Blog posts written during July 2009

Automatic optimisation in Agency software

Monday Monday, July 20, 2009 by Ian Pettman

Automatic Optimisation of temporary staff in a limited environment - some simple facts.

This is a non mathematical view of recruitment software for temporary staff which seeks to optimise cost for the end user.

Optimising people is not the same as optimising machines.

 

This was written by Ian Pettman who has a degree in Physics from Oxford University. It was written after a number of lengthy discussions with the following:


Dr Peter Kelen of Power Optimisation. Power Optimisation specialises in providing routines which cycle power stations down time and work schedule for major UK generating companies for the lowest cost of generating the electricity.
https://www.powerop.co.uk
Dr David Nelson who's Doctoral thesis was on optimisation of Nurses within a Hospital Trust in New Zealand. https://researchspace.auckland.ac.nz/bitstream/2292/332/9/02whole.pdf
Dr Barry Stoker who is heavily involved in extensive analytical, modelling, business and research consultancy including employment optimisation for large commercial groups.
https://www.jigsaw-consultants.co.uk/aboutus.html

 

Overview


There are three sections to this document: Mathematical factors and Human factors and Other factors. In spite of its name, Mathematical factors section is very non mathematic in its content being largely descriptive of the issues: The maths required is 5x4 level and we even give the answer!  Please give it a read, aspirin not a requirement.

 

Mathematical Factors

 

There are some straight forward rules when considering how difficult it is to perform optimisation. Optimisation of any sort rapidly becomes a complex issue when the number of items optimised grows. It is really just simple multiplication.


When it comes to choosing non interchangeable people or objects then if I am choosing one of five I have five choices. If I am choosing two of five then I have five choices for the first item but only four (remaining) choices for the second. The total is choices are 5x4 or 20. If I am choosing from ten items then 10 for the first choice and nine for the second. In this case I have a total of 10x9 or 90 choices. Only twice the number items to choose but over four times the range of choices. It rapidly gets worse as the numbers increase. In the case of an average day when 200 temp staff are booked spread over 7 or 8 categories with around a quarter HCA's (50) then the total possibilities are simply huge!   50x59x48x47x...7x6x5. In fact as numbers go this is a big one by anyone's standards.

 

To calculate every possibility will not take forever, it will take many lifetimes. Some drastic short cuts are needed for a computer program to make even a simple first choice.  Basically we need to guess what might be a good choice to start with. If we don't try a short cut the computer will not finish on the first day's shifts till after we are dead and gone. (It is actually a lot longer than that)! Of course a staff Bank administrator faced with such a task simply makes what they consider a good first choice for the first vacancy, fills it then goes on to the next. The Nurse Bank administrator can actually play an Ace card when they get to the end. They can phone someone up who has previously said they were unavailable and persuade them to work, thus not only filling shifts more quickly, but filling more in the end.

 

Actually for the computer things are a lot worse when it comes to optimising for cost in an NHS environment. Generally optimisation programs work by making a first guess, then swapping a couple of people or objects around. If things get better- good keep. If are not better, swap back and try entirely different pair of choices.  This works well when each object is slightly different. Skip the following if you think this might be reasonable.

(Example: say a bunch of sticks all of different lengths being put in storage boxes of different sizes maximum 1 stick per box. The problem: have the fewest sticks over which won't fit in any box. We have an empty box but the stick we have over is too long for the box we have empty. We have a long box with a short slick in it. Solution: swap sticks: put the short stick in the short box and the long stick in the long box. Keep doing this until we have the smallest number of sticks over and when we do a swap thing don't change (all the longest sticks are over). Now we think we have the best solution because we can see things getting better. However in the case of nurses being scheduled for lowest cost, HCA1 is on the same pay as HCA2. At first sight this does not make a huge difference. However, when we swap HCA1 and HCA2 there is no change in cost. The optimisation program knows things aren't changing and because this is what it tests for to find out if it has arrived at a good solution, it thinks it has arrived at the best solution. Wrong! This is known as the (double) valley problem. It is especially severe when optimising for overall cost when large numbers have the same individual cost.)

To sum up: if there are lots of identical values (people on the same grade) optimisation is hard.

 

Human Factors


Because by definition scheduling programs are inhuman they will lack the touch of a good staff Bank administrator. In the medium and long term, in the nature of things, the automatic program will generate higher degrees of disaffection than good Human interaction and leadership. The inevitable consequence of this will be lower levels of availability. Because of this the efficiency of staff optimisation need to be measured over an extended period and not just an initial blip of implementation. Also results need to be returned for ALL implementations.

