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C. Todd Lom­bar­do (@iamctodd) is an Inno­va­tion Archi­tect for small busi­ness soft­ware provider Con­stant Con­tact [link]. He is also one of our NextSen­sors [link] and worked on the major NextBrief project that exam­ined the future of tele­vi­sion [link].

In the first of a two-part guest post on how to move ahead after your team has com­plet­ed an Oppor­tu­ni­ty Can­vas [link], C. Todd talked about the process he uses at Con­stant Con­tact to decide whether an oppor­tu­ni­ty fore­sense is worth pur­su­ing. Here, he con­tin­ues and expands on that theme.

If you have begun your Design Sprint with Dis­cov­ery Inter­views — as pre­sent­ed in my pri­or post [link] — you are prob­a­bly ready to make some big deci­sion about how and when to pro­ceed with your inno­v­a­tive ideas.

Before you get out your lab coats, the first things are to con­vert your hunch­es into testable hypothe­ses and to state what assump­tions you’re mak­ing along with them.

So, what’s a hypoth­e­sis? Accord­ing to my dic­tio­nary, a hypoth­e­sis is: (1) an inter­pre­ta­tion of a prac­ti­cal sit­u­a­tion or con­di­tion tak­en as the ground for action, (2) a ten­ta­tive assump­tion made in order to draw out and test its log­i­cal or empir­i­cal con­se­quences, or (3) the antecedent clause of a con­di­tion­al state­ment. Of these, my favoured def­i­n­i­tion is the sec­ond one, an assump­tion made to test some­thing, which is what we need to do in the case of our next steps.

Your assump­tions must be testable, and pulling them apart to deter­mine how you could test them is impor­tant. Remem­ber: a hypoth­e­sis does not have to be cor­rect, and you don’t want to take action on con­cepts derived from faulty analy­sis. Let’s con­sid­er an example.

The basic struc­ture of a hypoth­e­sis looks like this: If {these changes are made to an inde­pen­dent vari­able}, then we will see {a change in a spe­cif­ic depen­dent vari­able} — assum­ing {these ele­ments are true}.

Now, to trans­late the words above into real life: If we offer a con­ve­nient way for peo­ple to down­load and lis­ten to music on a device, con­sumers will will­ing­ly pay for it.

If you haven’t already recog­nised this, it is a hypoth­e­sis for the cre­ation of Apple’s iPod, which led to the iTunes store (per­haps an overused exam­ple, but one that makes the point suc­cinct­ly). Besides, it is always fun to use exam­ples that just about every­one can relate to. As famed designed Karl Lager­feld not­ed, “The iPod com­plete­ly changed the way peo­ple approach music.”

In order to form a hypoth­e­sis, you must start by col­lect­ing as many obser­va­tions about some­thing as you can. This is the first part of the can­vas. But quick­ly, after col­lect­ing a num­ber of obser­va­tions, you need to eval­u­ate them and look for pos­si­ble caus­es for the prob­lem or sit­u­a­tion you’re exam­in­ing. Put anoth­er way, you need to take obser­va­tions and con­vert them into ever more refined insights — which is the point of the next sec­tions on the canvas.

Going back to the iPod exam­ple, it is like­ly that a group of peo­ple used to lis­ten­ing to tran­sis­tor radios and Sony Walk­mans would have, pri­or to the advent of the iPod, prob­a­bly made a fair­ly long list of obser­va­tions tied to these (and per­haps many oth­er) points:

• How peo­ple con­sume audio entertainment
• How much audio enter­tain­ment is consumed
• How many peo­ple con­sume audio entertainment
• Which chan­nels are trend­ing up, which are declining
• What types of con­tent are being con­sumed more than others

The key thought is not to jump too fast from a list of obser­va­tions right to the busi­ness plan for an untest­ed oppor­tu­ni­ty fore­sense. The soon­er you can replace obser­va­tions with mea­sure­ments, the soon­er you can tru­ly draw a pro­file of what, pre­cise­ly, the true oppor­tu­ni­ty might be. Only then can you begin the assem­bly of a busi­ness plan that is wor­thy of the Design Sprint we have been discussing.

This is not to say that this process is about the stan­dard return on invest­ment (ROI) para­me­ters usu­al­ly found in busi­ness plans. The chal­lenge of true inno­va­tion always involves a high­er degree of imag­i­na­tion than, say, decid­ing whether to open anoth­er fast food restau­rant in a busy com­mer­cial district.

Set your­self this objec­tive: As you move from obser­va­tions to orga­niz­ing your thoughts to orig­i­nat­ing inno­v­a­tive ideas, you need to learn if your hypothe­ses derived from the process are accu­rate enough to move your busi­ness toward a new direction.

Sam Costel­lo, on About.com [link], reports that Apple was not the first com­pa­ny to con­ceive a prod­uct like the iPod. Oth­ers, going back to the 1970s, played with the idea long before Apple launched the iPod in Octo­ber 2001 (after a year of development).

In ret­ro­spect, it appears that what Apple did bet­ter than any­one else was to refine the core idea and come up with mea­sure­able ways their mp3 play­er would suc­ceed when oth­ers didn’t. Or, as Costel­lo puts it: “The iPod suc­ceed­ed in part because it was the first prod­uct to real­ly make the process of load­ing and lis­ten­ing to music ele­gant and enjoyable.”

My guess is that the Apple team work­ing on the first iPod test­ed a long list of hypothe­ses before they final­ly designed the prod­uct that went to market.

Hypothe­ses are won­der­ful. Valid hypothe­ses can change the way peo­ple live.