Index ID: 07-00-E





2007 Consensus Software Awards

Product at a glance

Product type


Target Industry Sectors

All sectors flagged, including;

Human Resource Management, Immigration, Military & Defence, Homeland Security, Energy, Police & Emergency Services, Not-for-Profit Organisations, Strategic Planning, Welfare Services, Insurance, Environmental Management, Real Estate, Marketing Research

Fault tolerance

Fault tolerant

Innovation indicators

Breaking new ground
New technology
Social change or empowerment of users

A scientifically-valid, explicit and transparent approach to decision making based on patented and award-winning research

Contact for more information

Dr Paul Hansen
1000Minds CEO (joint) & Director

+64 3 479 8547

Performance indicators

Enterprise quality system
Professionally executed code
Proof of real world performance
Successful beta testing
Real user benefits
Sets new industry benchmarks

Major advance, including patented algorithms, in the Decision Analysis software industry; e.g. for a recent international survey by industry magazine OR/MS Today that includes 1000Minds, click 

Contact for more information

Franz Ombler
CEO & Director (joint)

+64 4 934 5737 (home)
mob: +64 21 259 7503

Potential indicators

Government or other agency support
Designed for international use
Global design standards
Identified potential markets
International partner or distributors
Success in home or export markets
Other – such as awards, grants etc (see below)

Contact for more information

Dr Paul Hansen
1000Minds CEO (joint) & Director

+64 3 479 8547

Product Description

1000Minds (visit our site by clicking is advanced decision-support software to help users – businesses, government organisations and individuals – to make decisions involving prioritising, ranking or choosing from amongst competing individuals, alternatives or courses of action.

Based on users' knowledge and preferences, 1000Minds creates powerful Decision Models that can be deployed for fast, effective and transparent decision making. 1000Minds is easy to use from anywhere with Internet access, and 1000Minds solutions are available in both off-the-shelf and custom-developed formats. A fully-integrated process is also available for 10s or 100s (or even 1000s) of users (e.g. stakeholders) to work together or individually.

The universality of the prioritisation and decision-making problems solved by 1000Minds ensures it has myriad applications, such as: 

Other examples can be found by clicking

1000Minds’ unique selling point is its scientific validity and user-friendliness. Our technology is the result of a decade of basic R&D centred at the University of Otago, and new product developments are underpinned by ongoing collaborations with users and other researchers/developers (Development Partners).

Why not try 1000Minds yourself?

The Consensus Awards judging panel can log in by clicking (username = password = consensus). A demo Decision Model for judging the Awards is loaded (as well as other Model examples), by which the “points” (weights) for the judging criteria can be determined in a scientifically-valid, explicit and transparent manner, and used automatically to rank the Consensus entrants (easy to input) from first to last place.


Innovation is fundamental to 1000Minds.

Our technology has its roots in patented and award-winning research started in the mid 1990s at the University of Otago in the fields of Multiple Criteria Decision Analysis and Health Economics, where we sought a scientifically-valid and practical means of prioritising patients for elective surgery.

Our discoveries developed into a fully-integrated solution to the universal problem in many applications of how to combine alternatives’ characteristics on multiple criteria to produce a single overall ranking of alternatives (for the purpose of prioritising or choosing from amongst them).

As detailed below, two NZ patents were granted in 2004, and patents are pending in Australia, US and Canada (national examinations are underway).

The innovativeness of 1000Minds has been formally recognised in both NZ and internationally:

Scientific peer review is also very important, as this confirms 1000Minds’ overall credibility. Scientific papers are with top international journals; and PhD students in NZ, Australia and Germany are working, with our input, on theoretical extensions and further applications.

We are continuing to innovate via ongoing collaborations with users and other developers. As detailed below, based on our algorithms, we are currently developing several exciting new products:


The sophistication of 1000Minds’ algorithms is masked by its simple user interface. In essence, users have to perform just three simple tasks.

