Knowledge Management Processes
3.7 Intelligence Enterprise Architecture and Applications
3. Customer to business (C2B). Networks also allow customers to reach out to a wider range of businesses to gain greater competitive advan- tage in seeking products and services. Businesses such as Priceline.com (travel services) and Lendingtree.com (financial services) employ the C2B model to enable customers to secure rapid quotations and secure immediate purchases on relatively volatile products (remaining airline seats and changing loan rates, respectively). Similarly, the introduction of secure intelligence networks and on-line intelligence product librar- ies (e.g., common operating picture and map and imagery libraries) allows consumers topullintelligence from a broader range of sources.
(This model enables even greater competition between source provid- ers and provides a means of measuring some aspects of intelligence utility based on actual use of product types.)
4. Customer to customer (C2C). The C2C model automates the media- tion process between consumers, enabling consumers to locate those with similar purchasing-selling interests. eBay.com is the primary commercial example of C2C, brokering between diverse buyers and sellers worldwide on an limitless variety of items, based only on free- flow supply and demand. Intelligence nets that locate and connect collectors, analysts, operators, and even consumers with common interests introduce the C2C model, for all are consumers of intelli- gence at varying levels.
• Require intimate understanding of business operations and must adapt those operations to the changing threat environment, just as businesses must adapt to changing markets.
• Manage a supply chain that involves the anticipation of future needs of customers, the adjustment of the delivery of raw materials (intelligence collections), the production of custom products to a diverse customer base, and the delivery of products to customersjust in time[33].
Consider the general business enterprise model (Figure 3.11) that can directly represent an intelligence enterprise. The enterprise maintains a business strategy to define, measure, and monitor the value of goods and services deliv- ered to customers. The model includes both a front office, which services cus- tomers (intelligence consumers) and a back office, which includes the supply chain (intelligence chain) and the supporting business intelligence operations that monitor the supply chain and adapt to customer needs.
The enterprise strategy guides the entire enterprise by the value proposi- tion, goals, and measures defined in the last section. The components of the BSC, for example, can be correlated to the functions within the architecture.
Internal goals influence the BI and SCM components, while customer goals guide the implementation of CRM functions. Learning goals guide the imple- mentation of organizational development across all functional areas. Financial
Tasking
Collection
Dissemination Enterprise
strategy
Human resources mgt
Financial and intellectual capital mgt
Operations analysis Business operations
Business Intelligence Competitive
intelligence
Order capture Plan-schedule
Supply Chain Mgmt
Processing analysis Customer Relationship Mgmt
Back office applications Front office applications Advertise
products/services Customers Marketing
Procurement Manufacture Logistics shipping Customer
service
Figure 3.11 Enterprise architecture model related to the intelligence business model.
goals are achieved as an effect of these other activities; for this reason, attention to the architecture is critical to establish the organization’s functional base, which minimizes transaction friction in front- and back-office functions.
3.7.1 Customer Relationship Management
CRM processes that build and maintain customer loyalty focus on managing the relationship between provider and consumer. The short-term goal is customer satisfaction; the long-term goal is loyalty. Intelligence CRM seeks to provide intelligence content to consumers that anticipates their needs, focuses on the specific information that supports their decision making, and provides drill down to supporting rationale and data behind all conclusions. In order to accomplish this, the consumer-producer relationship must be fully described in models that include:
• Consumer needs and uses of intelligence—applications of intelligence for decision making, key areas of customer uncertainty and lack of knowledge, and specific impact of intelligence on the consumer’s deci- sion making;
• Consumer transactions—the specific actions that occur between the enterprise and intelligence consumers, including urgent requests, sub- scriptions (standing orders) for information, incremental and final report deliveries, requests for clarifications, and issuances of alerts.
