The new COO was a recent external hire tasked with transforming this wholesale reseller of IT products into a national competitor. The sales team focused on large, global customers, but the executive leadership team (ELT) believed that the needs of smaller, national customers in North America provided a segment that the globally-focused sales team overlooked and struggled to serve profitably.
This national strategy looked great on paper, but it depended on the ability to achieve more profitable execution than current levels. Consequently, the COO launched an internal analysis of the company’s past profitability and performance.
The findings did not inspire confidence. Over the past decade, the company had pursued performance improvement by investing relentlessly in technology, deploying a leading
CRM system, upgrading its ERP application, and acquiring a host of ancillary applications: a best-of-breed spend management application, a new general ledger (G/L), and several more. Each new technology arrived as a disruptive, costly, “big bang” event promising breakthrough results. In practice, the promised paybacks never materialized, and each technology created as many issues as it claimed to resolve. For example, few provisions were made for interoperability, requiring that skilled employees add new, costly drudge tasks such as “swivel-chair” data transfers and reconciliations between applications.
The technologies claimed impressive functionality, such as built-in artificial intelligence (AI), reporting, and workflow. However, these features came with drawbacks:
• Some were too complex or time consuming to be used by average employees.
• Others were costly add-ons that triggered even more drudge work.
The COO felt that standardization could help “de-layer” and simplify these interconnections so that automation (APIs, RPA, AI/ML, and workflow) could perform these tasks.
She also wanted an improvement approach that was the opposite of the previous “big bang” disruptions: it had to be consistent and build in cumulative operational capabilities that could survive employee turnover.
The wholesaler is an IT reseller organization, headquartered in the western U.S. Originally launched a half century ago, the business remains privately held, but with significant investment from a consortium of private equity (PE) firms.
The PE board members help moderate the “sales-at-any-cost” culture to include an emphasis on sustainable shareholder value. They backed the new COO’s cautious approach to ensuring a profitable national scale-up.
The outside investors were drawn to The Lab’s rapid, data-driven assessment that prioritized process standardization prior to automation. The project scope included documentation of existing end-to-end business processes from marketing and sales through fulfillment and product returns.
Their primary objective was to discover valuable opportunities to optimize the past investments in technology to help scale up existing operations to the national level while increasing margins.
The National Scale and Profitability (NSP) initiative began with an eight-week Phase I analysis across all U.S. locations, covering the major end-to-end business processes, including:
The Lab deployed our proprietary wholesale distribution standardization templates, including:
• Industry standard KPIs
• Related data taxonomies
• Business process maps
• Operations benchmarks
• Best practices
• Automation “use cases”
• And more
These enabled rapid, remote documentation and analysis of more than 85 percent of employee work activities (approximately two minutes each), while only requiring one hour per week of any subject matter expert’s (SME’s) time.
During the Phase I analytical effort, The Lab identified over 200 improvements. Just over 60 percent of these represented non-technology standardization improvements that boosted operational effectiveness, reduced avoidable rework, and/or enabled automation.
While the remaining improvements were technology-dependent, no new systems were required.
• Roughly half could be automated using the existing technology after the work was standardized.
• The remainder were automated using robotic process automation (RPA), and small, low-code applications (e.g., automated forms, onboarding apps, etc.).
• Most of the necessary technologies were already deployed in the business.
• Many could be further augmented with artificial intelligence (AI) for simple decision-making and proactive, real time notifications.
All of the improvements could begin implementation immediately. Progress could be achieved incrementally, without the risk of a “big bang” event. Each area could proceed at its own pace as part of a coordinated, transformational road map.
The end-to-end flow, or value stream, from sales prospecting through returned goods processing, was fragmented, poorly documented, and included few key performance indicators (KPIs):
Sales
The sales organization dominated operations. And their actions—often costly and counter-productive—were generally unchallenged.
For example, reps often delayed order submissions merely to increase their incentive compensation.
