Operations Strategy - How It Works
Key Steps:
(1) Create integrated data input and reporting systems to move previous Excel-based planning process to live dashboards.
(2) Develop new tools for rapid plan creation to speed project revenue estimates.
(3) Spearhead new 'big data' tools to create analytic reports.
Tracking People & projects
Operations …..was to help create a back-of-house system that minimized 'busy work' in executing projects so that teams could focus on the core work we need to accomplish - design and technical execution. The Operations role had several components: primarily, it comprised revenue-reporting and staffing, but it also managed technical execution and delivery, as well as legal review and risk management. So this role also creates an opportunity to align project management with design and technical execution.
Making Changes
One of the first challenges we tackled was that teams were spending a lot of time chasing project information and the system was cumbersome to update and aggregate. The firm had long-established processes, but it was difficult to get the larger aggregate picture. This was normal (I was told) but it didn't feel like it needed to be. After exploring a few solutions, it was clear the main problem we had was one of 'disconnected data' - each work-plan was a separate Excel worksheet, and aggregating them into firm-wide numbers was a manual process.
To solve this, we migrated to an Enterprise Resource Planning (ERP) system for project planning, and adopted Deltek's module for staff and project planning. We entered all new plans, as well as those in the early stages, into the system and began to get some integrated figures. We were beginning to connect the data. After about 6 months we had all the project activities in the system, and could look at firm-wide , 'connected' data.
THe 'Day One' Budget
The second challenge we tackled was that entering new plans into the system was often a very slow process. This is because our process to create workplans was to list all the tasks necessary for a design, then to assign hours and people to get a dollar cost for each task, and then add them all together to get overall labor budgets. With this method. It could often take months to get plans for large projects into the system.
We decided to flip the process. Instead of building plans from the ground up, it was just as effective to build them top-down. This was easily achieved by taking the Gross Fee, deducting consultants and expenses, and then - in a later stage - dividing the remaining fee into percentages that we knew historically were pretty consistent. The image below shows the basic breakdown for us to get an overall internal labor budget.
We start with Gross Fee, subtract consultants and expenses to get a Net Fee (Direct Labor Fee). Then we deduct a contingency and divide by the target multiplier to arrive at a DL Budget (amount of direct labor, or wages.)
The major benefit of this new method was that it was fast - often as little as 15 minutes to get the first version of a revenue estimate. This allowed us to very quickly populate the new ERP module with a plan's basic revenue over time, and very quickly we had a responsive, integrated revenue system. We even used this template for opportunities we were pursuing by multiplying the numbers by a percentage equal to our confidence of winning. So now we could track both contracted project work and also project pursuits.
Another benefit of the top-down method was that it was based on established market forces. Fee percentages are largely pre-established in the marketplace, and by building our plans this way (8% for typical new build; 12% for complex renovations, etc.), we were planning our labor budgets for projects according to fee breakdowns we were likely to see in the market.
Power Bi - Using Data Aggregation
Once we had created the ERP system, and found a way to quickly populate it, we tackled the third challenge - how to quickly aggregate and analyze the data in the system. We discovered that our ERP software had very primitive internal reporting formats, and often it was not possible to reference information from one report with that in another. So we turned to external software to create a dashboard system that consumed all the data and then parsed it into various reports that we could customize. We created the reporting system using Microsoft's Power BI (below).
With our third-party data aggregation tools, we could link to the data from the enterprise system, and create all manner of metrics and visualzations to communicate the metrics to the firm leaders and project teasm.
Over a period of 6 months we developed dozens of dashboards looking at various aspects of Operations, revenue projections, revenue-vs-actuals, staffing loads by office and discipline, A/R and days outstanding, project metrics, and a host of other variants. Once we had successfully solved the Operations information, we then were able to create a similar system for our Marketing group which allowed us to analyse wins and losses by sector, by individual, by year, month or any other metric we wanted.
Conclusion.
Overall the time spent in Operations was an interesting journey, and we were able to achieve our overall goal. We took an inconsistent, disconnected and slow process and transformed it with the use of new tools, but also new thinking on how labor -ntensive tasks can be achieved more simply and in far fewer steps. The result was a responsive, comprehensive firm-wide tool that can be viewed on any device (PC, smartphone, tablet) and in any city. No more chasing information.
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