Automated CRM capabilities have been deployed in the electronic retail- ing community with growing success, employing the knowledge of electronic transactions (from customers online browsing habits in online catalogs to their personal purchasing history) to better understand customer interests. Similarly, as intelligence has embraced wider dissemination on electronic networks, there are strong analogies between commercial retail CRM and potential intelligence CRM functions (Table 3.12). CRM offers the potential to personalize intelli- gence delivery to individual decision makers while tracking their changing inter- ests as they browse subject offerings and issue requests through their own custom portals.
3.7.2 Supply Chain Management
The SCM function monitors and controls the flow of the supply chain, provid- ing internal control of planning, scheduling, inventory control, processing, and delivery. Building on earlier generation enterprise resource planning (ERP) functions, SCM functions can also extend beyond the enterprise to coordinate the supply chain with suppliers (at the front end) and external customers (at the
delivery end). SCM is the core of B2B business models, seeking to integrate front-end suppliers into an extended supply chain that optimizes the entire pro- duction process to slash inventory levels, improve on-time delivery, and reduce the order-to-delivery (and payment) cycle time. In addition to throughput effi- ciency, the B2B models seek to aggregate orders to leverage the supply chain to gain greater purchasing power, translating larger orders to reduced prices. The key impact measures sought by SCM implementations include:
Table 3.12
Business Customer and Intelligence Consumer Relationship Analogies
Business CRM Intelligence CRM
The customer: a purchaser of goods and services. The intelligence consumer: an authorized person who uses intelligence or intelligence information directly in the decision-making process or to produce other intelligence
Business CRM Functions Comparable Intelligence CRM Functions 1. Track customer catalog browsing to understand
interests and trends
1. Track consumer intelligence portal browsing to understand interests and trends
2. Track and record customer transaction history:
inquiries, shopping (browsing offerings), purchases, returns, satisfaction survey responses
2. Track and record consumer transactions:
inquiries for reports, searches for online data, requests for intelligence tasking (e.g. topics or urgencies), uses of intelligence (e.g., decisions made based on intelligence, benefits of intelligence, or feedback)
3. Analyze individual customer buying patterns 3. Analyze individual consumer intelligence request patterns
4. Personalize sales promotions to customer interests (targeted marketing); suggest products based on prior purchase patterns
4. Personalize news, reports, and alerts to consumer interests; anticipate and deliver new products based on previous interests and current trends
5. Provide common access to customer profile to marketing, sales reps, delivery, and customer service to present coordinated delivery of service
5. Provide common access to consumer profile to tasking, analysis, and production to deliver coordinated intelligence to consumers from all elements of the enterprise that interface with the consumer
6. Analyze entire customer base: identify customer groups, purchasing trends, and behaviors to manage sales campaigns; introduce new products and reach new markets
6. Analyze entire consumer base to identify interest trends, concerns, and issues: identify consumer groups with common interests; develop products and services tailored to groups; identify individual consumers with near identical interests and offer collaborative analysis and products
• Cash-to-cash cycle time (time from order placement to delivery/
payment);
• Delivery performance (percentage of orders fulfilled on or before request date);
• Initial fill rate (percentage of orders shipped in supplier’s first ship- ment);
• Initial order lead time (supplier response time to fulfill order);
• On-time receipt performance (percentage of supplier orders received on time).
Like the commercial manufacturer, the intelligence enterprise operates a supply chain that “manufactures” all-source intelligence products from raw sources of intelligence data and relies on single-source suppliers (i.e., imagery, signals, or human reports). The analogies between business and intelligence SCM are apparent (Table 3.13) and the principles of automation, monitoring, and adaptive control can benefit the high-volume intelligence supply chain in terms of efficiency, product timeliness, and customer satisfaction.
Note that the supply chain in Figure 3.11 distinguishes the tasking, collec- tion, processing, exploitation, and dissemination (TCPED) stages associated with the high-volume national intelligence supply chain. (The TCPED intelli- gence model is compared to other models in Section 6.2.)