 

We have all heard the one about "the emperor has no clothes". So by definition software that costs £100,000 has to be better than software that costs less than £10,000? The only problem is that if you analyse the level of success against the cost of the project across all IT projects then there is an extremely high correlation between the cost of a project and the chances of it NOT producing the desired results. However, in very simple terms it is a lot easier for decision makers to decide to write a large cheque and go home satisfied that they have set in motion a big project, rather than to tune a small project for improved results even though evolution may be the most certain route. Unfortunately this is just human nature.

 

By definition sales choose the most successful implementations as their references. Unfortunately when talking about statistical improvements, this is the same as flipping a coin and choosing the best sequence of heads and tails to prove their software makes heads come up 75% of the time.
When writing a cheque for £50,000, expensive software must absolutely guarantee a saving of double this to cover the high cost of ownership. Otherwise you might as well spin a coin to see if you will save money.

 

So is there a case for optimisation software? Surprisingly considering all that has gone before, the answer is a clear yes. There are a number of household names that have implemented such projects with significant payback. However when you analyse such scenarios you invariable find that the starting point was a chaotic "system" with multiple large departments operating their own individual policies, some not worried about overall cost: just making sure bodies were available so target were met; others exactly the opposite: minimising personnel costs but missing deadlines.

 

Other Factors

 

People are not machines. One of the "methods" of proving optimisation is cost effective is to take an historical set of data and then optimise it and show a net saving. Unfortunately this is not a real world scenario for two reasons. One: requests come in over extended periods. Optimise once (to give people reasonable notice) and all later requests will be ignored limiting the range and effectiveness of the process. Inevitability a staff bank will resource less costly staff first. Then (later scheduled) expensive staff (where savings can be made) will not be optimised. Ok so optimise twice before shift patterns. Now the very nature of the process is that staff will be moved around, some cancelled (at short notice): others booked (who now at short notice may not be able to fill and have to then be replaced by more expensive agency staff).  This will inevitably be an unfeeling process and lead to dissatisfaction. Compared to electricity power generators where optimisation can be a rolling process because machines do not get in a huff, people are by nature homeostatic: they like a degree of organisation.

 

Summary


What is achievable for a reasonably efficient temporary staff bank office employing between 2 and 30 consultants to allocate and manage staff temporary staff and a budget of £50,000 to £100,000 pa for software?
Ava can save you £40,000 to £90,000 guaranteed.

Web design for small temp staffing agencies

Wednesday Wednesday, July 15, 2009 by Ian Pettman

If you are a small agency or even a medium size one looking for a new style for your web site: you could do worse than have a look at this site. Open source web design is a free source of web designs for all: not just agency software. There are over 2000 designs and if there is one that appeals to you it is free to use. On the other hand it may give you some new ideas for your proposed site.

The only slight drawback is that because it's free, other people can use the design you choose too. Even so, you may find a style that you like but is not quite perfect. The contact details for the designer are there. After all, half the battle of getting a site that meets all your needs is to find a designer that does things you like.

Open Source Web Design

Effective agency software

Wednesday Wednesday, July 8, 2009 by Ian Pettman

An overview of the functionality required in Agency software packages

Any Agency software package must support the practice of effective temporary staff management. This can be broken down into four main categories: efficient (customer) request gathering, resourceful (employee) availability generation, well organised booking of employees to clients and cost effective administration of the payment and invoicing processes.

Request gathering.

To promote efficiency, vacancy information should be gathered in a number of ways and then correlated.

  • Phone/voice: the traditional mechanism, where the phone operator should be presented with a series of pick lists which both progressively reveal choices to the operator limiting and guiding their recording of the request. This method still has advantages where vacancy cover may be involved in some sort of trade off.
  • Web: here the choices should also be progressive and limited to those authorised for that user. Only valid selections should be presented to the user as the request is entered. For example a department that does not work night shifts or only employs specific staff should only have day shifts and those appropriate qualifications presented as choices. Also MRU (most recently used) times should be presented to speed data entry.  There should be provision for a staged request process where lesser qualified (but still authorised) individuals can record the initial vacancy. This is then confirmed by an authorised manager before it can be filled. There should be an email or SMS (text) notification up and down this chain.
  • Email where standard format emails are used: these should be read automatically into the main database to be immediately available, with translation where needed from customer descriptions to standard in house descriptions. An alarm (email) should advise that a new request has arrived.

Availability generation.

Availability information should be gathered and correlated in the maximum number of ways possible to ensure the best utilisation of available resources.

