Real time planning and what it means for marketing success
A version of this article appeared in the January 2012 Admap magazine
Planning is just guessing.
We have hunches. We need to test them.
No-one really knows.
“Almost anything we do in the world is an interaction with an almost impossibly complex economy we’ve created around ourselves.”
So said Economist and author Tim Harford at the Research 2011 conference.
The suggestion that modern life is too fast moving and too complicated to understand is gaining significant ground. Especially in product development:
“You solve impossible problems through trial and error,” Hartford continued “The difficult thing is dealing with the politics and psychology of when things go wrong — as they will.”
Things constantly change. Most initiatives fail eventually (products, change management programs, start-ups, governments…). Change makes them fail.
Those organisations that exceed expectations know how to change, often dramatically, in order to survive. The Lean Start-Up movement, popularised by Eric Ries, calls these changes ‘pivots’; nimbly shifting direction in response to a new learning; a new normal.
The 2008 IBM Global CEO Study (‘The Enterprise Of The Future’) interviewed 1,130 CEO’s in 45 countries and 32 industries, and found that organisations not only felt bombarded by change, but that many are struggling to keep up. Eight out of 10 CEOs saw significant change ahead, and yet the gap between the expected level of change and the ability to manage it had almost tripled since the previous study in 2006.
Approaches that plan around ‘feedback loops’, ‘journeys’ and ‘just in time’ decision making are better placed to deliver outcomes that move businesses forward as we can learn swiftly from what is happening, rather than what we assumed would be happening.
McKinsey, for clients ranging from the military to manufacturers, is proposing techniques based around learn and react practices, suggesting that
“fixed annual planning and budget processes are antithetical to timely strategy setting and decision making.”
The danger of an increased tactical focus is short-termism. Long-term vision is still critical, but a mix of long and short term planning should be designed to create competitive advantage through learning, rather than simply to follow conventional industry practices. So several businesses have been balancing new nimble monthly (not quarterly) budget reviews with their 3-5 year planning. This allows for a clear long-term direction, but short term ‘pivots’. Vision remains intact, but tactics move in response to opportunity.
Yet planning is still just guessing. And we appear hard-wired to be optimistic about our plans: “optimism bias” also known as the “positivity” illusion is the heuristic that guides people to over-estimate their chances of experiencing a good outcome.
So confronted with this seemingly disastrous biological defect, we humans must test everything. And test quickly. ‘Fail fast’ is the dictum of start-ups, where bootstrapping and huge unknowns are the norm.
How many times have we followed the The Agile Manifesto’s advice of stopping and seeing if our tests suggest we pivot or even quit?
“At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.”
In reality, marketing campaigns come and go seasonally, and changes in competitive contexts make even the simplest learnings difficult to bank on.
What if we entered into this selling business with the assumption that a) we will likely be ineffective (Dave Trott said that advertising doesn’t work, only good advertising works), b) that we don’t really know what will work, and c) that our entire process for operating won’t help us succeed? We’d likely get ourselves into the mindset of the start-up with a desire to mitigate all risks, as quickly (efficiently) as possible. We’d design a system to help ourselves to succeed, rather than to just deliver.
‘Delivery’, it appears, is a ‘vanity’ output for agencies. Our output should be only to drive ‘Learning’ so that we deliver more effective outcomes over the long run. Delivery of assets is a secondary responsibility to sustainable outcomes, so focus should shift to what an asset is for, rather than what it is.
To help make this happen, here’s a collection of approaches being explored, which should help the industry deliver learning-based, nimble marketing.
The right vision
If marketing is moving from pointing stuff ‘at’ people, to doing stuff ‘with’ people, then being able to respond becomes crucial to building a successful selling engine.
To paraphrase IDEO: “Don’t make marketing, solve a problem”. Solving real consumer problems, over longer periods than a campaign, allows us to plan for continuous learning. 30% of the budget on making/getting it out there, 70% on pivots and making it better.
Taking a leaf out of the lean movement, we may see a process for marketing creation and improvement as follows:
Identify (the problem and the solution options)
Make (something that works)
Improve (the thing we create)
With Alignment becoming critical throughout.
Alignment comes in three varieties:
1) Alignment with customer’s needs.
2) With client organisations
3) internally with the right type of teams to create and improve the solution.
