Is Your Data Delivering? How to Get the Most from Your Information Management

Featured article by Jake Freivald, Vice President, Product Marketing, Information Builders

People in my sector of the software industry – business intelligence and analytics – focus a lot on how much our business is changing because of the huge influx of data coming from cloud, mobile, social media, and other emerging information sources.

That’s a mistake.

The Internet of Things (IoT) trend is accelerating this data deluge, making us expound even more about how it engenders new opportunities for companies to drive operational efficiencies by finding new insights in their information.

Also, a mistake.

Don’t get me wrong, business intelligence and analytics are important, they’re changing, and the effects of these changes are profound.

But it’s not just our industry segment that’s changing – it’s the industry itself, and it’s not just because of analytics. By focusing on the tail end of one type of data usage – the point at which a human being uses a general-purpose data visualization tool to manipulate large amounts of data to find some specific informational nugget – we risk losing out on the real benefits that big data, the IoT, and other new technologies can offer.

We can broaden our scope to include more of the ways big data can be harnessed to improve our businesses. One construct I use to accomplish this includes four key concepts: Harmonize, Visualize, Operationalize, and Monetize.

These concepts, when combined, enable organizations to focus more strategically on how they can use data to drive competitive advantage at every level of the company.

Harmonize

People love to talk about the amount of data the IoT generates. Often overlooked, especially in the business press, is the fact that most of this data has no context.

Sensor data such as 461002457819.940278 carries important information. Contextualizing that information by adding other data, such as 40.761438-74.2578777, can help. Even then, unless someone provides the full context of the business process from which it was derived, associated metadata, and other relevant data, nobody will know what it means: it is 46° and raining at my house in New Jersey on March 7, 2017. (I said it’s important, not that everyone thinks it’s important.)

Note two things:

First, this information can be used to make multiple decisions even though there’s no analysis involved; second, it’s no good if it’s old. I will use it to choose between my parka and my light jacket, as well whether to schlep an umbrella along with me. If the weather report is from yesterday, though, it doesn’t help me.

The same can be true for many operations within any business. Real-time, harmonized data can help people issue credit decisions, make offers, evaluate feedback – pretty much anything that requires a decision. Often these decisions can be automated by a real-time business process, allowing human beings to make judgment calls about edge conditions.

Harmonizing information across multiple systems, managing conflicting formatting standards, cleansing erroneous data before it infects downstream processes, normalizing hierarchies, getting 360° views of customers, facilities, liabilities, and so on – all of these things will help companies achieve a competitive advantage over companies that have little data, dirty data, decontextualized data, or fragmented data.

Visualize

In the BI and analytics marketplace, this is what most people are talking about when they mention big data and IoT. For better or worse, we tend to focus on self-service analytical tools.

Tool users can assemble their own data from multiple sources, or from multiple pools of data in a data lake. To be sure, there is value in doing so. Be careful though, because it takes a lot of time, reduces auditability, and may generate results inconsistent with others who have done the same. It also requires data-oriented skills. For instance, even though software vendors build mechanisms to help users avoid Cartesian products and chasm traps, they get frustrated when they don’t understand why we’re preventing them from doing what they [think they] want to do.

Although tool users can source their own data, the best and most reliable analysis comes from consistent, trusted, accurate data. It makes it much easier for business users and analysts to visualize that part of the data that gives them the insights they want. When they do need outside information, it helps them reduce the number of ways that incorporating that data can go wrong.

Let me also address an elephant in the room. Despite what a major analyst firm tells you, there’s nothing particularly “modern” about doing ad hoc analytics without a data model and without interference from IT. Some of us have been doing that for decades, and we will keep doing it. (I remember getting in trouble for advocating doing so back in the day, in fact – including by members of that same analyst firm.) But it’s only one use case for a relatively small number of people. Curated data and other forms of BI and analytics are important, too.

Operationalize

Visualization tools are important, but the power of information is multiplied by the number of people who have access to it. Traditionally, too many organizations only considered analysts and power users when evaluating BI and analytics tools. But everyone makes decisions. When information gets extended to all employees – given to them in a way that they can intuitively consume and interact with – then you get thousands of people making better decisions instead of a few people in a back room.

I can’t overstate the importance of considering all stakeholders and their analytical needs. The tools utilized by business analysts are not appropriate for a non-technical user. That kind of user needs information apps that are self-contained, highly interactive (so they can get answers to a lot of different questions), and focused on a specific part of their business. Intuitive applications that enable continuous monitoring of key metrics and indicators allow frontline workers and other similar users to serve themselves and quickly derive answers from relevant data.

Monetize

If you consider the attributes that help companies successfully operationalize data – self-contained, business-focused, highly interactive information applications that use trusted data – they turn out to be the same attributes you need to reach out to customers and partners. Consider a retail bank that offers customers an interactive eStatement experience instead of static PDF or paper-based statements, or a digital agency that could provide advertisers with data to measure the impact of their campaigns.

The most dramatic ROI from BI and analytics comes from these types of applications. When you can give these external stakeholders the ability to understand their relationship with you and answer their own questions, that’s money in the bank. At times, this is taken literally, because you can charge for the analytical features, and sometimes through higher customer satisfaction, reduce customer complaints, lower churn rates, and strengthen relationships.

A Virtuous Cycle

This brings us back to data. When you show someone data about themselves, it had better be complete, accurate, and up-to-the-minute, which means that harmonized data is key to visualizing, operationalizing, and monetizing it. It’s also key to feeding downstream systems to ensure streamlined, consistent processes – and those processes generate data that needs to be harmonized, visualized, operationalized, and monetized.

Big data and the IoT are changing the way we do business, and it’s up to us to change the way we approach data so we can capitalize on it.