Order management and fulfillment
The lack of order-status transparency drove excessively high levels of costly customer queries for updates, further eroding margins. Order documentation was under-standardized and often informal, making it difficult to resolve disputes in favor of the company.
Product returns, like orders, were often timed to benefit monthly margins and related compensation.
This often resulted in expiration of return cycles from manufacturers—leaving the company with obsolete or unsellable goods.
A relatively new enterprise resource planning (ERP) system was also underutilized because order processing and warehouse staff preferred their familiar spreadsheets and email.
Customer service
As a result of all of the above, customer experience suffered, while order-management costs increased and inventory management was unnecessarily difficult.
A state-of-the-art customer relationship management (CRM) application was underutilized because sales reps disliked the transparency it delivered.
Pricing discipline was lax, fees were waived, and unexplained discounts proliferated.
The COO and the PE board members knew that the business needed a “transformation,” but were loath to use that word; they wanted change without disruption. From the analysis they knew they had sufficient, up-to-date technology infrastructure (cloud-based ERP and CRM systems). They worked with The Lab to craft a “light-touch, minimally-invasive” approach to standardization implementation.
It began with a curated list of “Super KPIs.” These were performance indicators that subtly delivered three critical transformational capabilities at non-disruptive “nano-scale”:
1. Prediction:
– Which customers were likely to leave?
– Which were candidates for profitable cross-sales?
– Which orders were likely to require substitutions?
– Data analysis helped select KPIs that answered many of these critical questions.
2. Preemption:
– Who should be notified to avoid the consequences of errors or customer dissatisfaction?
– Who should be notified of promising sales opportunities?
– KPIs linked with RPA bots, and sometimes basic artificial intelligence (AI), can easily deliver preemptive capabilities.
3. Prescription:
– What root causes can be addressed to institutionalize the learnings from above?
– Selected KPIs can point the way and store many of the insights to help improve forms, business processes, and organizational responses.
This is how the executive leadership team (ELT) was able to gradually transform the enterprise without disruption. Only the “critical few” data elements, dashboards, and work activities were changed at each step, supported by fact-based data analysis.
Notifications could be sent confidentially to employees and managers to help them predict and preempt, avoiding uncomfortable “coaching” sessions. Improvement goals were established for each Super KPI, and the organizations involved were free to perform the work with any mix of resources they chose: internal resources, The Lab’s resources, or others. The Lab maintains a three-tiered service offering structure (plus ongoing post implementation support) to make this approach as flexible and sustainable as possible for clients:
The Lab implemented more than 200 standardization improvements that reduced rework, improved service levels, and enabled automation across the enterprise. Examples:
The Lab provided hassle-free, post-implementation hourly sustainability support for this client to maintain automations, process standardization, and operational data analytics models implemented during the Phase II engagement.
If the client’s team was not up-skilled enough to perform any needed automation updates, they leaned on The Lab for Tier 3-level support. If analytics dashboards required additional views or data connected, The Lab’s team was a simple phone call away.
At The Lab, we’ve spent three decades refining every aspect of our transformation engagement model. We’ve made it easy for clients—from the C-Suite to the front line—to understand and manage the initiative:
• Minimal use of client time: One to two hours each week, maximum.
• Measurable benefits: Typical 12-month ROI is 3x to 5x.
• Pre-built templates and tools: Process maps, data models, bots, and more.
• U.S.-based, remote delivery: Nothing is ever outsourced or offshored.
Since 1993, The Lab has led the industry in eliminating risk for our clients. Whether your engagement involves a handful of bots or wall-to-wall transformation, we make it easy to do business with us:
• Fixed pricing and clearly defined scope
• Pre-project feasibility/value assessments at nominal cost
• Early-out checkpoints and options
• Money-back guarantees
The best way to learn about The Lab’s patented Knowledge Work Standardization® approach is to book your free, no-obligation 30-minute screen-sharing demo. And you’ll get all your questions answered by our friendly experts. Simply call (201) 526-1200 or email info@thelabconsulting.com to book your demo today!
