Data maturity is a major priority for innovative manufacturers today. However, despite the considerable advances in the availability and capabilities of dynamic reporting tools as part of DX (digital transformation) innovations, manufacturers are still wondering where the additional data insights—and their perceived benefits—are to be found.
A recent 2022 survey of manufacturing organizations found that even though 72 percent of participants had invested in new technologies during the pandemic, only 44 percent found those investments were providing them with actionable data. In fact, 19 percent claimed to have not harnessed any data insights at all with the additional investments. Something isn’t clicking, and it’s likely that these manufacturers are struggling with data because they have not laid the foundational groundwork to capitalize on the benefits of more advanced digital tools; their operational digital maturity is out of step with the investments they’ve made.
Data organization and value mining can take many forms within manufacturing, but the more mature and robust your data strategy is, the more operational and financial rewards you’re likely to receive. Most organizations can identify their current state with one of the four stages on the data maturity journey—crawl, walk, run, or sprint—and then set their sights on the next stage for further improvements. Let’s review each one.
Crawl: Account and lead management
The first stage of data maturity as a manufacturer is ensuring you have a firm grip on account and lead management. This is the foundation of all other downstream enablement, so it’s critical that you take your time mastering the perfect “Crawl” before starting to walk. This stage includes creating a well-structured and well-managed home for account records and hierarchies, their contact relationships, and supporting lead management processes that gather, enrich, and align with your account data model.
A CRM tool, if you don’t already have one, is a great way to make sure you have a structured account and customer engagement model that keeps ongoing tabs on who and where your customers are, what products they do or don’t have, and how their own organization is structured. And it’s CRM (or, more precisely, mature data management within these tools) that provides value to manufacturing organizations striving to extract actionable insights within big data. Without this “Crawl” foundation, you won’t be able to compete with the organizations that are 6.3 times more likely to go to market faster and three times more likely to expect significant near-term valuation increases.
Salesforce CRM is an excellent choice for managing your foundation of “Crawl” information and empowering your sales reps with a fuller understanding of the customer lifecycle. The goal of CRM is to accelerate and grow sales, and CPQ (Configure Price Quote) tools are another add-on to the CRM base that can really amp up your quote to cash process for better, faster selling—but that’s something you’ll want to save for after your crawl stage is proven out and well-adopted. In short, crawl is all about automating the critical sales functions and establishing good data maturity standards to carry transactions and customer relationships forward: sourcing and sending quality leads to the right people, winning new and managing existing accounts effectively, and having account-based insights and product information at your fingertips for improved selling.
Walk: Partner enablement and CPQ
Walking is an exciting time, whether you’re an infant or maturing your data practices. In manufacturing, due to high volumes and disparate sources of data points, this stage is a crucial time for turning towards better partner management and serious consideration of CPQ.
Partner enablement is really just extending (not reinventing) the automation you’ve already put in place with your internal sales department and sharing it with your network of distributors, suppliers, resellers, and even logistics partners to benefit everyone bringing your products to market. Many manufacturers depend on partner channel sales models to penetrate, grow, maintain, and otherwise keep their business afloat, so anything you can do to make partner sales more seamless and effective is an essential consideration during the walk stage.
Since partners can usually generate and manage leads and deal opportunities, you need to empower them with the data to co-sell and collaborate on the selling motions, processes, forecasting, and reporting activities alongside your own team. You can also extend this data collaboration further with joint marketing funding, community support portals, multichannel collaboration platforms, and more to ensure your partners look, feel, and act like an integrated extension of your business. Stanley Black & Decker is a Salesforce customer leveraging the platform for more effective partner data management that gets answers where they’re needed quickly. Because, as Joanna Sohovich, Global President of Stanley Engineered Fastening, says, “The common thread throughout our business is speed. The people who represent us in the marketplace – franchisees or distributors – need answers quickly because demand is perishable.”
