Help IT Understand The Business Impact Of Back End Work To Drive Business Value


wile_businesscardA Business Impact Example from the World of Business Intelligence

Whether you’re a DBA Wizard or a business user who relies on some mysterious back end where the heavy lifting of computing gets done you are swimming in data.  But all too often the data wranglers we rely upon to keep systems performing under peak loads and at peak capacity are left in the dark as to why the systems they manage do what they do.

The result is that updates, upgrades and capacity expansions become their own justifications.  Context is lost.  Eventually an executive asks the simplistic question; why are we spending so much to update these systems? The results are predictable; answers are devoid of business impact and budget cuts and even layoffs are the result.  Unfortunately, this is an all too common a scenario and it does not have to be this way.

There is a wealth of value and insight trapped inside the data that is being processed and stored every second.  The challenge for those who manage the data systems is to both understand the business impact of that data and make it readily available.

To some extent Business Intelligence systems and fancy reporting dashboards have helped expose the value hidden in large amounts of work-a-day data.  These can display efficiencies, machine and network monitoring statistics and regional sales activities at a glance.  But even those findings are still missing the core point about exposing the value inherent in the data.

It is vital that data practitioners understand how to explain why the dashboard data is important.  For instance, operational efficiency charts show through-put from physical processes and business workflows.  Spotting clogs in the process is as valuable as having real-time traffic maps when you decide your daily commute route.  It lets you advise the decision makers on how best to rout your products, services or information so that it gets to its destination on time.  While a traffic jam may be a perfectly reasonable explanation for why you are late to an appointment, it is always better if you can get there on time by taking an alternate route.  This is the business impact that operational efficiency reporting delivers.

Machine and network monitoring have similar values.  These display much data from load to processor heat to the health of network pathways that our critical business systems rely upon.  But the biggest business value is not in simply being able to see when a node is down and then reacting to it.  Rather the value is in spotting trends that suggest something new is happening.  The ability to predict load and health and then respond appropriately is the entire premise behind the cloud and elastic buzzwords so prevalent in technology today.  But why is elasticity so important?  Why should we take for granted that it is a good worth thousands of dollars a year?  Elasticity of compute systems allow organizations to consume (and therefore pay) for only what the system needs at the time.  Rather than staying reactive and buying more bandwidth or new nodes after a spike occurs, machine and network monitoring data combine over time to illustrate trends that are graphed and displayed.  Automated elastic compute triggers are configured to free up or obtain necessary compute and network resources ahead of a demand spike.  The end result and the impact is that there are no dropped transactions (whether buying/selling transactions in the case of e-commerce or internal processing transactions in the case of back office/back end operations).  No dropped transactions means no lost business (aka revenue) and no drops in efficiency (which impacts on the business operations intelligence you read about earlier).

Most BI systems also have a roll up dashboard view of sales activities. At first glance these will illustrate the performance of different sales regions.  Managers and executives can get an idea of how revenue is flowing against the backdrop of quarterly expectations.  Sales managers can see geographic regions where demand is strong or weak and then use that insight to redeploy account managers to areas where they’ll be most effective. This data relies upon integrated and normalized schemas between a host of systems that back end data wizards manage.  From CRM to Help Desk to HCM and IDM, they’re all integrated in order to display the easily digestible heat maps and speed dials that are popular on reporting dashboards.  But in order for those systems to first be integrated, the network health and compute capacity must first be available.  Business transactions and operational efficiency must be operating correctly.  Otherwise the sales reporting might be incorrect, incomplete or showing old information.  That would be a disaster for intelligent decision making.  The impact of a sales BI dashboard is most easily observed.  The relationship between the deployment of sales assets and business revenue is one of the most direct.  Better sales means more revenue.

When IT data wizards understand how their back end world helps drive better sales, better business operations and better health of business technology systems, they can feel a better sense of ownership in the workings of the entire organization rather than just the databases, warehouses and portal systems they manage.

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