Year after year the hype surrounding data analytics becomes louder. Thought leaders and research organizations have sung the praises of analytics as a means for generating much-needed insight into business operations, and companies that have embraced analytics have been able to translate insight to better operational productivity and faster, more accurate decision-making. In a competitive business environment where your competition is just as hungry as you are to reach and secure new customers and where business leaders need to make accurate, fact-based decisions about the company’s future, analytics can be the game-changer that makes the difference between success and failure. Here’s how:
The beauty of analytics is that it can serve as a guideline for transforming sub-par business performance to one that is efficient and profitable. Whereas reports provide a historical view of what transpired, analytic output is forward-looking, and plays an integral role in helping executives plan for the future.
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We’ve been thinking a lot about the various ways organizations can improve their existing business intelligence applications. Many of arcplan’s customers have been with us 5-10 or more years and are continuously improving their BI along the way. Some of the initiatives we frequently hear about are related to data quality improvement, but this may be an anomaly. According to Ventana Research’s recent study, less than half of organizations surveyed have taken on some kind of information management initiative, like data quality or data integration improvements, in the last 2 years due to budget restrictions or lack of employees with the right skills.
I’d argue that data quality initiatives should be a “top 5″ priority for organizations in 2012. Why? Because of stories like this: A friend recently told me about a meeting at his company where the regional sales managers were giving their summaries of pipeline opportunities. During one of the updates, a director interjected that he didn’t see the favorable developments mentioned in Salesforce, their CRM system. Based on the information that was present in the system, the director figured that the quarter would be an average one. However, the updates from the sales manager would really swing the potential outcome of the quarter in a positive way. Now I bet that director had to make some decisions that were compromised by the (lack of) current information in the CRM system. He might have started strategizing about how to re-engage with the (assumed) stagnant prospects, started working with marketing on a nurturing campaign, asked the telesales team to reach out…any number of things could have happened based off of the faulty information available to him.
Unfortunately, many organizations have to contend with poor data quality which ultimately results in poor decision-making. After all, decisions are no better than the data on which they’re based. Reliable, relevant, and complete data (as opposed to the incomplete data set available to the director in my example above) supports organizational efficiency and is a cornerstone of sound decision-making. So what are some of the consequences of sub-par data quality?
1) Mistrust. Poor data quality often breeds mistrust among internal departments. I read a great example from 1998 (if you can believe it) that could have been written yesterday:
In recent months we’ve explored Collaborative BI as a growing trend and how it’s gaining popularity as an extension of traditional business intelligence solutions. Despite all the hype around this topic, it can be confusing to determine what makes Collaborative BI unique. I’ve seen the terms “Collaborative BI” and “enterprise collaboration” used interchangeably a lot lately, and while both may fall under the categories “Collaborative Decision-Making” or “Knowledge Management,” there are distinctions between the two that are important to understand.
Though enterprise collaboration and Collaborative BI share some of the same features – the ability for users to interact like they would on social media, for example, rating, tagging, and commenting on content – enterprise collaboration is less specific about the type of interaction employees have. These platforms, like SharePoint and Socialcast, enable users to chat with each other, post blogs and wikis, make announcements, view the activity streams of other users, collaborate on projects, take polls, and generally do all the things they’d do in a workplace – but online. They provide a secure place for business users to work together and eliminate some of the need for project-related e-mails, phone calls, meetings, and shared drives. This article on CMS Wire gives a great example of how enterprise collaboration can improve the work life of a manager and his project team. It’s all about workflow and process-driven decision-making (as opposed to data-driven decision-making, which Collaborative BI facilitates).
Here are two ways that enterprise collaboration may look at your company: