How to execute better decision-making
Why do we hold meetings, jump on the phone or partake in impromptu hallway discussions when attempting to make a decision? Diverse opinions, backgrounds and expertise mean that we all approach the same question from different perspectives, sharing varied knowledge and experiences. It’s that multiplicity of input that helps us arrive at the best decision possible.
It’s that collaborative approach that enables business intelligence (BI) deployments to support better organisational decision-making. The success of BI tools used to report, analyse and present data in a range of formats, to help businesses identify trends and opportunities and support operational and strategic decision-making is driven by people.
Those familiar with the BI industry may contend there are many factors that determine the success or failure of a BI deployment. While it’s difficult to argue with this view, it’s my opinion that the ability to couple human interaction and insights with the factual information generated by a BI tool is critical. This is now known as collaborative BI.
What is collaborative BI?
Sometimes referred to as social BI, collaborative BI is a type of collaborative decision-making (CDM) module. Collaborative BI harnesses the functions and philosophies of social networking and Web 2.0 technologies, applying them to reporting and analytics. Such capabilities allow multiple people to cooperate in making sense of a data set and trend or instance within, leading to better and faster fact-based decision-making. The term collaborative BI encompasses and describes those shared activities and processes that, when drawn together, enable a collective decision to be made.
BI veterans Claudia Imhoff and Collin White provide a useful definition of collaborative BI, “BI software enables business users to report on and analyse business processes and associated activities, while collaboration tools enable the results of BI queries and reports as well as other related information to be accessed and shared by multiple users.
“The ultimate goal of any BI environment is to make timely and better business decisions. A collaborative BI environment supports team efforts to assess situations and make decisions.”
Demand for collaborative BI
If executed correctly, collaborative BI has the ability to form crucial connections between people, process, data and technology - to bridge the gap between insight and action by supporting peoples’ natural decision-making processes.
Gartner has suggested that around 15% of BI deployments now combine traditional BI and collaborative components in a single decision-making environment. I believe this figure is extremely conservative. Or if it’s accurate, far too many vendors are hopelessly behind the fast disappearing ‘ball’.
This demand for better enterprise collaboration, and collective decision-making capabilities, is part of a wider spike in demand for CDM software. Analyst firm IDC reported a 5.1% uptick in CDM software sales across 2012, making it the fastest growing global software segment last year.
More specifically, Wayne Eckerson’s ‘Collaborative Business Intelligence: Optimizing the Process of Making Decisions’ report found that 87% of BI professionals believe that “collaboration tools can have a positive impact on analysis and decision-making activities”, while “Fifty-eight percent of BI professionals plan to evaluate collaboration features when they purchase their next BI tools.”
According to InformationWeek’s 2012 Business Intelligence, Analytics and Information Management Survey, 59% of IT pros list “the ability for users to share and collaborate” as the most important feature to consider when purchasing a BI solution. Only mainstays “ease of use” (63%) and “fast data exploration” (62%) ranked higher.
Over the years I’ve found three key factors driving client demand and interest in collaborative BI:
- The increased demand for real-time information, in conjunction with the rapid expansion of corporate data assets, has resulted in organisations searching for faster methods to share and derive actionable meaning from reporting and analytics.
- Increasingly dispersed workforces have heightened the need for, and benefit of, fast information sharing and collaborative decision-making.
- The need to provide context to actionable information to underpin accurate, fact-based decision-making.
I’ve also found that clients who embrace best practice collaborative BI have the ability to improve productivity and visibility across the breadth of organisational operations, via enhanced knowledge sharing.
The need: why is collaboration important when using analytics?
The demand and drivers for collaborative BI seem clear. But why is conducting effective collaboration so important when attempting to use BI content to make better decisions? Information sharing and discussion allows human insight and understanding to be added to data, making it more meaningful and actionable.
Collaboration exposes the ‘why’ and ‘how’ behind data, helping us move beyond the simple ‘what’ and onto a deeper level of analysis and comprehension. For example, you might work for a sporting goods company assessing the monthly sales report. In one instance, that report might indicate a massive jump in the sale of boxing equipment. By sharing data with all the relevant business groups - Sales (did we have a focus on clearing boxing equipment this month?), Marketing (did we run a campaign?), IT (do we have errors in our data sets relating to boxing equipment?) - we’re able to determine not just what happened, but why and how it happened. Collaborative BI is about connecting the right people with the right data to maximise the effectiveness of data analysis and achieve better decision-making.
