Using Business Intelligence Solutions to Hone Strategies

According to technology research company Gartner, analytics and business intelligence (BI) solutions are now #1 on CIOs’ technology priorities agenda. Why? All kinds of companies, including multichannel merchants, are recognizing that they must harness the siloed data residing in transactional systems in order to tie their operational realities to short-term plans and long-term strategic goals. They must be able to readily analyze data in meaningful ways, and be able to act quickly to address problems and jump on new opportunities.

Most companies’ transactional systems employ different data definitions/terminology and reporting timeframes. Levels of data accuracy also vary. As a result, there’s no “one version of the truth.” Various managers rely on reports/data based on their own systems. Instead of collaboratively focusing on strategy, they’re focused on pinning down the true status and results of operations and initiatives. Collecting and updating data can absorb 80% of the time, leaving just 20% to analyze it.

BI solutions can cut through this morass by providing managers with ready access to integrated, enterprise-wide data and analysis capabilities, as well as action alerts.

Among the many potential benefits: Honing inventory and reducing costly back orders; a better understanding of the costs of core (never-out) products within broad SKU assortments; and a better understanding of merchandising and marketing results by catalog and digital channels.

BI’s true purposes/value
BI solutions don’t eliminate transactional systems and spreadsheets. They integrate all that siloed data—contact center, fulfillment, ecommerce, web analytics, marketing, merchandising, finance, etc.—through data-mapping between those systems and the BI database. Data updates can take place in near real time, or overnight.

Once integrated, the data can be tied to existing metrics and key performance indicators (KPIs), as well as to business-transforming analytical capabilities.

BI isn’t about creating “more” data or metrics, per se. (“More” data, at least if it’s unfathomable, is the last thing most companies need.) While BI should enable companies to tap into valuable new media data sources as business needs evolve, its core value lies in integrating existing sources to enable accurate performance monitoring, useful analysis, new insights and collaborative strategic planning.

Under security controls, BI should achieve these goals while largely eliminating internal data “ownership” issues.

Core strategic goals
Here’s a summary of the core objectives of BI solutions:

· Integrate siloed transactional data and reporting into an enterprise-wide strategic resource.
· Implement a framework for data and KPIs that aligns to your enterprise’s strategic goals and day-to-day departmental activities.
· Develop dynamic analyses that support strategic plan development.
· Use KPIs as triggers that highlight department performance as it aligns to short-term plans and long-term strategies, and alert managers that actions are needed.
· Provide insights to customer-facing functions and vendor and partner activities.

Guiding principles
To achieve these broad objectives, keep these guiding principles in mind. Your BI solution should:

*Achieve a “single version of the truth.” In many cases, transactional systems were developed without exacting standards for defining and naming data elements. Systems/spreadsheet data have been inadvertently misclassified. For example, in a fulfillment system alone there may be as many as 400 to 500 files and tables with thousands of data elements.

To achieve BI goals, the data-mapping between BI and transactional systems must employ stringent, nonvariable data definitions. In particular, data must be accurately classified as to whether it includes merchandise only, or also shipping/handling charges and other services.

Here is an example of defining data and how its use changes the intended results:

Sales: value of orders/items shipped
Gross sales: value before returns are netted
Net sales: value after returns and exchanges
Order demand: value of customer orders before cancellations

Once properly classified, all data should be further defined by “time slice” (daily, weekly, season) and/or by specific promotion—and by quantity/units sold.

*Create flexible analytical solutions. The solution should be capable of dynamic, ad hoc analysis. It should generate data in formats that reveal previously undiscovered relationships, insights or areas to research that may indicate opportunities to hone or expand your business.

*Become user-friendly and intuitive. Useful insights are far more apt to be gleaned from meaningfully presented data than from reams of tabular data. (Gartner reports that ease of use has surpassed functionality as the #1 criterion in purchasing BI software.)

