Part 3: The Value of Taking a Spec-First Approach

Posted on 
July 19, 2022
Mike Anderson
VP, Digital Transformation
Isabella Reed
Digital Transformation Consultant

In Part 1 of The Value of Taking a Spec-First Approach series, we covered why a compelling business case is important and what key components are typically included. In Part 2, we outlined the four key steps in crafting a rock-solid business case. Now we want to bring it all together to look at where companies are seeing the most value from taking a spec-first approach and what it ultimately means for their bottom line.

In our work of  discovering and quantifying uncovered value when taking a spec-first approach, we’ve found that specifications are one of the most broad-reaching data points in an organization. From product, to quality, to sales, to marketing, to sourcing, to leadership; accurate specification data is a must-have to deliver the right product, to the right customer, for the right margin.

Unfortunately, many companies just do not have this level of data granularity, which can manifest itself in numerous ways. However, for companies who have pivoted to a spec-first approach, cost savings, revenue acceleration, and risk mitigation  are the top three areas of quantifiable value.

How to Cut Costs, Responsibly

While these three areas are not laid out in any particular order, we find that cost savings is one of, if not, the largest driver when it comes to software solutions that affect product data. Due to manufacturing constraints, sales capacity, or numerous other factors, it may not always be feasible to grow revenue by producing or selling higher volumes. Because of that, many companies look to optimize margins, and responsibly cutting costs is one of the most impactful levers.

Here are a few areas where taking a spec-first approach creates tangible value.

Reduced Cost of Poor Quality - A division of a global life sciences company took a spec-first approach and was able to achieve a return on their investment within two months! How? By harmonizing their spec data, they were able to reduce manufacturing scrap by $200,000 in the first three months of going live with the solution. Additionally, the visibility they had into alternate components allowed them to reduce lead times by over 80%, enabling one of their customers, a producer of COVID-19 vaccines, to avoid a production line shutdown.

Improved Control of Suppliers and Sourced Materials - With the recent supply chain challenges seen worldwide, visibility into suppliers and sourced materials is more important than ever. Sourcing from a single supplier with no secondary or tertiary vendors approved is not only a risk to production timelines, but also leads to reactive buying which drives significant cost increases.. The ability to capture data for approved suppliers at the ingredient or component level is a way to mitigate risk and avoid unexpected price increases.

Reduced Packaging Spend - One of the most-common areas companies see tangible benefits is packaging spend. In a lot of cases, it’s just seen as a necessary evil and it costs what it’s going to cost. However, it doesn’t need to be that way. By capturing data across all packaging specifications in a centralized system, businesses can report on the packaging being used across all products today and make more intelligent business decisions on where consolidation and elimination can occur going forward.

One great example is from one of the United States’ largest producers of carrots. After digitizing their corrugated specs, they were able to save over $2 million in cost in just two separate RFP events. Not to mention, both of those occurred within one year of going live with their specification management system.

Revenue Acceleration

A close second for the most impactful benefit of accurate specification data, after cost reduction, is revenue acceleration. If the new product development process takes longer than it should; or if operations teams need clarification whenever products are manufactured; or if quality undergoes an arduous process to determine which lots were affected by a recall, then time to revenue is directly impacted. While not exhaustive, these are a few metrics that can be improved by taking a spec-first approach.

Faster New Product Development/Innovation (NPD/NPI) Cycles - Product Lifecycle Management (PLM) tools help address the process and data management challenges related to creating new products. Yet even with a PLM tool, there are often significant disconnects between teams and stages in the NPD cycle. Collaboration tools like email, phone calls, Slack, or Teams often leave room for duplicated data and incorrect versioning, which slows down the overall cycle time. Pair that with static documents and standalone systems, and it causes situations where ‘heroic efforts’ are needed to launch products on time, or at least with minimal delay. The faster these bottlenecks can be addressed through a single platform for specification data and communication, the faster companies can ship products and recognize revenue. As a minimum, companies that take a spec-first approach see cycle time improvements of 10-14 days.

Reduced Time Off Shelves During Recalls - One of the most challenging tasks during a product recall is identifying what caused the recall and where the failure occurred, especially if there are multiple suppliers involved in the value chain. In order for companies to inspect the cause, they must remove their affected product from circulation. Lack of visibility into the intersection of supplier data and specification data causes products to be removed from shelves longer than necessary, while companies uncover the cause of the recall. However, taking a spec-first approach allows for that data to be married in a single system, even capturing lot code and inbound quality data. With that granularity, root cause analyses can be performed quickly and efficiently, allowing the problem to be identified and rectified faster.

