Data Driven Planning
This is part 1 of a 5 part series on Data Driven Planning.
It’s the end of the year which means most businesses are hard at work planning for next year. Planning is inherently a data driven activity since most business goals are based on metrics and metric targets. Those targets, and how you set them, are the most tangible embodiment of your company strategy.
As with any decision, setting these metric targets requires balancing two extremes. On one side, you want to be aggressive and push your team to their best performance. On the other side, you want to set realistic goals the team has a chance to achieve. Great targets ride that balance well, and bad targets will under-motivate your team and decrease performance.
This week we’ll cover how to use data to set great metric targets as part of your business planning process.
Tomorrow we will get started by covering how to plan when your business is growing. Always a good problem to have!
Data Driven Planning: Planning for Growth
This is part 2 of a 5 part series on Data Driven Planning.
If your business is already as large as you want it to be and you are stable and secure in your market, planning can be easy: more of the same. Few businesses fall into this category, and in most cases your business is growing or will be growing soon. How do you set metric targets when your metrics are changing so rapidly?
Consider the following metric chart we might use to set targets for Year 3 based on data from Year 1 and Year 2:
Target A is obviously not good, since it assumes the growth stops completely and we are in the same place next year as we are today. Target B is a better goal, extending the linear trendline into the future, but it assumes the growth rate stops and we have straight line growth until the end of the year. Target C makes more sense, following the historical growth trend but it might not be possible to keep increasing the rate of growth indefinitely.
A much better way to think about metric targets is in confidence intervals. Let’s revisit that planning metric, but instead of setting targets let us create a spectrum of potential targets:
Instead of specific targets, now we have ranges from which we can choose the targets that are right for the business. The red area are low targets, which should be easy to hit. The light green are stretch targets that might be hard to hit. The dark green are the most likely set of targets we might choose for Year 3.
As you can probably see, these ranges are related to the targets A, B and C we discussed before! That is because an easy way to get started setting your spectrum is to use those same three strategies (no growth, straight line growth, continued growth rate) as the start of your Low, Good and Stretch ranges. You can then modify them as appropriate to encompass your knowledge of your business and expected events over the course of the year.
Having such a spectrum in hand makes it easy to balance between being aggressive and realistic, since it is clear where your target falls. You can then choose your targets using whatever methods you prefer, and then reference check them against your spectrum to see where they fall.
Tomorrow we’ll cover some of those methods of setting targets when we talk about Planning for Efficiency.
Data Driven Planning: Planning for Efficiency
This is part 3 of a 5 part series on Data Driven Planning.
One way to think about setting targets is to ask the question “Where do I want to be?” Another way is to ask the question “How far can I get?” While the former is important when setting your strategy, the latter is critical to ensuring your goals are realistic.
A useful way to think about how far you can get is to start by thinking about how much more productivity you can get out of your business today. If you think about your business like a series of funnels (we discussed funnels previously) it makes it easy to see where there are opportunities for improvement. For example, consider this sales process and the associated conversion rates:
There are some obvious places where the conversion rate can be improved, such as the large number of Deals Closed where there is no Payment Received. Other places for improvement might not be as obvious, such as the drop from Sales Leads to Qualified Leads since it might not be obvious why so many leads are not qualified. Any improvement you can make will increase the total volume of traffic from the sales process and increase your overall revenue.
By identifying all the funnel steps that can be improved, and accounting for those improvements, you can create an idealized target – how well would you do if everything went perfectly. That idealized target is a starting point for planning, and then you can decide which optimizations are realistic and adjust your target accordingly. For example, if I think I can improve Deal Closed -> Payment Received to 75% and Qualified Lead -> Pitch Delivered to 20% then the total Payment Received would double (assuming the other conversion rates stayed the same)!
However, there will always be a limit to how much you can improve the conversion rates in your funnels. You will never close 100% of potential customers, nor can you retain 100% of your customers forever. What the limit is for each funnel depends somewhat on how aggressive you are, but also on the fundamentals of your business.
This kind of bottom up planning technique is very useful, but can be dangerous if you are too conservative. It might not be good enough to get 1% improvements between steps in your process, so make sure to check the goals you create here with the spectrum we discussed yesterday.
Tomorrow we’ll jump into more ways to sanity check your plan once you have picked your targets!
Data Driven Planning: Sanity Checks
This is part 4 of a 5 part series on Data Driven Planning.
Once you complete your planning process, the final step is to sanity check your plan. If you have followed a good process (and used some techniques we covered this week) then you should already have confidence that your plan is realistic, but it helps to check one last time.
Here are some quick ways to check your plan and see if you’ve made some bad assumptions along the way:
- Revenue per Employee Projections. We’ve covered this metric before (simply divide gross revenue by number of employees), but it is doubly useful to check your plan. If you look at your Revenue per Employee today and what it will be at the end of your plan (if you hit your targets) it should be clear if your goal is realistic. If you plan to double revenue but not hire any more employees, then you should be sure that each employee can be twice as productive. If not, then you might have missed something.
- Reverse Chronology. There are only 365 days in a year, no matter how hard we try to change it. If your plan requires opening up 4 new locations and opening a new location takes 6 months, you might not be able to open all of them in the time you have. Work your way backwards from the end of the year to make sure that whenever you start executing leaves you enough time to reach the target.
- Capacity Planning. One of the most common ways we expect to hit aggressive plans is to do more projects at once. While it is great that you can do multiple projects in parallel, over-estimating how much you can do at once is the leading cause of missing goals. Break down your targets by the capacity they require (simultaneous projects) and look at your current capacity. If you are expecting your capacity to increase significantly, you may be overreaching.
A final, less quantitative check is whether your target is intimidating to your team. In my experience, great targets are intimidating but not depressing as the team feels challenged but not by an impossible goal. That can be hard to quantify but as team motivation is critical to success it’s an important factor to take into account.
Now that you have your plan in hand, tomorrow we’ll review some important things you should do to ensure your planning process improves over time.
Data Driven Planning: The Plan
This is part 5 of a 5 part series on Data Driven Planning.
With your plan in hand, sanity checked and ready to go, you are ready to get started! Wait one minute, actually, there is one last thing you should do: Make sure you write down all the decisions you made in coming up with your plan and the data you used to make them.
Why is this important?
When you look back at your plan after executing against it, you will have either hit your targets or missed them. There are two reasons you might miss your targets:
- You failed to execute well enough.
- Your plan was bad.
Telling the difference between a bad plan and plan execution is critical if you are going to make better plans in the future.
Okay, how do I make better plans?
When you look back to evaluate yourself against your targets, you will now be armed with the decisions you made and the data you used to make them. You can look back and see if the data you used was reliable and correct, and whether the decisions you made with that data were correct. This will help you avoid the trap of evaluating your past decisions with what you know now, instead of evaluating them based on what you knew at the time.
Chances are, no matter whether you attained your goal or not, some of the data you used was incorrect or unreliable. Knowing which data was bad and why will help you choose your data better in the future and hopefully make better decisions in the future. You’ll know that you are improving when you reliably attain your targets and can look back and believe they were the right targets to set.
Next Time: The Data Driven Daily is taking a week off for the holidays. We’ll be back in 2017 with more daily advice on using data to make decisions. If there are topics you’d like us to cover in the new year, or thorny data problems you are struggling with, send them over!