(1) Specify the criteria for the decision at hand; e.g. for short-listing investment projects (an important example most people can relate to):


(2) Answer a series of simple questions involving tradeoffs between the criteria



Such simple questions are repeated (with different pairs of alternatives) until enough information about the user’s preferences has been collected to accurately rank the alternatives. Users find this very easy to do.

In contrast, other methods, such as the Analytic Hierarchy Process (used by competitors), ask: “How much more important is one criterion relative to another?” (e.g., as above, “How much more or less important is ‘ROI’ than ‘Riskiness’?”)

Because 1000Minds questions are more natural – because picking one alternative from just two possibilities is the easiest choice in the world – users can have greater confidence in their answers and ultimately their final decisions.

(3) Use 1000Minds to rank alternatives


A Points (or ‘Scoring’) System that codifies users’ preferences is also produced that can be used repeatedly if and as the alternatives under consideration change:


Everything done with 1000Minds is recorded in an Audit Report, which lends transparency and focus to subsequent discussions, and if priorities change, 1000Minds can be fine-tuned easily. 

1000Minds also has a range of useful accessories (e.g. consistency testing of decisions, and facilities for multiple users to be involved and their results compared), and the software can be run from mobile phones (as well as the Internet).

Customers include:

Plus we have licensed academic users at:

A user survey and testimonials and references are available:


1000Minds’ IP is protected by NZ patents and international patents (Australia, US, Canada) are pending (national examinations are underway):

As mentioned earlier, there are myriad potential commercial applications of 1000Minds (e.g. click, which is available as a subscription system accessed via the Internet.

Our algorithms are also available as a software developer’s kit (SDK) that can be licensed to other developers to create their own software based on our engine and tailored for their applications.

Based on our SDK, we are currently developing these new products ourselves:

We are seeking partners internationally, especially in the US. For example, we have been invited to join Chesapeake Innovation Centre in Maryland (click, the main channel for homeland & national security technology into the US, and several defence-based consulting firms are interested in partnering with us to create new products (e.g. see 1st article below).

We are receiving an increasing amount of international exposure. For example, 1000Minds was recently included in the international survey of Decision Analysis software by industry magazine OR/MS Today (click

And, as mentioned earlier, 1000Minds has been recognised in four innovation awards, including being one of six finalists (148 entries, 13 countries) in the Global Entrepolis @ Singapore Award 2005 (with Asian Wall Street Journal’s Innovation Award; e.g. see 2nd article below).

Finally, we gratefully acknowledge the grants we have received from the Foundation for Research, Science & Technology (FRST), NZ Trade & Industry and Dunedin City Council, and the support of the Upstart Business Incubator.

Other information the judges should know

(a) Referees’ contact details

(b) Two testimonials about 1000Minds

(c) Three articles about 1000Minds and its inventors

(d) Two case studies of 1000Minds applications


(a) Referees’ contact details

Dr Jan Wright (has also provided a testimonial) 
ph: +64 4 387 1770 
Mob: +64 274 986 958

Dr Ray Naden (has also provided a testimonial) 
mob: +64 21 664 301

Associate Professor Wayne Gillett
Department of Women’s & Children’s Health,
University of Otago
ph: +64 3 474 7007, ext 8565 

Associate Professor Peter Herbison
Department of Preventive & Social Medicine,
University of Otago 
ph: +64 3 479 7217

(b) Two testimonials about 1000Minds


1. Dr Jan Wright’s Testimonial


Date: 20 July 2004; revised January 2007

To: Whom It May Concern

From: Dr Jan Wright
Director & Consultant
Parliamentary Commissioner for the Environment, from 5 March 2007

I met Dr Paul Hansen in 2002 when we were both appointed to a Ministry of Health working group on the prioritisation of health care interventions. My interest was immediately aroused when he told me about the decision analysis theory and software application that he and Franz Ombler were developing.

I first studied decision analysis about ten years ago when doing my PhD in Public Policy at Harvard University, and subsequently taught it to Masters students both at Harvard and at Victoria. At Harvard, a basic knowledge of decision analysis is “core” material at both the Kennedy School of Government and the Business School.