Streamlined Reformulation and Variation to Meet New Market Demands - SKU proliferation is a phenomenon that’s been observed over the last several years. As consumer demand increases, companies’ increase the variety of their product offerings:  more flavors, more sizes, and more formats of existing or new products. This phenomenon is vertical agnostic - industries from consumer packaged goods, to high tech manufacturing, to automotive, and more are observing SKU proliferation. This SKU explosion leads to a nearly unmanageable amount of product data; from different formulations, to retailer-specific packaging, to different manufacturing instructions based on the machinery production. With a new product variety introduction, companies often need to start the NPD process from scratch, or close to it, which increases the overall cycle time. By taking a spec-first approach, companies can easily take data from existing products, make the necessary alterations, approve only these changes, and get the new or updated products manufactured and into the hands of consumers faster.

Risk Mitigation

The third area we will focus on is risk mitigation, whether that be from regulatory bodies, poor data quality, or consumer impact. Poor specification data can lead to wrong product versions ending up in the wrong country, non-compliant materials used to create non-sellable items, or even lower margins from poor costing data. Getting this data right on the front end can significantly mitigate the financial and reputational risk possible from poorly produced or poorly tracked products.

Reduced Risk of Regulatory Non-Compliance - Almost in parallel with the explosion of product variations, product regulations imposed by governments and extra-governmental bodies have increased exponentially. From topics like Extended Producer Responsibility (EPR), to taxes and import bans on certain material usage, the regulatory environment has become extraordinarily complex for most businesses. A key to staying on top of the ever-changing environment is to have better control of specification data. That one point alone is saving them hundreds of thousands of Euros each year. Beyond that, a global chemicals manufacturer has been able to ensure that correct product formulations end up in the correct countries, avoiding significant fines from when those issues had occurred in the past.

Improved Data Quality through Robust Data Validation - Ensuring correct data has historically been a job for large teams of people, taking numerous man-hours to ensure data accuracy and cleanliness. As the complexity of data has increased, so have the teams needed to maintain it. Outside of the human cost, the risk of inaccurate data causing incorrect production runs, higher cost of poor quality, and slow time to market has grown as well. Taking a spec-first approach allows organizations to be more proactive with their data, driving better outcomes. A leading US-based producer of fruits and vegetables has seen incredible improvements after digitizing their specification data. Before utilizing a specification data management platform, they required a person to oversee data at every single production facility. However, after implementing an SDM tool, they were able to avoid $1+ million in annual salary costs across more than 20 facilities through the data entry, automation, and validation capabilities that a robust SDM tool can offer.

Deep Visibility into Sustainability Metrics - As it stands today, many companies struggle to have accurate and easy visibility into how they are progressing toward their defined sustainability goals. Those that do have visibility often utilize swivel-chair processes to take data from one system and enter into their Life-Cycle Analysis tool to calculate a product’s environmental impact. Often, this leads to directional guesses, rather than precision around those calculations. Deep data capture at the ingredient, formula, packaging, and finished good levels allow for precise knowledge of materials used, and paired with actual production volumes, reporting that has typically taken weeks or months can take mere days.

One European cosmetics company is doing just that by taking a spec-first approach. By digitizing their key specification data, they are able to marry production data from their ERP with exact material usage data to ensure they are paying exactly what they owe in taxes, nothing more.Without a doubt, taking a spec-first approach has tangible, meaningful impacts to organizations that adopt it. From driving significant margin improvements, to accelerating time to revenue, to mitigating risk, there are numerous proof points that articulate exactly how business value is created through specification data management. Regardless of what industry you find yourself in, better control of specs can drive top- and bottom-line gains.

If you are interested in learning more about what a spec-first approach can mean for your business, Specright’s Digital Transformation Advisory team can help.

Learn more about the value of taking a spec-first approach: VIEW PRESENTATION.


Mike Anderson

Mike is VP of Digital Transformation and Sales Operations at Specright, where he leads teams focused on defining and meeting customer outcomes and building effective sales strategies. Anderson has spent the entirety of his career in the Salesforce ecosystem in various roles at Apttus and Conga, as well as time at Deloitte implementing Salesforce technologies for enterprise clients. He is a proud graduate of Montana State University in Bozeman.

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