5 Biases of Business un-Intelligence

To effectively engage in data-driven decision making we must confront the five biases of business un-intelligence . Until the day when future BI technologies can help mitigate cognitive bias, big decisions call for a collaborative effort that harnesses data and intuition.

The top reason that the highest performing organisations had for implementing BI, according to the 2014 annual Business Intelligence Gleansight Benchmark report, is executive level demand for data-driven decisions (92%). Yet unreasonable biases can impede both analysis and intuition, especially when we're making sense of big data, or tapping into the power of business intelligence.

Data denial and the downfall

Mid-sized organisations are looking to business intelligence in order to build resilience amidst the uncertain and complex business climate. It’s about having the capacity to change before the case for change becomes desperately obvious, but building resilience rarely happens in isolation. 

Having to reform an entrenched business model is a daunting task, particularly for the giant corporations among us. To build resilience is to develop the capacity to respond intelligently to changing circumstances. When we, as executives, notice a reason to change strategy, but choose to avoid what the data reveals, we're in data denial, and that could make the difference between a mid-sized organisation taking market share and the downfall of a behemoth.

Maslow's Market Intelligence

We share an idea for how charities might become smarter in a networked world by using business intelligence concepts and a transparency index based on Maslow's Hierarchy of Needs.

There is no shortage of challenges facing charities. As humanity grapples with complex issues, it is through the power of networks that the not-for-profit sector can best address human needs. To make a greater impact, donors and charities should take a closer look at their organisation as one option in a marketplace of alternatives.

Entrenched poverty, food security and failing education systems are large-scale challenges that also present massive opportunities. Through open data, these opportunities can become more apparent as a form of market intelligence. In this blog post we hone in on how open data may be structured for the benefit of all.

Fighting failure with transparency

A review of how transparency in 2014 may help address some of the causes of significant failure and incidents of fraud in 2013.

In the Anticipate Change community we dig around in emerging issues relevant to those adopting business intelligence. This post is a summary of some of the lessons learned in 2013, which we hope leads to better decision making in 2014. The focus is on failures and fraud that we noticed around the world, emphasising the need for transparency about those individuals and organisations holding power over the public.

Winning BIG with Self-Service BI

Experts indicate that midsized organisations can win BIG by outsourcing business intelligence to a self-service provider in the Cloud.

Business Intelligence has long been considered a challenge for midsized organisations. With costly systems overburdening IT departments, there is a failure to focus on the changing needs of business users. New business intelligence services in the Cloud are inviting IT departments to outsource their biggest data challenges to data specialists who can deliver a single version of the truth to multiple business users, on demand.

Decisions in the Age of Abundant Data

A summary of bite-sized insights and views about decision making from fresh articles around the web.

Over the last several months at Cause Analytics we have been scouting the web to bring you some helpful articles from experts in business intelligence. Today, our team will summarise several insights we have collected in our Google+ community in order to save you time and help your organisation with decision making.

You probably know of the debate between speedy decisions based on intuition versus slower decisions that draw upon evidence and rational deliberation. It's a complex debate because both sides have a role to play in various contexts, but in the 'Age of Abundant Data', business intelligence can aid you on your quest for faster results. As analytics and algorithms increasingly offer practical predictions, executives and managers will be able to act upon these predictions to communicate decisions reflexively, and perhaps, intuitively.

Saving Lives: Business Intelligence for Healthcare

The NHS needs to save lives and save money by innovating with business intelligence.

In the summer of 2012, Orlando Agrippa was recognised by TechWeekEurope for implementing a public sector business intelligence project at the Colchester Hospital University NHS Foundation Trust (CHUFT). Acting as the social director of Business Informatics, Agrippa, rebuilt ageing IT infrastructure and introduced analytics into the Trust’s everyday operations by introducing business intelligence solutions.

The project at CHUFT has saved the hospital over £30,000 in reporting costs, as well as contributed to the reduction of mortality rates. Reporting that used to take over 200 hours has been reduced by 70 per cent. He has seen the benefits of the platform's ‘associated model’, which allows users to "link data in a natural, logical way [so that if] you wanted to know what the length of stay within the organisation was, you can do that in 3-4 clicks.”

Mobile Shoppers with Smart Assistants

In a future when shoppers have the assistance of artificial intelligence, will you have the Big Data to guide them to your store?

How often do you see someone shopping at a store with a smartphone in hand? Mobile devices will continue to augment customer experiences in ways that retail executives ought to know about. Consider a scenario: A future when the tastes of mobile-empowered customers are satisfied with the help of intelligent personal assistants. As smartphones grow smarter with apps like Siri and Google Now, users will shop more intelligently with greater satisfaction.

Learning to Anticipate Change

Learning to anticipate change is a challenge in complex environments. Business intelligence and predictive analytics can help make sense of the signals.

We have all heard, "A smooth sea never made a skilful sailor". Well, for an analyst, a complex sea of data makes the skilful means of sensing evermore necessary. An analyst also needs a crew to help anticipate and navigate the changes that may arrive. These changes arise in three types of systems: simple, complicated, and complex.

Managing a Black Swan Event

When catastrophes strike, organisations may 'fall apart'. Managers may try to prevent the 'breakdown' and sustain operations, but in the aftermath of a disaster, no simple 'fix' may restore the previous order. A mechanistic-view of organisations leaves managers ill-equipped to handle the consequences of an unexpected event, yet it remains a common view in spite of Black Swan events.

When organisations seize their signals

How can organisations best utilise data to navigate these rapidly changing times? Answering that question does not require us to entertain the successes, failures and potential futures of big data. It simply requires tools and capabilities that enable everybody to notice what busy executives sometimes fail to see.