Since returning to New Zealand, I have been a director of four Crown entities and also worked as a consultant. In both functions, my primary interest has been in allocation policy – the normative problem of what you do when you don’t have enough funding to do everything that is worthwhile. Typically, there are several criteria that are intended to form the basis of allocative decisions. Thus, some form of multicriteria decision analysis is required.

The approach most commonly used is to create a linear multiattribute utility function. Each decision-making criterion is given a score, and then the score is weighted by the importance placed on the criterion. The weighted scores are summed to give the utility of the option.

The appeal of this method is strong because it appears to combine objective measurement by analysts (the scoring of the principles) and subjective valuation by the decision makers (the assigning of weighting factors). But there are two major problems:

1000Minds avoids both of these problems through some very nifty mathematics. Because of this, my academic side is very excited by it and I look forward to its publication in a prestigious journal.

However, 1000Minds is also practical. To the best of my knowledge the method is original, but even if this theoretical advance has been made elsewhere, the user-friendly software is a major innovation. Although its application is most obvious in the health sector, it has the potential to add significant practical value to analysis undertaken by four of the Crown Entities of which I have been a director. These Crown Entities are Land Transport NZ (Chair), Transit NZ, the Accident Compensation Corporation, and the Energy Efficiency and Conservation Authority.

In my consulting work in the public sector, I see multicriteria decision problems everywhere. For instance, I have worked for PHARMAC in the area of hospital pharmaceuticals, and it is clear that DHBs could usefully use 1000Minds in controlling the use of hospital pharmaceuticals. The same kinds of dilemmas exist in the private sector, albeit with different kinds of criteria.

In summary, it is my opinion that 1000Minds is highly innovative, intellectually rigorous, user-friendly, and with great potential for practical applications.


2 Dr Ray Naden's Testimonial (from an email)

I am a contracted consultant to the Ministry of Health. Our project is to support the improvement of systems within the health sector used to prioritise which patients have access to elective medical and surgical services (essentially patients on “waiting lists”). We are using 1000Minds with groups of medical specialists who are leading the developments of their prioritisation processes. We have been using 1000Minds in a range of medical specialties for about 3 years now.

I consider 1000Minds to be excellent value for money. It fills a unique need for us in providing a structured and transparent way of allocating weights to factors which need to be taken into consideration in making prioritisation decisions. Furthermore the use of 1000Minds stimulates clarification of those factors; it is proving to be much quicker and more acceptable to the clinician specialists than previous attempts to do this. This saves considerable expense in the cost of (expensive) people’s time.

1000Minds is conceptually simple. The system has considerable flexibility built into it and this is being developed constantly. The only difficulty we have had is learning to use the considerable functional capability well. In this respect, the ongoing support from Franz Ombler and Paul Hansen has been prompt, efficient and extremely helpful.

Hope this is helpful. Feel free to call me if you need more information.

Ray Naden 
Ph 021 664 301

(c) Three articles about 1000Minds and its inventors

(Another 12 articles can be found by clicking

1. Article about 1000Minds in National Business Review, 5 May 2006


5 May 2006

Sharpening up to woo US national security

From kooky to GQ, the floral shirts are out for one of New Zealand's most promising program developers.

by Mark Peart 

The owners of an award-winning software program that aids decision-making by ranking user preferences is trying to crack the growing US homeland security market. 

Dunedin-based 1000Minds, formerly Point Wizard, is the developer of a point-and-click software programme, which is based on a combination of selected criteria and answers to specific questions. 

Owned by Paul Hansen, a senior lecturer in economics at the University of Otago, and Franz Ombler, a Wellington information technology specialist, 1000Minds has approached the Chesapeake Innovation Centre CIC in Anne Arundel County, Maryland. 

CIC is a business incubator and technology commercialisation hub whose focus includes the development of firms specialising in homeland security technology. 

