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Tag Archives: business analytics

CFO Journal: The Big Deal About Data in M&A

“In addition to leveraging intelligent tools, getting an early start and selecting an appropriate data management framework are also essential for increasing M&A transaction value in an environment where data is often an organization’s most valuable asset.”

Read More at The Wall Street Journal >

Harvard Business Review: Why Becoming a Data-Driven Organization Is So Hard

“Right now, the biggest challenge for organizations working on their data strategy might not have to do with technology at all. In the latest NewVantage Partners annual survey, which tracks the progress of corporate data initiatives, corporate chief data, information, and analytics executives reported that cultural change is the most critical business imperative.”

Read More at Harvard Business Review >

Harvard Business Review: The CEO’s Playbook for a Successful Digital Transformation

“The point of a digital transformation isn’t to become digital; it’s to generate value for the business.”

Read More at Harvard Business Review >

CFO Journal: 2025 Finance Predictions: The Pandemic Effect

“As real-time information moves closer to reality, and business analysis grows increasingly automated, finance will likely bolster its efficiency by offloading some responsibilities to captive locations, centers of excellence, and outsourcing vendors—all of which may be held to a higher standard. Lower costs can enable the function to invest in work that is building enterprise value.”

Read More at The Wall Street Journal >

CFO Dive: Data, Communications Pose Hidden Scaling Costs

“The central lesson from the exercise, Nucci said, is the hidden cost of misaligned analytics on a company’s ability to scale its operations efficiently. 

“I regret not taking the time to [centralize analytic operations] and have that single source of truth from a data perspective from the beginning””.

Read More at CFO Dive >

CFO Journal: Assessing Data Management Maturity

Here’s an important question to ask yourself when thinking about data:

What insights do you need to run the business?

In other words, what questions do you need answered, and which metrics would help answer those questions? This may involve financial results or nonfinancial information related to employees, customers, products, and market conditions.

  • Which available data management tools might help? Being able to combine data from multiple sources and getting it to refresh automatically at the right frequency to meet the business need is the ultimate goal. But in the near term, see what you can gather easily through advanced data management tools like the one at or even manually. Start with no more than 10 business questions so you can create visualizations of important results and explore relationships across data points. Once you begin automating your data, you can layer in more components to flesh out the picture.
  • Is the leadership team aligned? All key parties need to agree on what will be measured, how it will be defined, who owns it, who will be accountable for producing it, and the business mandate being addressed. At heavily matrixed companies, getting everyone on board is no easy feat, but taking the time to do this upfront is crucial.
  • Have you identified—and involved—your data ecosystem? As the company reaches certain milestones in, say, enabling automated data feeds with data quality controls or acquiring new tools for insight-driven decision-making, take the opportunity to test concepts in one market or line of business, create a prototype, and socialize your idea to gauge support. Be sure to involve those who will be using the new capability you plan to introduce.
  • Is the workforce suitably equipped? A data ecosystem based on next-generation digital technologies can demand new or enhanced workforce skills and capabilities, such as storytelling with data, problem-solving using advanced analytics, and business partnering. Consider ways to build or acquire the talent you may requireEmployees need a frictionless way to tap into the data flow, understand how to use it, and then act on it.

Read More at Wall Street Journal >

Harvard Business Review: Why Is It So Hard to Become a Data-Driven Company?

“To compete today, companies need to be data-driven. But for mainstream, legacy companies, that’s easier said than done. Despite a decade of investment and the adoption of Chief Data Officers, this survey of Fortune 1000 senior executives finds that many companies are still struggling against not just legacy tech, but embedded cultures that are resistant to new ways of doing things.”

Read More at Harvard Business Review >

The Role of Data Analytics

“The broad reach and wide applicability of data analytics across industries and professions have been known for decades, but the essential role of data analytics in delivering a competitive advantage to businesses, efficiently enhancing value delivery, and revolutionizing the role of business professionals is now undisputed. Even more, the enormity of the impact data analytics can have in times of crisis is nearly unparalleled, as evidenced by its contribution to progress during the COVID-19 pandemic.”

Read more at Strategic Finance Magazine

Transform the Quoting Process for Engineer-to-Order Manufacturing with Cost-Based Quoting

by Matthew Smith

For engineer-to-order businesses that manufacture products designed by their customers, the traditional CPQ process does not work. By its very nature, the CPQ process collects a set of pre-defined product options or features (Configure), then sums up the prices for each item selected (Price), and then presents the final pricing to the customer (Quote).

Traditional CPQ applications presume that every possible option or feature for a new product is already invented, costed, and priced. In an engineer-to-order world, this presumption falls apart. Successfully quoting new business requires inventing, costing, and pricing the product before a quote is sent to the customer.

The Cost-Based Quoting Process

Cost-Based Quoting (CBQ) is a process that differs from CPQ by supporting three phases: the product invention ideas, full costing of the product, pricing of the product, and presenting of the quote. In addition, the CBQ process is accompanied by an overarching management and control system that provides workflow, approval, oversight, and analysis of the process. Ultimately, a properly executed CBQ process brings consistency, accuracy, and speed to the effort.

