Shipping faster by tracking Distance to Value (DTV)
My approach to avoiding scope creep and staying on track with the help of an estimation metric
If you ever watched wild life shows, you might be familiar with this sight. When a top predator chases a herd of wildebeest, she has to quickly locate an achievable target (only one of them) and give her best shot to capture it.
Sometimes, if the herd seems too far, she wouldn’t even bother to begin the chase.
I used to wonder how those predators decide when to attack and when to conserve energy. Then, I watched a leopard cub who tried to earn his first meal. He was way off. It took him a few days before pouncing on his first prey.
Product Inceptions are no different. You must have an eye for the right chase and know where to focus if you ever begin the race.
I have had my share of successful and failed products. Some products went on to earn a decent revenue (and still growing) and some didn’t make a buck.
Plenty of times the outcome was a result of choosing or not choosing an achievable goal.
Hence, for past couple of years, I started paying close attention to something I like to call the distance to value (DTV).
Distance to Value (DTV) = the time taken [to deliver] the [promised value] to the [first active user(s)]
The factors in square brackets are interdependent. The said optimisation requires tweaking these for the right balance.
- First user(s): This offers a lever to tweak audience or segments based on who is likely to jump to trial. I like to focus on the very first user.
- Promised value: Must be tweaked to get to the first user(s) faster. It may be a feature or a group of features.
- Delivery: This accounts for not just development time but the onboarding and training time required to reach the first Aha! moment, the discovery of promised value, for the first user(s).
SpaceX has a lofty vision of putting man on mars. But they have been iterating with achievable promises first. The first one was launching satellites for countries, private companies and now sending astronauts to ISA (International Space Station).
By focusing on one promise and targeted audience they have been able to deliver and earn trust. A few years back, who would have trusted a private startup with such missions.
You often hear the startup mantra of shipping faster. But often comparing the combination of promised value, finding that first user and delivery time offers a way to compare features side by side.
The estimates can be an educated guess, can be derived from competitor analysis or through research. It need not be an exact time line but can be a normalized between competing features. (e.g )
How do you decide which promise to deliver first? Write to me and I will post the best comments here.