CIC has been developing partnerships with federal agencies, universities, and key corporations in the US as it seeks to develop new companies in the homeland security, defence, communications and IT sectors. 

Dr Hansen said the CIC was funded mainly by large companies associated with the US military and aerospace industries. The world's biggest spy agency, the US National Security Agency, is one of the funding partners. 

"They CIC partner up outside IP intellectual property such as ours with American companies that could have a use for it. 

"We're in there and on their books and they're assessing us and trying to decide whether there's a fit there. 
"Whether it comes off or not, you just can't tell." 

1000Minds' track record is mainly in diagnosing or prioritising patients for health treatment, which was the catalyst for Dr Hansen developing the program in the first place. He's been interested for nearly a decade in refining New Zealand's healthcare points prioritisation system to make it more accurate and fairer. 

The amiable Dr Hansen was well known on the Otago University campus for his long hair and floral shirts - unconventional garb for a leading economist and former senior Treasury analyst. 

But the commercialisation game has had an effect on his appearance. The long hair has been cut and the shirts are more mainstream, all part of the steep commercial learning curve he's on. 

Having smart technology is one thing, but looking smart can also help in wooing business partners.

Across the Atlantic, 1000Minds is trying to interest the UK's National Health Service in its software, because of the NHS's similarity to the New Zealand public health system, including troublesome waiting list management issues.

"The thing I'm learning is that you don't know what's going to happen, but you've just got to keep things in the pipeline," Dr Hansen said. He said he and Mr Ombler would definitely license the program at some point. 

"There are so many different possible applications that we'll licence the technology for a particular application while maintaining our interest in areas we want to continue in." 

The company has secured two New Zealand patents this year and has begun a three to four year process to secure patents in the US, Canada, and Australia. 

"There won't be much change out of 100 grand [for the patent process], so we've really had to decide: are we in this seriously, or not? We are." 

©Fourth Estate Holdings Ltd


2. Article about 1000Minds in The Asian Wall Street Journal, 21 Sept 2005
(note: 1000Minds was formerly known as “Point Wizard”)


21 September 2005
Asian Innovation Awards: Contenders Stress Different Ways of Thinking – Entries Vary From Software For Narrowing Preferences To an Imaginative Auto
By Jeremy Wagstaff

You would think that computers make decisions easier. All that information available. All those tools to sift through that information. All those programs to organize the information and to pluck from it the most important points. But that hasn't happened.

Say you are choosing a hotel. Sure, you can arrange a list of hotels according to their star ratings, their newness, their price or their popularity, but can you arrange them using a combination of criteria? And how about your own preferences – room size, whether the rooms have Jacuzzis, how close it is to a Starbucks? 

Computers haven't really helped us make these kind of choices, but that is something Point Wizard [now known as 1000Minds] Ltd. of Wellington, New Zealand, hopes to change with a program called Point*Wizard [1000Minds]. "The really innovative thing about Point*Wizard [1000Minds] is that it gets you to make the simplest of decisions," says Franz Ombler, Point Wizard [1000Minds] co-director. 

Point Wizard [1000Minds] is one of six finalists for the Global Entrepolis@Singapore Award, presented by The Asian Wall Street Journal in association with the Economic Development Board of Singapore. Entries for this award are judged on the basis of innovation, technology and commercial potential.

Point*Wizard [1000Minds] uses a mathematical approach called "pairwise trade-offs." Simply put it is a process of ranking your preferences and then whittling down the choices by pitting two choices against each other in a series of run-off contests based on the rankings of your preferences. Mr Ombler explains: "It generates a points system, which can then be applied to alternatives as they arise: hotels in the city you land in, choosing a new car, patients that apply for fertility treatment." 

