Analytics Success Should Be Measured by Business Users

Published
  • May 06 2016, 6:30am EDT

Organizations are creating an enormous amount of data, from a growing number of sources. The task of managing it all falls on IT, but determining success with any analytics project starts with business users.

Information Management spoke with Shikhar Agarwal, founding engineer at ThoughtSpot, for his observations on what attendees at the recent Strata & Hadoop World conference in San Jose, CA, are trying to do with their business intelligence and analytics efforts, and the questions they should be asking themselves to determine if they’re on the right track.

 

Information Management: What are the most common themes that you heard from conference attendees and how do those themes align with what you expected?

Shikhar Agarwal: With more data comes more responsibility. As companies are increasingly equipped to generate and store massive sets of data, IT must now take on the nearly impossible task of managing, provisioning, governing, preparing, and analyzing growing data volumes with increasingly nuanced expectations from line of business users. We keep hearing, at Strata and other conferences, that as business intelligence and analytics expand beyond the purview of traditional IT roles, tech investments are be tied to and measured by their business impact. Some questions that organizations should ask:

Are line-of-business users able to uncover insights on their own and make decisions quickly?

Is the information accurate and timely?

Do they improve campaigns, programs, products and policies, thus driving the business’s bottom line in a positive way?

There’s a dirty secret in the world of BI: most BI or analytics projects are plateauing at a dismal 25% adoption rate. That’s hardly enough to have meaningful impact cross-functionally.

Everyone -- from line of business users who need access to insights; to the data science teams who, strapped for time and resources , need to focus on more strategic data initiatives -- are clamoring for technology that puts analytics and insights into the right hands, at the right time.

 

IM: What are the most common challenges that attendees are facing with regard to data management and data analytics?

SA: Data prep came up a lot. Many new BI products that have launched over the past few years fulfill one or more of the self-service data prep steps: data discovery and profiling; catalog and metadata; data structuring and modeling; data transformation; data curation; enrichment and collaboration. Despite this, many BI professionals who operate in complex data environments still spend up to 90% of their time preparing data for analysis. As data volumes balloon, companies know they have to adopt new technologies that automate a good deal of this legwork. The alternative -- to continue to lock precious data science resources into routine data preparation -- simply isn’t feasible.

Whether it’s preparing traditional, structured data in an attempt to monetize said data or rolling out a big data initiative, businesses of all shapes and sizes are evaluating technologies that reduces the time and complexity needed to bring analytics to life in their business. This has the potential to give users access to their enterprise’s data, wherever it may live. It’s the first step to true fulfilling the self-service analytics revolution the BI industry has been promising for years.

 

IM: What are the most surprising things that you heard from attendees regarding their data management initiatives?

SA: At this point, every business knows it needs to become a data driven organization, so it was surprising to see just how many organizations still rely on analytics tools that require massive time and labor investments to return even the most basic queries. Businesses no longer operate at the pace they did even 10 years ago. The industry is moving in the right direction, but it will be interesting to see who makes the jump to the future, and who remains locked up with legacy tools.

 

IM: What does your company view as the top data issues or challenges in 2016?

SA: Finding and recruiting high-quality data scientists will continue to be a problem; and not a problem we can continue to lament.

Data needs to be the lifeblood of a company, rather than an IT-managed resource. Making that transition might be painful and expensive, but it’s necessary if a business wants to survive in the future. It’s going to take a new approach to data technologies, as well as a culture shift.

Finding the best ways to provide governed data discovery while guard-railing secure access will allow a lot of companies to break free of the current data bottleneck headaches. In order to realize the full potential of a data driven model, however, businesses must engender a data curious culture, where employees across functions, and not just IT, feel confident and empowered to explore their own data, finding their own insights, and making their own decisions accordingly. This is critical for businesses as they increasingly seek to monetize data assets.

 

IM: How do these themes and challenges relate to our company’s market strategy this year?

SA: Going forward, data analytics needs to integrate more seamlessly into existing workflows to encourage adoption. That’s the only way users will see the power, and value, of their data.

Here at ThoughtSpot, we’re on a mission to give users of all stars and stripes the tools they need to not only consume data insights, but to create them whenever and wherever they need them, without disrupting their workflow with a call to IT or a data scientist. We’re always evaluating, testing and building new product features that will make data more intuitive and more accessible to all users than ever before. Data must be actionable for all, especially if it’s to be monetized or incorporated into decision making. We believe a self-service solution like ours, that truly meets users where they live, can make this a reality.

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