/ Thu, 06 Apr 2023 18:01:35 +0000 https://www.silvon.com/blog/?p=2283 The balanced scorecard is a powerful tool for helping companies improve their performance. It provides a clear and concise way to measure...

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The balanced scorecard is a powerful tool for helping companies improve their performance. It provides a clear and concise way to measure progress towards strategic goals, and it helps to align the efforts of all employees with the organization’s strategy.

We always recommend to the manufacturers we work with that they focus on a limited number of KPIs deemed most critical to their businesses when putting their scorecards in place. These KPIs should be quantifiable, relevant to your strategic objectives, and actionable. It’s key that you don’t overload your balanced scorecard with too many metrics, too. Instead, focus on the most critical indicators that will have the greatest impact on achieving your strategic goals.

 

Scorecarding – Best Practices

Here are some best practices for developing and using a balanced scorecard, along with 5 scorecard examples that are ideal for businesses in manufacturing and a number of other industries:

  • Start with a clear strategy: Before developing a balanced scorecard, ensure that you have a clear understanding of your organization’s mission, vision, and strategic goals. This will help you align your metrics with your overall strategy.
  • Develop a balanced scorecard framework: The balanced scorecard is typically divided into four or five perspectives (depending on your business type).  These areas of perspective include financial, customer, internal processes, and learning and growth. We are also seeing more companies include “environmental impact” as part of their scorecard framework. Regardless how many perspectives you examine, each should have its own set of metrics that align with your company’s strategic goals.
  • Communicate effectively: Make sure that everyone in the organization understands the balanced scorecard and how it relates to the organization’s strategic objectives. Use clear and concise language to explain the metrics and their importance.
  • Monitor progress regularly: Review your balanced scorecard on a regular basis to track progress and identify areas where you need to improve. Use the data to make informed decisions and adjust your strategy as needed.
  • Continuously improve: Use the information from your balanced scorecard to continuously improve your organization’s performance. This may involve refining your metrics, changing your strategy, or making operational changes to improve efficiency and effectiveness.

 

Balanced Scorecard – Examples

As mentioned above, the balanced scorecard framework should focus on the key performance “perspectives” of your business.  Highlighted below are example scorecards for each of these areas, including potential objectives for each scorecard and the KPIs you may want to highlight.

A.  Financial Scorecard

Objective:

Increase profitability and shareholder value.

KPIs:

  • Revenue growth rate: The percentage increase in revenue over a set period of time.
  • Gross profit margin: The percentage of revenue remaining once cost of goods sold has been deducted.
  • Operating profit margin: The percentage of revenue remaining after deducting all operating expenses.
  • Return on investment (ROI): The amount of profit generated for each dollar invested.
  • Cash flow: The amount of cash generated or used by the organization over a set period of time.
  • Cost reduction: The percentage reduction in costs over a set period of time.
  • Market share: The percentage of the market the organization occupies. 


B.  Customer Scorecard

Objective:

Increase customer satisfaction and loyalty.

KPIs:

  • Customer satisfaction: The percentage of customers who report being satisfied with the organization’s products or services.
  • Net Promoter Score (NPS): A measure of customer loyalty based on the likelihood of customers to recommend the organization to others.
  • Customer retention rate: The percentage of customers who continue to do business with the organization over time.
  • Customer lifetime value (CLV): The total amount of revenue the organization can expect to generate from a single customer over their lifetime.
  • Customer acquisition cost (CAC): The amount of money the organization spends to acquire a new customer.
  • Time to resolution: The amount of time it takes to resolve customer complaints or issues.


C.  Business Process Scorecard

Objective:

Improve efficiency and effectiveness of internal processes.

KPIs:

  • Process cycle time: The time it takes to complete a specific process from start to finish.
  • Process quality: The number of defects or errors in a specific process.
  • Process improvement: The percentage increase in efficiency or effectiveness of a specific process over time.
  • Resource utilization: The percentage of resources (such as time, materials, or equipment) used during a specific process.
  • Capacity utilization: The percentage of available capacity (such as production capacity or personnel capacity) used during a specific process.
  • Time to market: The time it takes to bring a new product or service to market.


D.  Learning and Growth Scorecard

Objective:

Develop and improve the skills and capabilities of employees.

KPIs:

  • Employee satisfaction: The percentage of employees who report being satisfied with their job and work environment.
  • Employee turnover rate: The percentage of employees who leave the organization over a set period of time.
  • Employee training and development: The percentage of employees who receive training and development opportunities.
  • Employee engagement: The level of commitment and involvement of employees in their work.
  • Innovation and creativity: The number of new ideas or innovations generated by employees.
  • Knowledge management: The percentage of organizational knowledge that is captured, stored, and shared effectively.


E.  Environmental Scorecard

Objective:

Minimize the environmental impact of the organization’s operations.

KPIs:

  • Energy consumption: The amount of energy consumed by the organization over a set period of time.
  • Greenhouse gas emissions: The amount of greenhouse gas emissions generated by the organization over a set period of time.
  • Water consumption: The amount of water consumed by the organization over a set period of time.
  • Waste reduction: The percentage of waste generated by the organization that is recycled or reused.
  • Sustainable sourcing: The percentage of raw materials sourced from sustainable sources.
  • Environmental compliance: The percentage of the organization’s operations that comply with environmental regulations and standards.

 

While financial indicators can certainly provide you with a lot of information about your company’s performance, they don’t give you the whole picture. Non-financial aspects of your company’s business (like product quality, employee turnover and production productivity) enable you to identify problematic trends before your profits are negatively affected. The Balanced Scorecard provides a solid framework for defining the financial and operational matrixes that you should examine and how.