This idea isn't new, but the fact that Point Wizard [1000Minds] has been able to harness it into simple point-and-click software is. "The idea of pairwise trade-offs for this sort of task was considered back in the '70s but was abandoned because it was considered too hard," Mr Ombler says. "Instead the academics opted for harder questions. On a scale of 1 to 9 tell me how much you prefer Heineken to Guinness? Instead, we ask the simpler and more accurately answered question: Which do you prefer? Heineken or Guinness?" Point Wizard's [1000Minds] patented approach is called Potentially All Pairwise RanKings of Alternatives, or PAPRIKA for short.

Of course, the software isn't just about choosing hotels or beer. Mr Ombler says the software is being used to prioritize patients for treatment by New Zealand's Ministry of Health. "The exciting bit for nonmathematicians, e.g., doctors, is that now there's a decision-analysis tool that asks the simplest of questions [and so the easiest for them to answer, especially in a group], and produces the most accurate prioritization decisions." 

Singapore company System Access Ltd., another GES finalist, also uses software to simplify things. In its case, that is financial systems. Banks long have been, as the company describes, "a patchwork of in-house-built departmental systems and niche software packages stitched together and layered upon each other." System Access's solution: Symbols, a software overlay that allows customers to cherry pick their products from rival vendors, but weaves them all into a "highly cohesive and seamless experience." 

Symbols is a kind of umbrella for all the kinds of software a bank uses, making a complex system more manageable and easier to use. At the other end of the spectrum, a finalist from Malaysia, ViTrox Technologies Sdn. Bhd., is like a microscope, improving the way companies check for defects in computer chips. Its product, in the company's words, "has the power of sight. This computer system enables the automated visual inspection of manufactured products for quality and process control." 

Not all the GES finalists are for backroom experts. REVA Electric Car Co. in India, for example, makes the environmentally friendly electriCity car that now is being sold not only in India but also in such places as the U.K. In Britain, customers receive government support in the form of a subsidy, no road tax, no congestion charge in the capital and free parking.

The car's commercial success caught the eye of fellow Indian Anil K. Gupta, one of the judges, who says the car "has a futuristic tinge, has created global demand and has influenced polices in the direction in which world markets need to be molded in view of an energy crisis looming in the horizon." 

This approach of leveraging innovation for the ordinary consumer lies behind another finalist, Hong Kong Broadband Network Ltd. Not just another Internet provider, the HKBN uses a technology called Metro Ethernet to pump super fast – 100 megabits a second – Internet connections into half a million Hong Kong homes. If your senses have been a little dulled by claims of super fast Internet connections, compare that speed to the average ADSL connection, which allows for six mps. What might you do with all that bandwidth? Think Internet-based television, downloading whole CDs-worth of music in a few seconds or sending large chunks of video to friends across town (or the world).

Finally, if you feel you don't get enough advertising on your television set at home, China's Focus Media Holding Ltd., another GES finalist, has the solution: outdoor media. It promises a network of flat-panel television displays in building lobbies, supermarket aisles and other consumer-rich locales, running specially devised DVDs chock full of commercials "to bring audiovisual advertising to various locations to target people where they work, shop, travel and entertain." 


3. Article about 1000Minds in New Zealand Listener, 12-18 Feb 2005 Vol 197 No 3379

Dial a decision

by Hamish McKenzie

One day soon, your cellphone may tell you what to do next.

You’re on your way to a barbecue and you stop at the supermarket to pick up a bottle of wine. You want to limit the damage to your wallet, but you want to buy something decent. There are dozens on offer. How do you choose?

Help is at hand from a computer program that, in the not too distant future, could deliver an answer straight to the screen of your cellphone.

Decision-making is big business. A company may need to decide which of 150 job applicants to short-list. A surgeon has to choose which of 250 invalids wanting knee surgery will go under the knife. 

These are the questions academics love to grapple with. They scribble stuff on napkins when they should be having lunch or they write long analyses for obscure journals like the Journal of Multi-Criteria Decision Analysis. And these academics include Dr Paul Hansen.

A young economics lecturer at Otago University, Hansen has been interested in surgery waiting lists for more than 10 years, since New Zealand introduced a prioritising points system in 1996. His analytical brain was exercised by wondering how the points were allocated – and how we could know they were allocated fairly.

