Overcoming Data Obstacles for Integrated BI
How you can avoid three barriers to taking an integrated BI approach to providing a multifaceted view of enterprise data.
By Donald Farmer, VP of Innovation and Design for Qlik
The partnership between IT and business users has changed significantly in recent years as consumer technology has advanced and services move to the cloud. More demanding (and involved) users now expect support teams to ensure enterprise technology keeps pace with consumer-grade devices, apps, and features.
To meet the needs of such tech-savvy users, organizations expect a new, multifaceted view of their data that is accessible and easy to consume. Both business and IT want that "light bulb moment" when at last they grasp all the pieces of the information puzzle and how it can transform their work.
Data's Double Vision
Companies may invest in the best technology and solid data, but many wallow in the data without a clear purpose. The new mandate does not stop when (or if) your company achieves a 360-degree view of its work and data. The connected enterprise needs a deeper, detailed view and a business intelligence (BI) strategy rooted in data discovery and visualization.
Today, users must often switch between a high-level view of data and detailed, focused scrutiny. For example, a manufacturing company sourcing parts and materials worldwide requires a global overview. However, facing problems such as bad weather and shipping delays and the need to react efficiently, supply-chain analysts must drill down to very specific issues while keeping that 360-degreee view in mind.
Such a complex, emerging demand can only be met with an integrated BI approach, but three barriers block the way of the forward-looking IT team:
-- Disparate data both in where it sits and its language. System architects must bring together data from different systems, applications, and departments. Deep data integration while eliminating silos calls for a broad and targeted platform: We have worked with Scribe Software to clear this barrier for many customers.
Nevertheless, users understand data differently than IT does. Users think in terms of operational meaning rather than the technical specifics. Having integrated disparate data you must present it for users in their terms.
-- Static dashboards and broken predictive analytics tools. Businesses can no longer rely on cookie-cutter reports and documents. The competitive landscape changes too rapidly and modeling technology cannot predict all possible scenarios, issues, or uses.
Even if you could answer all your pre-defined questions, today's teams must still react to unplanned, or even unprecedented, events. Who could have predicted a volcanic eruption halting much of the world's air travel for weeks? New technology or new laws can also change the game overnight. Tools that enable users to explore new scenarios with good data in turn deliver new answers and continuing success.
-- Reliance on simple reports rather than storytelling. A typical IT team generates a great number of reports, but to what end? Do users really read and understand them?
Perhaps surprisingly, businesses run on stories rather than reports. Reports only give a snapshot of a predefined scenario: they rarely provide the rich context needed to make sound choices.
For example, too many of those weather-delayed shipments in December could mean our manufacturer misses an annual target. A simple static report may show the miss but not the reason, and it's unlikely to show that manufacturing will return to normal within the first few days or weeks of the next quarter. In the past, developers would simply create another report listing delays, and perhaps yet another highlighting lagging indicators, but who needs or wants more reports to read?
Although the static views of this problem are at best worrying and at worst unhelpful, the story of this weather event is not so discouraging. When managers tell the full story, reasons and context and outcomes can be better described. Decisions are more relevant and sound.
To break through today's barriers requires organizational and strategic change. IT teams must take on a new role. They can no longer be data gatekeepers but need to act more like data storekeepers. They can no longer control and micromanage all our corporate data or its uses. Instead, they should make available good quality, appropriate, and timely sources and feeds for business to use when and how they need it.
For their part, users can become more active participants in the data dialogue. Explaining requirements to IT takes too long and the standard life cycle of design, deployment, and feedback is cumbersome and slow. Business users can no longer afford to act as passive consumers; they must be integral to the information supply chain by becoming resourceful contributors, bringing their own insight and intelligence to bear.
Forward-thinking teams have changed their view of enterprise information. They push past the barriers that hindered outmoded BI and reporting practices. They know technology and data infrastructure is but one small piece in a bigger puzzle. The pieces that matter to the bottom line fall in place only when users make new and effective decisions with these resources.
Donald Farmer is internationally recognized speaker and writer, with 30 years in data management and analysis. Before joining Qlik, Donald was a leader in the Microsoft Business Intelligence team, working on new products for ETL, predictive analytics and OLAP. An author of books and many articles, he has applied his knowledge in fields as diverse as archaeology and fish-farming. You can contact the author at firstname.lastname@example.org.