How to Operationalize Data Maintenance for Better Forecasting

Operationalizing data maintenance is as much about solving human challenges as it is about implementing technical solutions. Emerging tech services companies must mature in their approach to data, and founders play a critical role in that. Here's how to ensure data is properly maintained and leveraged for better forecasting.

Start Small

The most important thing is to start small. Don't push your systems to take on more than they are mature enough to handle. Remember to be gradual with data analysis—build up your understanding through consistent, sustainable effort. If you aim too aggressively, you run the risk of becoming blocked on data collection before you can get to data analysis and interpretation. Focus on incremental improvements rather than trying to perfect everything at once.

Understand Cadences

Different data pieces need to be reviewed at different cadences. Understanding this helps ensure your team remains efficient and avoids missed reviews or burnout. Something can be easy to do once a quarter but can quickly become overwhelming if you have to look at it daily.

Here are some possible ways to categorize data review cycles, along with examples of suggested data categories:

• Daily: partner touchpoints
• Weekly: bookings, talent/people attrition rate, delivery utilization rate
• Monthly: average project margin, effective bill rate
• Quarterly: win/loss rate, average PTO/employee, partnership status
• Bi-annually: employee satisfaction (ESat)

Bear in mind that you will need to increase the review frequency for any metrics that are off. For example, you may need to review your cash daily if you are running tight on cash. A similar issue may apply to some marketing campaigns, sales pushes, and so on.

Bring the Team Together

Data collection and analysis should not happen in silos. The frequency of data collection aligns with how often stakeholders sync and collaborate on the data. These meetings reinforce deadlines for data accuracy and ensure data-driven actions are taken. Examples of key meetings include:

• Sales pipeline reviews
• Accounting and financial audits
• OKR planning meetings

But as important as they are, meetings alone aren’t enough. Accountability for the accuracy of data is crucial to preserve its value. Holding the team accountable ensures reliable data and actionable insights. There are softer tools at your disposal to do this, like reserved pre-meeting time to make sure owned data is accurate. A stricter approach we used at Flux7 was to make it clear that the CRM reflects the current state of the deals. If they are not up-to-date, then associated bonuses will be delayed.

Establish a Single Source of Truth

There must be a single source of truth for any piece of information, and people need to know the system of record containing that information. All updates to that data must be in that system. If you must choose between the two, then it is better to compromise on the customizability of a platform for your data than to have two competing platforms.

If you must still have multiple systems, then create automations to ensure the data is kept in sync. That’s because two copies of data are worse than no data. When there is no data, people recognize the gap and try to figure it out. But when there are two copies of the data, they will inevitably be off without being immediately identifiable as such. It’s similar to the difference between a compile-time error and a run-time error.

Wrapping Up

Operationalizing data maintenance requires both technological and organizational discipline. By starting small, understanding data cadences, fostering team collaboration, and enforcing a single source of truth, emerging tech services companies can improve forecasting and drive better business decisions. Leaders of emerging tech services companies must champion data maturity within the organization to drive more predictable and scalable growth.

A Gift for You 🎁

At Vixul, we spend a large part of our time reviewing the forecasts created by the founders of our portfolio companies. It is amazing for us to see our founders mature as executives and be able to answer questions they couldn't in the past. Unfortunately, most founders struggle with these issues until we point them in the right direction. We believe the lack of guidance on forecasting is a primary issue for early-stage tech services founders.

That's why we're working on an eBook with detailed instructions on how to set up forecasts for sales pipelines. This will help you plan your new year with better foresight. The book will be free for people on our mailing list when it is published, so please subscribe now to ensure you receive it.