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Improving S&OP with Forecasting Analytics & Business Intelligence https://www.silvon.com/blog/improving-sop-with-forecasting-analytics/ Thu, 16 Mar 2023 14:07:57 +0000 https://www.silvon.com/blog/?p=2237 Sales and operations planning (S&OP) is a consensus-based communications process that provides insight and control over a company’s supply chain decisions. While...

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Sales and operations planning (S&OP) is a consensus-based communications process that provides insight and control over a company’s supply chain decisions. While a manufacturing organization can have an S&OP process in place, though, it can still have issues aligning demand and supply effectively.

Advanced forecasting technologies and processes are needed to improve that alignment. This article quickly explores those technologies and describes how they can improve S&OP outcomes.

 

The Value of Forecasting Analytics
(aka Predictive Analytics)

A demand forecast is a key component of the S&OP process with the ability to predict future requirements with a reasonable degree of accuracy. Unfortunately, seasonality, promotions and unexpected spikes in demand are difficult to forecast with precision when based primarily on human input.  Even when historical patterns are consistent, forecasts created by human input (or gut feel) can be inaccurate.

The creation of an unconstrained forecast should be based on a statistical analysis of time series historical data. This is where predictive analytics (or forecasting analytics) comes into play.  Predictive analytics uses historical data to forecast potential scenarios that can help drive strategic decisions. Using predictive analytics, a forecast baseline can be established that provides the necessary means to initiate fact-based discussions during the S&OP process.

There are a myriad of forecasting products on the market today. The selection of an integrated forecasting and analytical solution should be made by paying careful attention to functionality that enhances the overall effectiveness of sales and operations planning. Here are just a handful of characteristics that a viable software solution should offer:

  • Advanced analytics with optimized model selection
  • Scalability
  • Reduced forecast cycle times
  • Exception-based forecasting
  • The ability to support collaborative planning

It’s important to note that an automated forecasting / predictive analytics solution can significantly improve S&OP cycle times. This is particularly true when a business is constrained by a short forecasting cycle and the ability to quickly create demand forecasts, identify exceptions and make recommendations for change becomes a necessity.

Supporting New Product Forecasting, Too

New product forecasting can also benefit from predictive analytics by providing better information to forecasters responsible for developing new product demand curves. This is possible by basing new product introductions on the evaluation of historical sales data related to “like products.”

Also having the ability to perform a more detailed analysis of key factors like target markets, product functionality, demographics and promotions and discounts can provide additional insight into establishing demand profiles. Then such demand profiles can be applied to a new product forecast with greater confidence level since the forecast is supported by the data.

At the bottom line, automation and forecasting analytics can provide the best level of prediction with a lower degree of risk. The ability to review forecasts by exception using filters and customized list views can help demand planners manage their plans in a more effective and timely fashion. Adjustments can be made quickly to problematic and high-value forecasts while adhering to the S&OP timeline. This results in a more dynamic planning process and detailed evaluation of supply chain drivers as they relate to demand, production and inventory management.

 

Leveraging S&OP with Business Intelligence

Driving S&OP activity throughout an organization can be greatly enhanced by using a business intelligence (BI) solution, as well. Some of these solutions (like Silvon Stratum) can consolidate and organize data from every corner of the enterprise and make that data available to every group participating in the S&OP process in a format that supports their specific reporting and analysis requirements.

Business Intelligence solutions deliver the insight, reporting capabilities and drill-down analysis needed to support the sales and operations planning process. The business intelligence platform that supports the S&OP process should have the following capabilities:

  • Portals and dashboards
  • On-line data analysis
  • Advanced data exploration
  • Report creation (both recurring and ad hoc reports)
  • Report broadcasting (scheduled distribution)
  • Built-in exception management
  • Automated alerting
  • Microsoft Office integration (Excel and Power BI)

A dashboard provides participants in the S&OP process with easy access to specific data and reports that need to be reviewed and evaluated. Advanced functionality such as the ability to drill down on important data elements enables users to perform a more detailed analysis of key business drivers. BI reporting should support the evaluation of specific S&OP metrics like forecast accuracy, forecast volatility, demand consumption, and various supply chain and inventory management liabilities.

 

Investing in the Right Technology

No sales and operations planning initiative can deliver results without full visibility into your company’s data streams. Having access to a single version of the truth in the form of both historical and real-time data spanning the enterprise is essential, together with collaborative planning capabilities.

A comprehensive S&OP process effectively merges predictive analytics and business intelligence with an organization’s consensus-based planning process. The right blend of human and artificial intelligence can boost an organization’s confidence in assessing situations quickly and making decisive moves. You need to implement a technology platform where you can build collaborative plans, increase the transparency of information, and seamlessly connect with key stakeholders to improve your supply chain visibility.

Improving S&OP using business intelligence and advanced forecasting analytics provides a competitive advantage in these ways:

  • Advanced analytics drive the S&OP process via model optimization, event planning, and high scalability.
  • The automation of forecasting tasks improves S&OP process flow and reduces forecast cycle time. This gives you more time to analyze inaccurate forecasts, react to trends and make recommendations for change.
  • The business analytics framework provides the necessary means to collect and deliver information using portals, dashboards, data exploration, consensus planning, and corporate-wide data consolidation. Additional integrations with tools like Excel and Power BI provide the added ability to visualize important KPIs and other metrics and to easily transfer data between spreadsheets and the business intelligence platform for planning, analysis and reporting.

While not all-inclusive, we hope the technologies and processes covered in this article are helpful to you in your quest to improve your organization’s S&OP initiatives.  Keep on the lookout for our future articles on this topic and on technologies and best practices related to sales and operations performance management.

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