Business Intelligence

Business Intelligence

Artificial intelligence (A.I.) is often characterized as being highly-theoretical and the appropriate domain of academic researchers and graduate studies. Until recently these characterizations were not completely inaccurate. In the last few years a new generation of artificial intelligence technologies have emerged — coupled with significant increases in computer power — that have made A.I. a viable tool in such applications as cash flow, distribution requirements, manpower forecasting, and inventory control. Practical applications of A.I. are often referred to as “Business Intelligence”. These technologies are no longer expensive, large-scale implementations within the reach of only large corporations or universities. They are now practical, proven tools for increasing the capabilities and decreasing development cost of business applications.

THNK began implementing business intelligence technologies for our clients with our first decision support system — an expert systems based loan approval Web application — in 2001. Since that time we have continued to expand our expertise in applying advanced computing techniques to application development as the technologies became feasible investments for our customers. We now employ a wide range of techniques from the fields of machine learning, operations research, and decision support systems.


  • Business intelligence techniques can extend the capabilities of traditional software such as accounting and manufacturing systems making existing systems ‘smarter’.
  • Appropriate applications of the technology improve the functionality and speed of software.
  • Existing data can be used to discover ways to improve your business. Years of sales orders may contain important information about your customers buying habits that can be used to improve sales. A database of work orders may contain information about optimal allocations of resource that can be used to speed production process or improve quality control. B.I. approaches allow you to harness the untapped potential of your data.
  • Business intelligence applications can be used to improve the productivity of your knowledge workers by encapsulating expertise and automating decision processes. This frees your experts to focus on improving your operations.

  • Example Solutions

    Sales Forecasting

    Analysis of customer buying patterns both for prediction of future sales totals as well as for predicting the future purchases of specific customer for proactive sales initiatives (Regression Analysis).


    Adding modules to existing ERP software that minimizes inventory costs by effectively allocating inventory (Inventory Scoring, Cutting Stock Solutions).

    Sales Force Scheduling

    Extending CRM (Customer Relationship Management Systems) with scheduling extensions to maximize the effectiveness of sales staff (TSP Solutions).

    Comments are closed.