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2 Posts authored by: carth13 Employee

After my recent blog on performance dashboards, I want to follow up by clarifying some IT terminology prevalent in the modern software factory: business intelligence (BI) and business analytics (BA). While superficially similar, there’s a very important distinction between the terms:

  • BI uses past and current data to generate insights to improve near-term success for the organization
  • BA analyzes the same data with a different goal: to help the organization make well-informed assumptions, uncover or anticipate trends, and prepare the organization for the future

 

We immediately see a distinct difference in these definitions: BI provides insights to optimize the organization for near-term success, while BA is used to prepare the organization to adapt to a foreseeable future landscape. Optimizing a business versus adapting a business is a huge distinction: A blacksmith in 1910 would use BI to understand that he needs fewer horseshoes in inventory, but BA would be more likely to tell him he needs to get into the tire business.

 

That’s not to say that BI is less important than BA; past and current data are always crucial in creating and maintaining efficiencies as well as identifying and resolving operational and strategic issues in order to optimize the business in the present. Despite the need to anticipate the future as accurately as possible and position our organization to thrive in a changing world, we’ll always need to understand our present state to increase productivity and limit costs—the perennial, all-important fundamentals.

 

While BI will always be useful, the modern economy is defined by change, and as we all know, change in IT leads to more change in IT—causing the pace of change to accelerate. For that reason, analysis of big data is very valuable in understanding where organizations (and society at large) are headed. Because consumer choice is a dominating force that compels technological change, collecting consumer data allows analysts to use data mining, quantitative analysis and predictive modeling—all elements of BA—to adapt a business to align with consumer trends.

 

Keep in mind that BA is different from data science. Most would agree that data scientists do not try to answer specific questions; rather, they examine data and allow the data features (aka the data itself) to guide the analysis.

 

BI—knowing how many horseshoes to keep in inventory—has always had a place in the business community. BA—learning that tires are the future of transportation—has become a more and more important tool. Organizations are investing more resources in data warehousing and huge data stores, cleaning up and maintaining data integrity, and new and sophisticated analysis techniques. As they do, organizations will look to CA and other state-of-the-art technology companies for the best tools and the best practices.

 

I'm a Sr. Services Consultant with CA Services; I look forward to using my experience to respond to your comments and questions.Please post them below—I value your feedback. 

When using media for connecting and sharing information in short, efficient increments, families and friends turn to Facebook, Snapchat, and Instagram, career professionals use LinkedIn, and others turn to Twitter.

 

When monitoring a business, think of dashboards as social media for IT: a platform to socialize information, provide context, move people to action and build ties through data with people who share common interests and goals.

Just as with other social media, there are good practices, rules, and considerations for getting value from IT dashboards—and costly pitfalls of “bad dashboarding.”

The dashboard creator needs to consider:

  • Who is my audience?
  • What information needs to be presented?
  • What is the frequency for refreshing data? What is the frequency for viewers to consume data?
  • How can data be organized to provide helpful context and avoid misinterpretation, or worse, misuse?
  • What actions might we expect viewers to take based on the information?

 

At a minimum, your dashboard strategy for CA Performance Management (CA PM) should address two key dimensions: the intended audience and the desired benefits of viewing the information.

 

Just as it is good practice that tweets are segregated from professional LinkedIn group postings, Snapchat conversations, Facebook pages and Tweets, it is good practice to segregate dashboards by audience and desired benefits. The key point is to tailor dashboards to specific audiences: A dashboard should not morph into a forum for all relevant data for disparate audiences. Potential benefits of dashboards include:

  • Driving continuous improvement of applications, networks or business services
  • Increasing data transparency across IT teams and business stakeholders
  • Improving alignment throughout the business and promoting better business decisions using valid data

 

The benefits of a strong dashboard strategy are slightly different. These include:

  • Frequent (or timely) use of dashboard data
  • Confidence in shared data
  • A healthy ratio between time spent consuming data and time needed to derive insights from the data and develop a plan of action
  • More efficient cross-team communication

 

Let’s look at each type of dashboard.

 

Operational dashboards

These dashboards monitor services that change frequently and track performance of key metrics and KPIs. Data updates very frequently, normally every five minutes. Viewed throughout the day, they often monitor progress toward a known goal or against a specific benchmark. Many enterprises prominently display operational dashboards for all to consume—looking for insights to change behavior and drive incremental, continuous improvements.

Dashboard creators should have a solid understanding of the data’s context. For CA PM, the design may be applicable to multiple sets of CA Performance Center groups for quick, easy changes to the data group represented geographically or by business unit, data center, or other relevant data segmentation required by technical data consumers.

Some metrics that CA PM customers include in operational dashboards are:

  • Amount of traffic through key network links
  • Resource usage (CPU, memory, etc.)
  • Website activity

Strategic dashboards

These dashboards monitor KPI status. Data is updated less frequently than on operational dashboards. Most strategic dashboards are viewed a few times per day by executives. The key is understanding how the current state of KPIs impacts the business.

The dashboard creator needs to understand what the business day looks like: Does it follow the sun or do we need to establish business-hour reporting using site groups in CA Performance Center?

Some metrics that CA PM customers include in strategic dashboards are:

  • End-user experience
  • Application usage rates
  • Availability of key resources

Analytic dashboards

These dashboards analyze large volumes of data to investigate trends and discover business insights to ensure that the trends fit business goals. In CA PM, analysts use scorecards and metric projections to predict outcomes. These dashboards can be updated less frequently as long as the data is accurate and current when viewed.

Some metrics that CA PM customers include in analytical dashboards are:

  • Top-viewed web pages
  • Percentage of visitors on mobile devices
  • Average time spent at the website

Parting Words of Advice

Dashboard formatting and graphic design are important, but dashboard design starts with knowledge of the audience and the type of dashboard the audience requires to align IT goals with larger business goals. From there, you can make intelligent decisions about important data, where that data resides, and how to best represent the data.

Well-designed, frequently viewed dashboards can be an effective business tool. By monitoring your current state, you can make incremental changes to your business that over time, deliver substantial results and ongoing learning.

So don’t fall into the “set it and forget it” trap with dashboards. Take a more agile approach to using dashboards that can meet new challenges as the business evolves:

  1. Plan to adapt each dashboard over time: Start small and build on successes.
  2. Monitor usage by group or individual and by dashboard element, and map actions taken to insights derived from specific data.
  3. Focus on top-most priorities; question the value of secondary priorities until teams are confident that the highest priorities are being successfully attained.

Comments or questions? Please post them below—I value your feedback.