Turning Knowledge into Wisdom with Business Intelligence for Project-Based Businesses

What does it mean for a business to be data rich and knowledge poor? The truth is, extracting information from data across multiple systems can be fraught with complications. Understanding the difference between reporting and analytics and how they fit into the effective management of a project-based business via enterprise resource planning (ERP) are vital components to making strides rather than staying stagnant.

Getting Smart with Business Intelligence

Having mounds of data is great, but data is nearly useless if it can’t be turned it into actionable information. That is why investment in a business intelligence application to make sense of all of the data is a critical component of success. A right-fit application, like Costpoint Business Intelligence, is a one-stop shop for assessing results by project, department, account, customer, organization, and vendor.

All business intelligence systems have some components in common:

Data – All functional areas within a business likely have their own applications, databases and spreadsheets. Maintaining systems for accounting, time and expenses, human resources, customer relationship management, budgeting, and manufacturing are part of the day to day.

Metadata – Metadata is the way a business intelligence system makes sense of data. Similar to a library catalog, it allows for categorization of data by all the attributes that are important to a business.

Report-Authoring Interface – This aspect of a business intelligence system allows for graphical representations of data. Authors will choose elements from the metadata (for example, revenue by project) and structure the report in a manner that’s easily understood.

Consumer Interface – The view of the business intelligence system that most employees will interact with. Provides access to information for reporting.

Administrator Interface – Where the designated administrator secures data, controls the environment and monitors use.

Creating Useful Reports

The foundational elements for building useful business intelligence reports are fairly simple and generally help the reviewer avoid wasted time. By keeping things simple and considering what a reviewer really wants and needs to see, their “care-abouts,” users will start out on the right foot. Ensuring data is current is vital for effective decision making, as is consistency of use and communication. Using the same reports for everyone as much as is practical allows everyone to stay on the same page with internal intelligence.

Getting to Know Analytics

Analytics is best defined as the use of data and analysis to identify trends and make business decisions. Although analytics may be easily confused with reporting, there are notable differences.

An analytics platform is deployed as a series of dashboards, with each one typically tied to a specific key performance indicator (KPI) or metric. Because different members of an organization may be interested in different KPIs, it is typical that executives may follow one set of dashboards, while project managers follow others. KPIs are the measures that drive business. Although each business is different, there are several KPIs that apply nearly universally to project-based businesses:

• Revenue
• Profit
• Backlog
• Labor utilization
• Indirect rates
• Proposal win rate
• Days sales outstanding.

Budgets, Forecasts and Trends, Oh My

If the labor utilization for a specific company division over the first six months of the year was 75%, what kind of assumptions could be made, and what actions would likely be recommended? It is hard to say, because it’s difficult to make sense of that statistic without any perspective or comparisons. Now imagine that division’s utilization for the prior year was 78%, and that the budget for this year is 82%. This gives a better idea of where the division stands and some cause for concern. Stir in a little more analysis, and decision makers could start to suggest corrective courses of action.

Comparisons to budgets, forecasts or targets are critical components of an analytics environment. As the example highlights, metrics in a vacuum are virtually meaningless. Evaluating performance against the baseline budget is often the best way to gauge whether the organization is meeting expectations.

Forecasts typically represent the “best guess” today of how the organization will perform in the future. Combined with actual results, forecasts can provide valuable visualizations of trends.

Analytics can provide insights that drive informed decisions. Reporting nearly always focuses on looking in the rearview mirror. That can be important, but it’s also history, something that cannot be controlled. A company can start to impact where it’s headed by charting out trends that incorporate both history and future projections.

Examining the Metrics That Matter Most

Every organization measures itself in a slightly different manner, but certain key metrics are relevant for a high percentage of project-based businesses. Here are some of the metrics likely to be most useful to a project-based business.

Revenue – The revenue recognized by project-based businesses is shaped substantially by the contract type(s) in effect for each project. Revenue is calculated differently for time and materials, cost-plus, and firm-fixed-price contracts — and countless variations exist for each primary type. Evaluate your revenue analytic by organization, project manager, customer and specific project.

Profit – This is arguably the most important metric for any company and is the ultimate measure of your success. As with revenue, profit is impacted largely by contract type. Companies should be able to assess profitability trends across contract type to ensure that they’re pursuing the right type of business.

Backlog – Backlog analytic helps track how much work remains for an organization and allows for measurement of whether they are operating above or below budget. Make sure that this analytic includes existing contracts and those proposed opportunities.

Labor utilization – This metric evaluates how efficiently employees are being applied to direct, or billable, projects. The labor utilization analytic can offer insight into which employees are over- or under-performing and to confirm if staffing levels are appropriate. It’s imperative for management to review both direct and indirect components of the metric.

Indirect rates – Many companies track at least two different versions of rates for indirect pools, such as fringe, overhead and general and administrative (G&A). The target rate is the estimated rate based on its budget, while the actual rate is calculated based on incurred costs. Comparing both as the fiscal year progresses is a critical function and a valuable component of an analytics system.

Proposal win rate – Setting targets for proposal win rates across different parts of a company will allow them to evaluate the performance of their business development function.

Days sales outstanding (DSO) – The processes of quickly and efficiently recording costs, billing the customer and receiving payment have a dramatic impact on company success. Errors in coding vouchers or timesheets or delays in generating invoices can be devastating to cash flow. Days sales outstanding (DSO), is a measure of the time it takes to collect on an invoice, converting a receivable into cash.

Projects at risk – Perhaps the greatest potential of an analytics application is the ability to draw attention to areas that need corrective action. Project-based businesses want to quickly know whether they’re operating projects that have the potential to generate losses or leave the company out of compliance with contract terms. Examples of risk categories:

• Billing in excess of the funded contract value
• Costs incurred after the project’s end date
• Revenue recognized in excess of the contract value
• Revenue recognized below the budgeted amount.