Why is Resource Optimization So Difficult to Get Right? By Alpesh Patel

This blog explores the complexity of resourcing and some of the typical challenges enterprises face


If companies can basically give themselves unmerited pay-for-play meaningless awards, then ProFinda can certainly arbitrarily define ‘resource optimization’ as the science of selecting the best person for any role, project, assignment or task. By science we are referring to making the decision as data driven as possible, complimenting the implicit knowledge of the person actually doing the matching. Resource optimization is fundamental to every services based firm and may sound simple but in large firms, the ability to match the right people to the right work is more difficult than it sounds.  In this blog we explore four or the many challenges that make resource optimization so difficult to get right.

1. Data

Let’s talk data. Now in 2022 we would hope we are making data driven decisions on the best person. A data driven decision is likely to be a fairer and more transparent decision and far more likely to result in an optimal one. After all, Dunbar’s law suggests you can maintain about 148.3* people in your network, but could you also memorise their hourly schedule, previous work history and ever-changing personal work preferences? There may well be people out there with a photographic memory that can, but most of them won’t be employed in a resourcing and staffing team. For the rest of us mortals, we have no choice but to rely on technology to help us compute this amount of iterative data.

Sounds straightforward, right? However, one of the issues is that the data required to make the decisions – skills data, availability data, and economics data is scattered across different systems that largely do not talk to each other. Not a great start, and an extremely frustrating and duplicative exercise for the resourcing team. By the time they have finished manually aggregating the data, much of it has already changed and is no longer relevant to base deployment decisions on. 


KEY TAKEAWAY: Please put all data required to make optimal staffing decisions in one place.

2. Systems

It’s hard to be a resourcing and staffing person and not feel “technology envy”. Most of your colleagues in other parts of the organisation have new modern cloud based systems, many with AI to support their work and even a decent mobile app! HR – tick, Finance – tick, Reception- tick. Even the meeting rooms have fancy iPads attached to show who it is being used by. On the other hand, the systems that most resourcing staff, and workforce members have to use seem to be stuck somewhere in the early 2000s about the dawn of Windows 3, Motorola flip phones and belt phone holsters. Suffice to say, they make everything vastly more complicated and difficult than it should be and at great cost, all the while perpetuating sub-optimal resourcing processes and decisions.

KEY TAKEAWAY: CFO to immediately release disaster relief funds to the resourcing and staffing team. Also, to save the sanity of the vendor sales people, please don’t make the RFP a long list of compliance questions and please do not send it out just before Christmas and expect it back on January 4th. Finally, donate existing legacy resourcing platforms to a 1980s museum where they belong with the rest of the relics.

3. Employee Engagement

Life in large firms can often be a Kafkaesque form-filling nightmare. Even today, with organizational, emotional and cognitive intelligence at an all time high, employees are still expected to diligently fill in dozens of forms. When even getting employee bank details to pay salaries is hard, forget about ever getting employees to create or update a skills profile. Thinking  and best practise around skills is still very nascent and some of the claims around AI capabilities are greatly exaggerated. That said, well-trained AI combined with company-specific traditional HR  frameworks and good change management/communications can help immensely.

KEY TAKEAWAY: Please for the sake of employee sanity use AI to create skills profiles, and at best ask employees to verify any egregious errors. For every form an employee is asked to fill out the organization should plant a tree.

4. Cost Bias

Basic efforts at resource optimization tend to focus disproportionately on hard drivers such as cost, location and contractor-mix, whilst overlooking other factors such as project fit, skills-match and career development. The people tasked with optimising a project for cost may not have all the information they need to make a rounded decision and consider the flip side of cost – value generation and quality of project outcomes. The hard metrics one can be held accountable for tend to centre around costs. This can lead to defensive decision-making, where the decision-maker chooses to opt for a conservative decision, that is least likely to cause them any personal repercussions – in this case, being overly-inclined to minimise cost. This may not always be best for the business, and defensive decision-making, with a heavy focus on cost-saving, can lead to poor project delivery and poor resourcing.

KEY TAKEAWAY: Don’t over-rely on basic cost metrics  – take an intelligent and sustainable approach to resourcing decisions to support the needs of the overall business.

Concluding remarks

To be honest, I only wrote the first three points – I ran out of steam and a colleague wrote the fourth. The point is it doesn’t have to be this way. Any service firm is only months away from transforming the resourcing and staffing process.  If you’d like to learn more about resource optimization, or if you are a resourcing and staffing person who wants to vent their anger and needs a shoulder to cry on, please – get in touch. Thanks for reading!

Alpesh Patel
Commercial Director (and Voice of Reason)

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