For example, the first question we ask when a client asks for a social strategy or similar is “can you respond in real-time online?” If the answer is no, then alignment of their organisation and culture towards a listening and responding way of marketing is required before anything else happens.
Exploring potential solutions as a ‘minimum viable product’ is a useful trick. What if we did something like this? Would anyone be interested? What’s the need out there? Who’s doing this already and how could we improve it? Google insight tools provide one of the most powerful ways to test one’s earliest assumptions. Business cases can be made with minimum viable products and a few hundred pounds spent on AdWords. Brainjuicer has insight testing methodologies, so ideally all the assumptions are tested before and during the solutions are created.
We should plan for how we will create learnings up front.
So assumptions are just that. Every insight should be tested and when it comes to using things we make, claimed behaviour must be treated with great suspicion.
Scenarios, Feedback Loops and User Stories
With our ideas, we can build Scenarios: ‘what-if’ scenarios based on all available data. We don’t know what will happen, but we can model scenarios. If we don’t know anything about the area we are in, then fast Iteration and Split tests become the only way forward.
Depending on the type of thing we are creating we can judge the speed of the ‘Feedback Loop’. Fast feedback loops (as seen in digital solutions) allow us to plan how to improve what we do in close to real time. Slow feedback loops (as likely from a traditional ad campaign) will dictate what can be improved and when. The slower the loop, the more the need for Scenarios. The faster the loop, the more an Iterative approach can be used.
User Stories are a great way to show how features will work, and why certain content or asset ideas are required. When budgets get slashed (as they always do) User Stories help show how our ideas are connected. Superfluous ideas can then be ditched. Core ideas that are based on consumer journeys can be protected.
Aligning the right team to the type of brief you have is the most important part of this stage.
The teams will already be working together through Identify. Many ideas will have been explored. Honing these ideas takes the right combinations of people to be involved all the way through.
This stage is also about the plan for improving the things we create. How to learn depends on the type of brief. Anything other than a linear film requires real behavioural testing if we wish to ensure it will work. Even linear films have a place in the consumer journey, so the objectives and KPIs of that stage of the journey can be tested before and after exposure to a film.
Most solutions now are multi-faceted. So planning around the consumer journey becomes the most useful tool. Ideas have roles, and they fit within the journey model, being optimised based on their performance at that stage in the journey. This is where the data dashboard comes in.
When devising the solution we can look at Scenarios again, but through a RAP Plan. RAP stands for Responsive, Anticipated, Planned and scenarios, or actions, are mapped on a time basis (short, medium, long term). You might start with Planned and work backwards to Reactive.
Dashboards provide the raw data for the improvement of what we put out there. Data should be displayed as a ‘cohort analysis’. This means that each new person’s behaviour with our solutions is judged as unique.
‘Engagement’ in this example is simply ‘return visits’
If performance from each new cohort is not changing from our improvements, we must consider if the fundamental idea is wrong. Cohort information (vs ‘vanity’ measures like compound visitor growth) allows us to view actual success. Read Eric Ries for more on his ‘innovation accounting’ and ‘validated learning’ techniques.
I’m loving these two dashboard start-ups at the moment:
Examples of fast learning and testing:
Instagram went from an early unpopular idea based around foursquare (Burbn) to a simple, immensely popular photo-sharing app in a matter of weeks. Learning: learn fast and focus on doing one thing really well. Read the founder’s story here
Macintosh was famously designed as a writing and spreadsheet computer. It’s early users and the software it inspired suggested in was better for desktop publishing. A partnership with Aldus PageMaker software saved the company. Learning: follow your customers and partner if you have to.
Dropbox could not convince a single VC to invest in its filesharing idea. So to test their vision their Minimum Viable Product (MVP) was a video of what they *wanted* to build, not what they had built. In hours they’d attracted 10k beta testers wanting to try it. Learning: test you idea, however you can. Here’s the original MVP video
W+K’s Off-On internal energy saving solution won a Gold at the APG Awards under the Real Time planning category. It’s use of data to constantly improve the product was commended. Learning: Do, then learn. It’s journey is documented here
Made by Many’s Skype in the Classroom service that connects teachers up to help school learning are blogged about here
Old Spice W+K did a great job of responding to fans – building on what they said and finding new fans through it. Learning: invest time to have fun with your fans, and reap the rewards
Filed under: advertising, innovation, open | 2 Comments
Tags: admap, eric ries, planning, real-time