“One day I had a eureka moment, an enormous insight as to how the point values could be determined,” says Hansen, sitting in an unkempt office strewn with takeaway coffee cups. He’s a flurry of words as he squirms in his seat or bounds across the room to draw diagrams on his whiteboard. And the reason for his buzz is his new decision-making program, Point Wizard [now 1000Minds], which he hopes will revolutionise the decision-making process.

Hansen developed the system with Franz Ombler, a Wellington computer programmer also bitten by the problem-solving bug. Though it’s still in its preliminary stages of development, a PhD student at the Australia National University is using the program to help East Timor decide what to do with the billions of dollars coming from its undersea oil fields. “Should they spend it on armaments to try and keep Indonesia at bay?” Hansen asks. “Should they blow it on a party? Should they put it into health or education?”

At its core, Ombler and Hansen’s program makes the process of points allocation for priority lists fair and transparent. It also considerably simplifies multiple-criteria decision-making.

It’s a more significant achievement than it sounds. The Ministry of Health is currently trialling the system to help devise waiting lists for heart operations, hip and knee replacements, cataract operations and fertility services. Dr Ray Naden, a physician working with the ministry, says it wants to improve its methods of assessing the relative priority of patients. It is difficult, he explains, to decide how much weighting to give social as opposed to clinical factors: how the wait for surgery will affect someone’s employment, for example. Point Wizard [1000Minds] allows doctors to determine the points weighting of each factor by answering a series of scenario questions.

“There’s always a nervousness when the factors being assessed are entirely subjective,” says Naden. “Maybe the doctor is being swayed by emotional things.” Point Wizard [1000Minds] removes the emotional element from the equation. It’s a prospect that Naden says is looking “really good”.

The program’s use is not limited to life-and-death decisions. Hansen has a colleague who used it to help him choose a house. One popular girl used it to rank a list of 20 potential paramours.

“We imagine it being on people’s cellphones, or certainly something that’s on your laptop to help you when you’re sitting in an airport lounge,” says Ombler. “We’ve even imagined it on automatic teller machines, where instead of it just giving you cash, you go there to make a decision,” he chuckles. “But that’s probably pushing it a bit far.”

All content © 2003-2007 APN Holdings NZ Ltd. All rights reserved.


(d) Two case studies of 1000Minds applications


Case Study 1: New Zealand Ministry of Health’s Use of 1000Minds

Historically, in New Zealand and most countries internationally, demand for elective health services has typically exceeded their immediate availability. Prioritising patients, usually via waiting lists (or ‘booking systems’), is therefore inevitable.

Prior to their overhaul in 1998, New Zealand’s waiting lists were “a diverse mix of patient cases – placed and kept on the list for a number of different reasons, and with no agreed criteria for admission to the list.” (National Health Committee, Fifth Annual Report to the Minister of Health, 1996). Patient access was also often inconsistent across regions and specialties.

In 1998, Clinical Priority Assessment Criteria (CPAC), often implemented as points systems, were introduced to remedy these problems. But since then the validity of the patient rankings (and the resulting health outcomes) produced by some of these original points systems has been seriously criticised.

Since 2004, using 1000Minds (formerly known as Point Wizard), the Ministry of Health has led several projects to create and validate new points systems (and where possible revise existing CPAC tools), with the goal of more equitable access to elective services and improved patient outcomes overall.

In collaboration with the New Zealand Region of the Cardiac Society of Australia & New Zealand (CSANZ), this was done first for coronary artery bypass graft (CABG) surgery. A group of CSANZ cardiologists and cardiac surgeons in different locations throughout New Zealand used 1000Minds software via the Internet and teleconferences to create points systems for prioritising patients for CABG surgery. These points systems have been formally accepted by CSANZ, and CSANZ intends also using 1000Minds to prioritise patients for heart valve surgery.