CPQ is another element of the walk stage that will drive dramatically faster, more successful deals for your business. Integrating Configure-Price-Quote tools into your CRM and its selling motions can help internal and external sales teams navigate complex, voluminous product catalogs; ensure your products’ configurations are feasible and fit for purpose; protect and apply pricing rules; bundle together warranties, accessories, or available options; and overall ensure a proposal for the right product at the right price gets to your end customer—and at the right time (as soon as possible!). At the same time, a well-built CPQ guides and enhances the data capturing and staging process to streamline downstream processes and build even more robust customer profiles, expanding your data maturity and business intelligence capabilities. CPQ can automate necessary approvals in record time to generate professional quotes and signature-ready contracts based on existing customer and deal-based data. Research (and common wisdom) shows that a vendor who is first to produce an accurate quote to the customer can almost double their chances of winning the deal; this is a huge advantage not only for your bottom line but also for building customer relationships or solidifying loyalty in existing clients while minimizing the amount of time your sales reps spend doing tedious tasks, instead of actually selling. CPQ is, for many, a significant step toward achieving true customer 360 insights, data governance maturity, and digital transformation enablement.
Run: Fulfillment & Service
The “Run” stage of data maturity for manufacturers focuses on two critical functions: deal fulfillment and product servicing.
No matter how world-class your sales capabilities are, if you cannot deliver on what is sold, your “Run” stage will be understandably very short-lived. Many manufacturers struggle to bridge the gap between an accelerated, efficient sale and a similarly expedient, streamlined downstream fulfillment process. Often this is due to poor data controls at both the Account and Deal level; in other words, the data needed to facilitate a production, delivery, and fulfillment experience that matches that sales excellence is simply overlooked and left to these teams (including finance, billing, and revenue operations) to figure out. An exemplary “Run” design ensures the end-to-end capturing of critical fulfillment information is part of your data maturity journey.
Now that your data maturity is optimally managing and delivering product, customer, and partner data, you’re a prime candidate for extending smart data management to your service agents delivering repair and maintenance—either virtually or on the ground. A good “Run” strategy will focus on streamlining day-to-day operations and creating a more seamless experience for customers by empowering field and remote agents with the data they need in real-time—in other words, servitization. When expirations are approaching, when an emergency malfunction occurs, or when a customer is expressing interest in upsell products, your team should be one step ahead with information at the ready to take action. These modern, empowered service teams—often relabelled from traditional “cost centers” to “value delivery teams” in recognition of their achievements—simply cannot achieve this without a strong data backbone driving every step of the customer lifecycle.
Sprint: IoT and eCommerce
Finally, the “Sprint” stage is the holy grail of manufacturing data prowess. This is for manufacturers ready to make a big impact and explore the possibilities of both IoT (the always-on, always-connected Internet of Things) and eCommerce in an industry that has traditionally shied away from such business strategies. In many ways, this is ironic since manufacturers are often excellently positioned to integrate IoT devices and capabilities into their products and their data gathering/management infrastructure. These can be integrated right alongside existing additional product insights that can help you stay ahead of factory floor errors, unlock unique product usage understandings, flag imminent failures or performance issues, or identify potential research and development opportunities to gain market share—all thanks to seamless machine-delivered data. It’s a major win for efficiency, and that’s why 98 percent of companies adopting these technologies cite this as the top motivator for investment.
Next, eCommerce is a unique opportunity for additional revenue and market attention for manufacturers ready for the pivot. By taking a few lessons from the B2C success of other innovative industries, you can directly reach your customers and delight them with seamless experiences that build up brand loyalty for you rather than just a network of distributors alone. Of course, if you have a robust and loyal partner sales model and network in place, your eCommerce strategy must be designed not to isolate but rather to support or complement these channels. An excellent example of this can be cited from manufacturers who provide customer-serviceable replacement parts or add-on products in high demand. With the robust data foundation you’ve already achieved up to this point, not only can you identify, measure, and efficiently test this potential go-to-market strategy using data-driven decision processes and performance measures, but then expanding and integrating your eCommerce model to partners, new customers, and existing clients alongside marketing efforts will be made that much easier.
Are you looking to take the next step in your manufacturing organization’s data maturity journey? Simplus has helped manufacturers at every stage in defining value in digital roadmaps, critically assessing their data maturity priorities, and connecting siloed systems and processes into one powerful single source of truth to streamline operations and deliver actionable data insights at every internal, customer, and partner touchpoint. Reach out, and let’s talk.