Lanark Systems LLC provides mission-critical analysis of the major business areas in your organization: customers, products and services, finance, supply chain and human resources.  We use advanced predictive and descriptive analytics (data mining) to help your organization uncover trends and business drivers (customer churn, product profitability, supply chain effectiveness) transforming your operational data into actionable information.

Data mining involves the use of computer technology to help business users exploit data.  The tools sift through large quantities of data looking for insights, which can be turned into action delivering value to the business.  Data mining techniques typically used include clustering, neural networks, data visualization, statistical analysis, rule induction and genetic algorithms.

We have expertise using the latest business intelligence and data mining tools and techniques, and considerable data analysis and modeling experience.

Our analytics methodology supports:

• Proof of Concept studies, useful for demonstrating capability and potential benefits
• Longer scoping studies useful for building a business case for further investment or building analytical capability within firm.
• Delivery of customer insight to the point of customer interaction

Customer Insight

Your operational systems generate a wealth of information on customer behavior and preferences.  Customer Insight is the art of analyzing this interaction data and the overall customer relationship in order to optimize customer lifetime value. 

Customer Insight involves the integration of large volumes of data from multiple sources (touchpoints) to create a single view of the customer.  Initial analysis may include creation of an economic model of customer value.  Customer value is used to drive more effective communication and management of these customers.  Data gathered over time is used to develop the means to predict customer behavior and ultimately manage interactions with customers.

Our approach to customer analytics has proved successful for many businesses, especially in the area of customer segmentation and profiling for direct marketing, cross selling, risk management and customer acquisition, retention and growth. Other analytics include fraud detection and store location planning.

Customer segments can be defined by behavior, demographics, (firmographics for organizations) and customer value. Metrics include lifetime value (LTV), recency and frequency of purchases, and monetary value scores (RFM).  At the segment level, customer analytics can reveal changes in your firm’s competitive environment. It also reveals the behavioral of the relatively small percentage of customers who generate the most revenue and the most profit.

Analytics Outsourcing

Analytics Outsourcing puts sophisticated analytics within the reach of most enterprises.  Advantages of outsourcing include time and resource saving by delivering results that don’t require software and hardware procurement and maintenance, and results that are immediately usable – no ramp-up time for internal staff to learn the technologies.  We provide experts to develop your models and a hosted environment to use them.

Model Management

Predictive models have a finite lifespan. In order to maintain the accuracy of your predictive models, Lanark Systems LLC offers a subscription based service to periodically revalidate and tune your models. This model management can be performed at your site or on an outsourced basis.

Data Management and Data Hosting

Hosting decreases your investment in staff, hardware, software and infrastructure while increasing productivity and customer service.

Contact us to create a services retainer and/or hosting relationship with service levels configured to your needs.

BI Tool Assessment

Business Intelligence tools have among the highest ‘shelfware’ rates of any purchased software.  Our BI Tool Assessment services help you select the right tools to meet your needs. We assist you with:

• Needs Assessment: Includes interviews with end users to determine intended uses and skill levels.  We work with your IT staff to analyze the relevant data sources to ensure the required data is available to meet your business requirements and to uncover architectural or tool specific issues.  We also review your current architecture to determine appropriate hardware requirements and software compatibility.
• RFI/P Development: Findings from the Needs Analysis phase are outlined to provide a common roadmap and description of your requirements. We help you prepare an RFI communicating this information to the vendor candidates.
• Tool Selection: We continue working with you through vendor product demonstrations and help determine appropriate product configurations.  We have the capability to test competing vendor’s tools with samples of your data to provide a truly hands-on tool evaluation.

Analytical Tool Assessment

Analytical tools vary widely in capability and cost.  We work with you to select the right tools to analyze your data and generate the results you need to be competitive.  We have expertise in tool selection across the major components of Data and Analytics architecture including:

• Data Quality
• OLAP
• Data Mining
• Visualization
• Data Delivery

Data Asset Management

Your company’s data is one of its most valuable assets.  The first step toward unlocking data value is to assess the overall quality and suitability of the data for analysis.

Data Quality Assessment

Good analysis depends on good data quality. Lanark Systems LLC can assess your customer, supplier, product and other data to determine issues which could impact analytical success.

A “Single View of Customer” is the key to effective customer relationship management (CRM). Many organizations have been unable to create a unified view of their customers.  Low data quality is typically the root cause.  Inconsistent customer identification and description data is common in many organizations and is the major stumbling block to achieving a Single View of Customer.

Data Asset Analysis

We assess your data sources to determine the suitability of the data for analysis.  This includes: determining where the data comes from, what is in the data and identifying any issues that might impact analysis.