3.7.3 Business Intelligence
The BI function, introduced in Chapter 1, provides all levels of the organization with relevant information on internal operations and the external business envi- ronment (via marketing) to be exploited (analyzed and applied) to gain a com- petitive advantage. The BI function serves to provide strategic insight into overall enterprise operations based on ready access to operating data. The objective of BI is to enhance business decision making by providing accurate and timely infor- mation to decision makers. In many complex businesses, this has not been the case; near-real-time quantitative data and models of operations have been absent and management decisions have been base on intuition and scant measured data.
Similarly, in large intelligence organizations, it has been difficult to quantify overall operating performance due to the lack of dedicated operations metrics capture, storage, and analysis. Wal-Mart has become a commercial legend in BI implementation by warehousing all point of sales, inventory, and supplier data to analyze customer trends and adapt the entire retail supply chain to a high level of response and efficiency. As shown in Figure 3.11, BI is integrated to both CRM and SCM functions in measuring and providing intelligence to management to adopt the strategic operating policies and tactical CRM and SCM operations.
The emphasis of BI is on explicit data capture, storage, and analysis; through the 1990s, BI was the predominant driver for the implementation of corporate data warehouses, and the development of online analytic processing (OLAP) tools.
(BI preceded KM concepts, and the subsequent introduction of broader KM concepts added the complementary need for capture and analysis of tacit and explicit knowledge throughout the enterprise [34].)
BI implementations within an intelligence organization provide “intel- ligence about intelligence”—insight into the operation flow through the
Table 3.13
Business and Intelligence SCM Analogies
Business SCM Intelligence SCM
The Supply Chain:
Suppliers: upstream producers of raw materials (tier 2) and components (tier 1)
Supply chain—order, plan, procure, produce, ship (delivery, order fulfillment)
The Supply Chain:
Suppliers: intelligence collectors and single- source processing and analysis
Supply chain—plan, task collect, acquire data, analyze all-source data, produce intelligence products, and disseminate
External customers External intelligence consumers
Business SCM Functions Comparable Intelligence SCM Functions 1. Supplier integration—provide electronic
interactions with at least tier 1 suppliers, sharing demand models and supplier capacity and projected deliver data
1. Collection and silo integration—integrate collection planning, tasking to respond to current and projected demands; coordinate multiple-INT collections of data
2. Inventory and warehouse management—
automated monitoring and management of individual inventory items and movement through warehouse to transport
2. Intelligence holdings management—data warehouse management to monitor use of holdings, and current/projected demands to assure key data availability
3. Process planning and scheduling—monitor supply and demand in real-time; project demand and schedule supply processes based on current data and statistical models; eliminate inventory stock outs
3. Intelligence production planning and scheduling—measure current requests, tasking, processing, and analysis workflow to allocate resources to optimize to priority, timeliness, and depth metrics; eliminateno response to consumer requests
4. Delivery and order fulfillment—plan order sequencing to consolidate orders to combine deliveries and deliver on time.
4. Digital production—provide electronic delivery of products withemerging results as well as final point-in-time delivery
5. Extended customer integration—share supply chain data with consumers: status of current orders in the supply chain and tracking past history of performance
5. Extended consumer integration—share supply chain data with consumer, reporting time to delivery for each request.
intelligence cycle. The intelligence BI function should collect and analyze real- time workflow data to provide answers to questions such as:
• What are the relative volumes of requests (for intelligence) by type?
• What is the “cost” of each category of intelligence product?
• What are the relative transaction costs of each stage in the supply chain?
• What are the trends in usage (by consumers) of all forms of intelligence over the past 12 months? Over the past 6 months? Over the past week?
• Which single sources of incoming intelligence (e.g., SIGINT, IMINT, and MASINT) have greatest utility in all-source products, by product category?
Like their commercial counterparts, the intelligence BI function should not only track the operational flows, they should also track the history of opera- tional decisions—and their effects. Both operational and decision-making data should be able to be conveniently navigated and analyzed to provide timely operational insight to senior leadership who often ask the question, “What is the cost of a pound of intelligence?”