Has anyone actually proved that collaborative BI works? Aside from the strong customer results I’ve seen, analyst firm Aberdeen Group has conducted early research into this emerging area. The results of its study - ‘Collaborative BI: Harnessing the Extended Enterprise to Boost Productivity’ - are profound. Organisations that embraced and implemented best practice collaborative BI enjoyed a 42% improvement in employee productivity, a 30% increase in business process efficiency and a 40% rise in BI adoption.
Why do current attempts at collaborative BI fail?
Given these astounding results, it’s perplexing that Gartner recently revealed that some 80% of BI projects fail, citing poor communication and collaboration as the primary reasons. And, according to Accenture’s ‘Competing Through Analytics’ survey of 250 IT executives, 40% of major business decisions are not based on information generated from reporting and analytics, due to limited capacity for business decision-makers to share and discuss BI content. Eckerson’s study backs those results, finding that of those using BI solutions that already contain collaborative features, only 16% use them. Consequently, “we still see a real gap between the level of information in BI and the quality and transparency of decision-making”, according Gartner’s Rita Sallam.
How is this possible, you ask, given the proven benefits of collaborative BI? Why are users snubbing many of the collaborative elements currently available when there’s such an obviously strong demand for features that can assist collaborative decision-making within a BI environment?
Well, it seems that many technology vendors haven’t understood how to support enterprise collaboration - in relation to BI at least anyway.
What components are essential for a successful CDM module?
How should you support enterprise collaboration in a BI context? Firstly, you need to ensure that the process of collective decision-making is able to take place in full view of your up-to-date and interactive data. Inside or outside your BI environment - wherever it makes sense.
Most analytics-based group decision-making does not occur in full view of live reports and dashboards. Shared decisions are most often made via emails or in meetings, opening a gap between human insight and the business data. Decision-making remains isolated from the data that should drive and underpin it.
BI vendors should be adjusting the technology to seamlessly integrate into your natural decision-making processes, rather than making users adjust to the technology - it must be intuitive.
Eckerson’s landmark study into collaborative BI found that meetings are the overwhelmingly preferred collaborative mechanism employed by people looking to make a collective decision based on the insights gleaned from data analysis - people like to make crucial decisions together; face to face. Why would it be any different when acting on the information produced by BI?
Best practice collaborative BI is about understanding and enabling people to share BI content; discuss overlaying knowledge and contextual information on that data; and collectively decide the best course of action whenever and wherever needed - inside a BI environment, embedded within your company wiki or during a presentation.
It’s about understanding how BI technology can support the ingrained processes humans naturally undertake when making important cooperative decisions.
Or, as Imhoff and White put it: “Organizations can implement collaborative interaction and information enhancement features using the capabilities currently offered by, or being added to, many BI tools. Supporting collaborative decision-making, however, requires the use of a collaborative platform or a separate system designed specifically to meet the need for collaboration in the decision-making process.”
Enabling collaborative BI by enabling a culture of collaboration
To achieve real collaborative BI, organisations also need to adopt a collaborative mindset and support a culture of organisation-wide information sharing and data access. This breaks down departmental silos, enabling faster, better and more effective decision-making. It’s also a non-negotiable prerequisite for success, as cautioned by Gartner’s Carol Rozwell: “If you have a culture where people are rewarded for hoarding information and being experts without sharing, you’re not ready. Technology will not make an organisation collaborative if it does not already support the notion of teams from different business units working in concert on common projects.”
The birth of collaborative BI has highlighted two BI truths. The technology must assist the right people to make decisions in an intuitive, natural way; and, the right technology alone isn’t enough to ensure great reporting and analytics. The environment must be right too. It’s not just the technology but what you do with it that drives performance and return on investment.
Adopting technology conducive to innate human decision-making processes, and establishing a corporate environment conducive to collaboration, is the only way to achieve the best from your BI implementation.
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