In an engineer-to-order business, inventing the product starts when a customer presents a concept for a new product. The product details are shared by the customer through drawings, specifications, or other descriptive documents, and the relevant data is captured to move forward. The compiled customer information is structured and passed to product engineers who establish the product specifications, bill-of-materials, and process routing for the new product.

The next phase of activities focuses on calculating product cost and price answers. The associated costs and margins are typically calculated in three steps to determine the final selling price to the customer:

  1. The material, production labor, and overhead costs are computed.
  2. Specific equipment like crane scales (visit website), tooling, engineering, design, or other required non-recurring costs are summed, amortized, and added.
  3. Freight and distribution costs, SG&A coverages, royalties, required profit margin, and other monies are assigned to the product.

Lastly, the price is approved and presented to the customer in the form of a completed quotation. Along the way, the internal team provides the necessary approvals, analyzes the quote performance, and monitors the opportunities and risks of all active quotes. If needed, quote details can be automatically shared with downstream systems and processes.

ImpactECS by 3C Software enables Cost-Based Quoting processes through its flexible architecture and ability to connect data and business rules. Our platform supports the unique needs of quoting, commercial, manufacturing, product, finance and executive teams through an end-to-end quoting process with deep costing insights.

The three phases of CBQ described below – inventing the product, calculating costs and profits, and sharing and analyzing results – are the road map to improved profits for engineer-to-order and custom manufacturing companies challenged by an ineffective quoting process.

Phase 1: Invent the Product

Collecting product data from customers is unique for every company and industry, with information coming from spreadsheets, emails, CAD drawings, CRM systems, PLM tools, or any combination. Streamlined data collection process with options to collect, organize, and validate the data are needed. ImpactECS creates environments to support data entry through custom interfaces, editable product templates generated based on user attributes, or by creating clones of existing products.

Next, the list of materials is needed for the invented product. To create the new bill-of-materials, two things are required – access to historical BOM information and a straightforward way to add new materials and pricing. ImpactECS provides a simple process for setting up new product BOMs. Users browse and select from existing raw materials, maintain or override prices of existing materials, or create new materials and enter price estimates in one place. After the new BOM is established, the production routings are defined with similar capabilities to browse for plants and processes, choose from routings of similar products, or manually enter the process steps, labor rates, and machine times.

Engineer-to-order companies who use product lifecycle management (PLM) systems to often struggle to invent BOMs and process routings. They are limited because PLM rules are too structured and require a level of detail that is often not available during the quoting process. As an example, PLM applications often insist that all raw materials or purchased components used in a new product must already exist in the system with a valid purchase price. Or, the new product must have a valid finished good ID, documented ECO or ECN process for multiple versions, or even complete product master data in the ERP system. While these requirements and compliance processes are certainly relevant – and required – for production, they hinder the flexibility needed to generate quotes when the products or their materials do not exist.

Phase 2: Calculate Costs + Prices

The costing function is core to ImpactECS’ capabilities – with the ability to create and centralize costing rules that determine how to calculate cost answers for the new product. Raw material prices are either manually entered, retrieved from pricing tables, or the system can invoke a procurement activity to identify a supplier and estimate the price.

Determining which cost center and machine rate data to use when costing the process routing often depends on the company structure. For companies with their own factories and equipment, ImpactECS can dynamically calculate cost center rates or import them from the ERP standard cost module. For companies with subcontractors, just substitute the calculated rates with the agreed contract rates to calculate the routing cost. Cost comparisons between production locations or blended production costs from multiple locations are also available options when costing the routing.

The centralized costing rules include calculating costs for freight, distribution, SG&A, cost of capital, and any other relevant costs. Like materials and routings, users have the option to override default values for each cost category to both drive consistent costing processes and provide the flexibility required to generate accurate, realistic quotes.

With the costs calculated, ImpactECS can apply the desired profit margins to calculate recommended selling prices and analyze different scenarios for the quote – like order quantity breaks, payment terms, and pricing conditions – to determine the true profits. The platform can compare costs with target or competitor pricing if available to show the realized margin at each price point. ImpactECS also manages approval workflows that include stakeholders across departments and maintains quote versions to improve speed and efficiency of the quoting process.

Phase 3: Share Quotes + Analyze Results

Once pricing is approved, ImpactECS can generate formal quote documents or send the results to CRM, ERP, or other downstream systems to complete the quote process. Quote simulations makes it possible to revalue quotes with updated commodity, raw material, or other input costs as they age to manage risk and negotiate terms.

Additionally, ImpactECS’ dashboards and reporting features provides insights into overall performance of the quoting process. Users can access information like the value of outstanding quotes by customer, business unit, product type or region, monitor quotes by stage or activity, and evaluate win/loss analytics to identify opportunities.

Time to transform to Cost-Based Quoting

Companies that build products based on unique customer requirements need consistent, efficient, thorough quoting processes that eliminate under- or over-quoting, reduces errors, and provides one place to manage materials and routings, calculate costs, apply margins, and analyze results. And one thing is certain, traditional CPQ applications don’t fit the bill. Cost-Based Quoting with ImpactECS gives finance and commercial teams the ability to transform the quoting process into a competitive advantage.