Effective BI solutions provide dashboards and other graphical user interfaces (GUIs) to show relationships and assist in analysis. But, a word of caution: Don’t develop the dashboard concept first. Decide what results, KPIs and business rules are important, and use those to guide dashboard development.

*Enable ready “drill downs.” Users should be able to click on summarized data or a dashboard and see relevant, usefully formatted detail data. One example: a pop-up pie chart summarizing products/SKUs by category, by age (0-30 days, 61-90 days, etc.).

*“Push” alerts to managers. Again, BI solutions should be tied to key plan metrics/KPIs and be able to alert managers to potential problem/opportunity areas. Examples include marked-down product sales not meeting a liquidation plan, or products showing sales volume that exceeds the vendor’s lead time to replenish.

*Enable flexible, open-ended development/analysis evolution.The solutionshould be adaptable to changing data/analytical needs as your business evolves, including adding new data sources to the BI database. These might include ecommerce analytics; marketing service bureaus; systems for call management, order management, inventory, forecasting, budgeting and finance; and myriad spreadsheet data.

The solution should enable relative ease of integration of new sources by IT, so that users get access to these sources’ data presentation, analysis and action-alert capabilities as quickly as possible.

*Maximize “self serve” capabilities. The BI solution should strive to maximize users’ ability to employ analytics and generate reports on their own, and minimize the need for IT intervention on a day-to-day basis. (Effective BI solutions should not create IT bottlenecks; in fact, they should free up IT time.)

Achieving the self-serve objective can be challenging (some systems have a way to go in this regard), but it’s critically important to ensuring high usage of the system, which is the key to the overall success/ROI of a BI investment.

BI software vendors/solutions
Gartner’s Magic Quadrant for Business Intelligence Platforms Report is an excellent starting point for assessing BI solutions. It lays out key software selection criteria and provides a competitive analysis of major providers. The latest report can be downloaded from the site of BI software provider Microstrategy.

The many consultants, web solution providers and software companies targeting the multichannel marketplace include Cognos, SAS, Microsoft SRRS, Merkle’s Lenser division, NetSuite, SAP, Oracle and Taurus Software. In addition, order-management systems providers Junction Solutions and HSO (both Microsoft Dynamics divisions), SAP, Natural Solutions, Jagged Peak, Micros-Retail (CommercialWare) and Red Prairie (Ecometry) all have BI software options that work with their systems.

Solution providers often start with one siloed activity (such as inventory or marketing), and then build on those applications to add analysis across the enterprise. The challenge is to ensure that the solution chosen will truly open up access/analysis to all relevant users.

Some multichannel businesses have embarked on in-house development of BI solutions. While this may be the best option for some, my observation is that, in general, merchants that go that route experience higher investment costs, elongated development and delayed realization of benefits.

For companies with $50 million or less in sales, selecting BI solutions that have pre-built application templates, data models, executive analytics, dashboards, mobile device connectivity, etc. is critical. These provide a quick start in applying BI, and platforms that can accommodate applications expansion.

For most companies, BI solutions yield the highest ROIs in marketing, merchandising and inventory management by revealing new data relationships that can be applied in growth and profit strategies.

Here are some top-line issues to consider:

· What analytics will be needed as your company evolves in ecommerce and other channels?

· What is the quantifiable value of knowing immediately which customers are responding to which ecommerce promotions, and what products they’re buying?

· How do various ecommerce channels (your site, Amazon, email blasts, affiliates, etc.) build your business?

· Do you have the tools to measure customer loyalty, repeat buyers and lifetime value?

· How might BI give your merchants a competitive edge over the competition?

· What cash invested in inventory would be freed up by reducing inventory turnover? How would operational costs be decreased with reduction in back orders and a higher fill rate? What savings could be achieved in overstocks?

Generally, the payback, or ROI, for a BI solution offering focused development or pre-built analytics and data models should range from about eight to 12 months.

Curt Barry ( is president of F. Curtis Barry & Co., a multichannel operations and fulfillment consulting firm.

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