The validity of these new points system was evaluated by the participating clinicians examining the face validity of the relative importance of the criteria implied by the point values, and also by comparing the overall ranking of sets of patient case descriptions (‘vignettes’) produced by the points system with the rankings from the clinicians’ unaided expert judgments (effectively, the ‘gold standard’ here). As well as passing these tests, a survey of the participating clinicians revealed high levels of ‘user’ satisfaction with the 1000Minds method/software.

Other professional bodies, also supported by the Ministry of Health, have also used 1000Minds for prioritising patients for hip and knee replacements, vascular surgery, cataract surgery, and gynaecological, sterilisation and infertility treatments respectively, with similar results.

Based on this overall body of work, 1000Minds/Point Wizard won the Telecommunications Users’ Association of NZ (TUANZ) Healthcare Innovation Award 2005, and was a finalist for two other (independent) awards: Global Entrepolis @ Singapore Award 2005 (in association with The Asian Wall Street Journal’s Innovation Award) and the 2006 NZ Health Innovation Award.

Working together as Development Partners, the Ministry’s and 1000Minds’ goal of developing a fully-integrated prioritisation process supported by information technology has been realised. 

Other uses for 1000Minds include diagnosing patients and predicting health outcomes, advanced planning for pandemics (e.g. allocating Tamiflu), Health Technology Assessments, Strategic Planning, and assessing students for admission (e.g. to medical, dental & pharmacy schools) and health care professionals for jobs (e.g. junior doctors for hospital posts).


Case Study 2: University of Otago’s Use of 1000Minds

The University of Otago awards approximately 300 scholarships (worth up to $25,000 each) for Masters and PhD study annually, from 800 applications. Effectively, the ‘winners’ are selected via a university-wide competition where, for example, Music students are assessed against Medical students by a Scholarships Committee comprising senior academics from the four faculties (Humanities, Sciences, Health Sciences and Commerce).

Each applicant is assessed on three criteria: (1) Grade Point Average (GPA), and an assessment by the Head in the applicant’s nominated department of her/his (2) past research performance (e.g. for an Honors or Masters thesis) and (3) ‘fit’ with the research program in the department.

Before using the 1000Minds software, the Scholarships Committee, notwithstanding its good intentions, effectively mostly ignored criteria (2) and (3) and did little more than rank applicants by their GPAs. This happened because the ‘hardness’ of the GPA data effectively overwhelmed the ‘softness’ of the data for criteria (2) and (3) (so that they ended up, in effect, being paid ‘lip service’ only).

This generated a great deal of unease around the university. It was felt that students who had performed exceptionally in their exams (thereby ensuring a high GPA) but who (in the opinions of academics in a position to judge) were less gifted research-wise or who did not fit into the department’s research program were being awarded scholarships at the expense of other students with slightly lower GPAs but with more promising research careers and who matched their department’s research program.

To remedy this, in 2004 the Scholarships Committee sat down with the 1000Minds software and created a Points (or Scoring) System for awarding scholarships that properly recognized the importance of all three criteria. The end result is that criteria (2) and (3) now receive approximately half of the total points available for assessing a student (with the other half dependant on GPA). 

These relative weights (derived using 1000Minds) were consistent (ex post) with Committee members’ common sense (i.e. had face validity). Moreover, members reached a greater appreciation of what each (representing their respective faculties and departments/disciplines) considered to be important when awarding scholarships. Finally, the transparency (including an audit trail) of the software’s processes was especially important to the wider University community.

1000Minds is also ideal for assessing students for admission to restricted-entry courses such as medical, dental and pharmacy schools and MBA programs. 1000Minds has also been used at the University of Otago for selecting Teaching Fellows in the Department of Design Studies and for benching-marking the School of Business against its ‘peer’ and ‘aspirant’ Schools internationally.

Contact Details

Principal contact:

Dr Paul Hansen
CEO & Director

+64 3 479 8547


Upstart House, Level 1, 333 Princes St, Dunedin, New Zealand 

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