Why data is more valuable when it's shared

This is a guest blogpost by Glen Rabie, CEO, Yellowfin.

 The role of collaboration in decision-making has been a question for academics and business leaders since modern business began. In fact, well before. In ancient Athens, back in 500 BC, the Greeks ran what can arguably be viewed as the world’s first formal collaborative decision-making process. Each Athenian (excluding women, slaves and people from the Greek colonies of the time) was invited to vote, not for a representative to make laws, but actually on the merits of each individual law.

Today, business leaders are also acutely aware of the merits of making decisions collaboratively – involving different stakeholders that can help the company arrive at the best course of action. In a recent Economist Intelligence Unit study titled Decisive Action, 87% of senior decision-makers claimed to involve others when making decisions. Similarly, when asked what single factor would improve their ability to make better decisions, over a third said “being able to take decisions more collaboratively”.

 BI’s historic shortfalls

In the Business Intelligence (BI) industry, our job is to empower people and organisations to make more decisions based on a solid foundation of trustworthy and easy to interpret data. Unfortunately though, BI vendors have done a poor job of thinking beyond the initial analysis – the focus was placed on core analytics and the technical community alone. Usability (the ease of data consumption by business users) and, importantly, an enterprise’s ability to share those insights tended to be afterthoughts – if they were considered at all. When I founded Yellowfin, after a long career working with inflexible BI tools on behalf of one of Australia’s ‘Big Four’ banks, I wanted to change exactly this situation. I wanted to remove the cost and complexity. I wanted Yellowfin to help make BI easy.

 In a world where BI technology is becoming more pervasive, and insights can be valuable to ever increasing numbers of managers and employees, the trick was surely to make things simple for BI consumers. That is, to empower business users to make better, faster and more independent fact-based decisions by focusing on how data is displayed and shared. Collaboration is a huge part of this. There is very little point in having world-beating analysis if it is the exclusive preserve of a limited number of people and is hard to interpret and act on amongst decision-making groups.

 Moving to a collaborative BI environment

Advances in the Internet – particularly the Web-based interfaces of pervasive social media platforms – have taught me and many others some valuable lessons. The rise of social media tools like Facebook, Twitter and Instagram demonstrate how successful you can be by playing the role of a content facilitator – allowing content generated by users to be shared, distributed and interacted with by an interested user base of content consumers. If people on Facebook want to comment on or share a photo, they can. Why should BI be any different?

The omnipresent and collaborative nature of such social media platforms has many people in the modern workforce quite rightly wondering why enterprise BI can’t be architected in a similar way. Downloading analysis to a static dashboard or spreadsheet and emailing it to colleagues, then phoning to discuss, then undertaking new analysis based on the new questions and then emailing another static chart simply isn’t competitive or efficient practice. It won’t deliver better, more accurate decision-making, and it’s painfully slow.

 Closing the gap between decision-making and the data

What’s needed is an acknowledgement that human decision-making today is, on the whole, taking place outside the BI platform. It could be in a meeting room or a conference call but, all too often, it is not where the data resides. Why not collaborate, and make collective decisions, within the BI platform itself? Why not facilitate the decision-making process alongside the data and data analysis, where stakeholders can interact with live datasets in real-time, add comments, make revisions and collaborate until the correct decision is reached? This is the direction in which our developers have been moving for some years now, and it’s consistently been one of the areas our customers have told us they value.

Imagine a scenario where a restaurant manager wants to know how a new product line has been performing to decide if he will continue to stock it. Not only can he instantly view product performance via a self-service chart or dashboard, he can then annotate the chart and share it with other store managers to obtain their thoughts and insights.  He can even start an entire discussion thread around the performance of this new product, allowing others to contribute knowledge and other relevant BI content, to establish the underlying factors impacting performance and to agree on a desired course of action. Allowing such collaboration enables users to connect trends in their data to real-world events more readily, providing more context and deeper, faster insight. Perhaps the product has undersold due to a company-wide stock take shutdown during the end of the financial year? Or perhaps other store managers have experienced more success because they’ve promoted the new product with a series of discount coupons.

Data alone doesn’t deliver ROI; it’s the quality of the respective business decisions that yield the benefit. When data is shared – and therefore complemented with a range of appropriate human insights and other contextual information – it is easier to take smarter collective action that delivers better business outcomes. That’s why I believe organisations should be focusing attention on collaboration as a means of increasing the value of their data, which improves decision-making processes and enhances the business benefits derived from BI.