  • Phone/voice: whenever an employee is on the phone, the office consultant should have the ability to update availability (and any other employment critical data) and offer outstanding vacancies.
  • Web: a simple web interface should allow employees to (directly) update their own availability and see their bookings both on a standing (weekly repeated basis) and on a day by day basis.
  • Mobile: with the advent of more sophisticated phones the Web interface should be available in an appropriate style on the more modern phones. Otherwise standard text (SMS) functions should be implemented where appropriate.
  • Text / Email reminders should be sent when availability has not been updated for rolling week(s) in advance.
  • Registration: Employees current and potential should be able to register their interest securely and automatically via a web interface. To eliminate unnecessary administration and set up costs, there must be a simple secure way to link new web profiles (registrations) with existing back office entries.

Employee booking.

As this is the event that actually generates the cash flow, these options should be promoted across the board.

  • Office: A diary or journal should present outstanding vacancies and availability (historically completed bookings as well) for quick and effective placement. Work rules and laws, employee and client preferences should be automatically and fully taken into consideration to prevent inappropriate bookings. At this point there are two options: The first is to provide the consultant with appropriate information for cost effective booking and where a vacancy may not have a pre-notified suitable employee allow the consultant to use their skills to "discover" previously un-available staff.   The second is to try to use some sort of automatic or inhuman process. There are a number of technical and non technical reasons why this later process may be significantly less cost effective and indeed more costly over a period of time than the Human interface of the good consultant. These are discussed in the attached document.  
  • Web: The web should be used to provide a booking facility to authorised Manager for their respective areas of authority. The Interface should be simple, secure, by definition available 24/7 and out of office. It should draw fully on the availability stored by the system with due regard to work rules and laws, employee and client preferences. When web booking occurs there should be automatic notification via an SMS (text) to both the designated employee and other members of the management (request generation chain). The employee should be able to accept or reject the booking offer via the web or via SMS (text) reply. The system should allow multiple offers and acceptance / rejection to any given employee to be active any time. However once a booking is accepted, overlapping offers should automatically be withdrawn and management automatically notified.
    When booked jobs are displayed, identity information on employees should be available to authorised logged on users.  
  • Text / Email: Job offers acceptance and rejection should be communicated automatically via text (and backed up by email messages) where appropriate. The communications should be both to employee and the various appropriate concerned individuals for the original vacancy request.

Payroll and Invoice Administration.

Payroll and Invoice processes benefit from automation because of the elimination of human error and increased transparency by making more detailed information more readlily available. This minimises queries from both employees and clients.  

  • The system should be able to import and export employee data from standard vanilla payroll and accountancy systems (such as ESR in the NHS) via a range of standard formats. In addition it is essential that it provides automatic verification and error checking to ensure that employees (and invoiced customers) are charged at the correct contracted rates. Issues such as payroll assignment numbers being accidentally reutilised for different pay grades so causing ambiguous exports should be automatically trapped.  Contractual information for rates in different departments and working with different responsibilities (or indeed ad hoc agreements) should be readily available with standard reports. The system should maintain an audit trail of these contractual settings. These processes should be largely automatic and "instant" with manual audited overrides. Secure mechanisms should be used to communicate the information between systems.  This information should be available via appropriate the Web interfaces for employee and management access. Thus largely eliminating time consuming and inevitably costly queries which need to be dealt with manually by the staff running the employment bank or finance department. 
  • Given that a web system is in place Timesheets should be signed by Employee and Dept Management electronically where possible. Unique booking references should be used to limit accidental errors and fraud. These should only be disclosed to authorised individuals. The time sheet evaluation process should also allow performance to be scored, and this should automatically reflect back to the staff allocation page to improve the allocation process.

Summary

There are low cost of ownership software systems available off the shelf. Added value applications Ltd provides 98% of the above functionality with the exception of automatic employee rostering optimisation. For a Trust with a budget of say £50,000 to £100,000 annual spend on Temp Bank software, Ava will guarantee a saving of £40,000 to £90,000 pa. To justify a Budget holder writing a cheque for £50,000, the expensive, high cost of ownership software supplier must absolutely guarantee a saving of double this figure. Otherwise you might as well spin a coin to see if you will save money. The accompanying document which considers the complex problem of automatic optimisation, when and where it works, when and where it may actually cost money. Yes you could well be financially worse off in coming times of strict budgetary constraints. The article may help you see some of the smoke and mirrors involved in a number of sales pitches.

Acknowledgments

In preparing the accompanying document I have had numerous conversations with Dr Peter Kelen of Power Optimisation, Dr David Nelson whose Doctoral thesis was on optimisation of Nurses within a Hospital Trust in New Zealand and Dr Barry Stoker who is heavily involved in extensive analytical, modelling, business and research consultancy including employment optimisation for large commercial groups.

 

 

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