The Next Step on the Road to Future Ready
Previous articles in this series presented findings from our joint research with the MIT Center for Information Systems Research (CISR) that has established a pathway companies can follow to become Future Ready. More recent MIT CISR research reveals that Future-Ready companies are 20% more profitable than their industry peers. We pointed to use of a Common Data Model (CDM) as a key enabler to becoming Future Ready.
A CDM that contains comprehensive internal and external information about a company can promptly facilitate business intelligence (BI) and the ability to automate business processes. This third article focuses on the ways BI is important to identifying and prioritizing where to focus for taking action to maximize results and progress toward becoming Future Ready.
How Can a CDM Lead to Rapid Digital Transformation?
…with prompt Business Intelligence and Automation
Identifying and Prioritizing Areas of Focus on the Road to Future Ready
It’s hardly a secret that the more robust a company’s business intelligence (BI) capabilities are, the better its financial performance.¹ BI—in conjunction with the key performance indicators (KPIs) that BI feeds and enables— gives companies the power to make smart, fact-based decisions, to improve their operations, and to enhance the experiences they offer their customers. But if all that is so widely known and accepted, why do more than:
of companies worldwide lack adequate BI capabilities?²
One possible explanation is that the leaders of those companies look at BI implementation and digital transformation and see only a massive undertaking that consumes disproportionate amounts of financial and human resources and takes years to execute. If those leaders looked closer, they might see that today’s business technology marketplace is teeming with affordable BI solutions. Within a matter of weeks, they can stand up a comprehensive BI solution—with KPI reporting and dashboards—that has a positive impact across the business. And today’s technology requires little or no custom coding, thereby eliminating the need for costly special programming.
Rapid Business Intelligence
Rapid BI gets accomplished when business leaders own and drive a focused, intentionally agile process to develop, test, and activate a BI system and a hierarchy of relevant KPIs. At the end of the process, companies will be able to operate differently by using nearly real-time information to run their businesses. Think of KPIs as the guideposts by which leaders steer their businesses.
Typical KPIs that lead to success track both sales and operational metrics and their impact on revenues and profits (figure 1). Measurements along both sales and operational dimensions are necessary because, as joint research by AlixPartners and MIT CISR confirms, companies have to balance investments in customer experience against investments in operational excellence if they are to obtain the best overall results. Overinvesting in the customer experience increases revenues but tends to compress margins because spikes in customer activity increase handling costs that companies cannot manage without comparable investments in operations.
Overinvesting in operations, on the other hand, yields efficiency gains that improve margins but usually have little impact on revenue growth without corresponding digital investments to improve sales and the customer experience.
FIGURE 1: A ROUGH TAXONOMY OF KPIs AND WHAT THEY MEASURE
KPI examples that drive improvements
Typical sales KPIs focus on customers, prices, promotions, referrals, and the sales force. Those KPIs get operationalized by using them to optimize such activities as:
Customer relationship management (CRM) systems are common for pursuing new customers and managing existing ones, but they become much more effective when driven by analytics that isolate the most-profitable potential and existing customers, which get assigned to the best salespeople.
Pricing KPIs, combined with competitor prices scraped from the web and elasticity analytics, enable companies to set optimal prices and adjust them in line with shifting supplyand- demand patterns.
Allocation of Marketing Investments
By analyzing the effectiveness of past promotions across customer and product types, companies can optimize returns from future promotions.
Referrals and Sales Performance Measurement
Tracking sales, associated costs, and return on investment across referral sources and salespeople helps identify the most valuable referrals, the salespeople with the best relationships and results, and underperforming resources and relationships.
Typical operational KPIs focus on profitability, labor investment performance, spending, and asset usage, which management can use to guide operating decisions. Examples are:
BI can deliver KPIs that lead to a granular understanding of relative profitability from customers and products after factoring in the full cost (including service and overhead costs) of each customer and each product. The same analytical method can be applied to channels, contracts, and other profit components. Sales management can then reorient resources and spend toward the highest value customers and prospects—and discontinue products and customers if it is determined that they can’t be profitable.
Returns on Labor Investments
KPI metrics track worker productivity and the layers of management needed to maintain or improve it. Plant managers can use the data to support scheduling, manage head count, minimize downtime, and profile the highest performers to achieve better training and targeted recruitment. Similarly, brick and mortar retailers can use expected store traffic to optimize the number of salespeople on the floor.
By tracking where money gets spent, these KPIs help finance managers identify and understand areas of over- or underspending, which appear on the KPIs as outliers. Regular spend analytics across cost categories and vendors together with comparisons to the budget facilitates prudent cost management.
KPIs that deliver insights into productivity and asset usage help finance professionals determine whether assets are being optimized so they can pinpoint opportunities to reduce costs and increase proceeds from asset dispositions. Typical KPIs cover utilization of plants and equipment, real estate usage, and the performance of other fixed assets.
Getting Started with BI
Companies can create—and start operating— comprehensive BI functions in a matter of weeks. That’s all the time that is needed to set up nearly real-time reports and dashboards that display comprehensive KPIs business operations can put to effective use. From that solid foundation, companies can move on to full digital transformation, wherein sales and operations become optimized through the use of digital methods.
The BI and KPI development process takes a whiteboard-to-dashboard approach that follows agile practices collectively deployed by business, finance, and technology functions (figure 2). In this process, senior management collaborates with operational and functional leads around a whiteboard to produce a hierarchy of KPIs that proceed from observed results to actionable operational steps. Business leaders are accountable for making the BI system a reality and for driving value creation initiatives. They are supported by business and technology managers who jointly design, plan, and implement the system. The managers in turn are supported by functional, financial, and technology experts who contribute to development and execution.
FIGURE 2: THE BI AND KPI DEVELOPMENT PROCESS
Once the whiteboarding team has identified the key information that can be used to improve business operations, business experts can develop a vision of how that information would best be disseminated and operationalized. Next, business experts develop business rules that set forth how to use the KPIs to run operations and make decisions. With those elements in place, the experts then turn to developing reports and dashboards that can be quickly adapted to handle dynamic real-time data.
For example, a medical products company that established a BI system quickly identified large performance discrepancies among product profitability and salespeople. It also became clear that operating functions were being performed with excessive labor costs (figure 3).
FIGURE 3: MEDICAL PRODUCTS COMPANY EXAMPLE
A well-designed BI capability helps business leaders see the path to becoming Future Ready. The BI information reveals insights that can be analyzed and acted upon. After getting BI insights into where the company is making money and where it’s losing money, the BI system can be used to further analyze the key drivers of that performance. Those insights lead business executives to (1) set priorities for where to take action and (2) identify how digital solutions and technology can be used to maximize results from those actions.
Whatever the industry, a strong BI function drives profit improvement— and more.
Each of the following companies generated eight-figure earnings improvements and significant valuation increases:
- A retailer moved from a rudimentary pricing model to a model whose pricing was based on intelligence about competitors’ prices and demand elasticity.
- A consumer products company which trade promotions worked and which didn’t across different customer profiles and geographies.
- A business services company profiled its customers and ranked them by performance, which enabled the company to prioritize which customers to target and retain.
- A manufacturing company improved sales and operations planning by means of demand forecasting and production scheduling.
- A healthcare company used claims management analytics and automation that resulted in higher recoveries at lower costs.
- ‘Why Digital Matters Now: The Road to Future Ready,’ report by AlixPartners based on 2017 joint research with MIT CISR that was updated by MIT CISR in 2021
Meade Monger, founder of Dallas-based CenturyGoal, is an expert in corporate restructurings, transformations and digital strategy. He is currently a PhD candidate in healthcare research.