New Product Development in the Age of Smart Things

If you’re respon­si­ble for new prod­uct devel­op­ment in your com­pa­ny, you will be famil­iar with the sev­er­al steps of that process. Experts most­ly sep­a­rate the new prod­uct devel­op­ment process into seven or eight steps, start­ing with idea gen­er­a­tion and fin­ish­ing with a post-launch review. The fact that more and more things become smart; i.e. they either fea­ture some intel­li­gence or they are con­nect­ed and con­trolled through the IoT, has sig­nif­i­cant impli­ca­tions on new prod­uct devel­op­ment, par­tic­u­lar­ly in its very first phas­es. Here’s how new prod­uct devel­op­ment in the age of smart things works.

Tra­di­tion­al­ly, ideation and screen­ing of first prod­uct ideas have focused on research, brain­storm­ing, SWOT analy­sis, mar­ket and con­sumer trends, and so forth. All these activ­i­ties imply cer­tain hypothe­ses and more or less tan­gi­ble per­cep­tions of prod­ucts or prod­uct com­po­nents. This works fine, as long as the final prod­uct is a one-way prod­uct; i.e. once pro­duced and sold it won’t change (other than to age and break, ulti­mate­ly). How­ev­er, smart things aren’t one-directional, but bi-directional: they com­mu­ni­cate, they change, and there­fore their effects on con­sumers are far more com­plex and vari­able than those of their “dumb” pre­de­ces­sors. The smarter a thing, or a group of things, is, the more com­plex the sit­u­a­tions they will cre­ate for their envi­ron­ment and their users. The much-discussed self-driving cars which algo­rithms must decide whom to run over in case of an inevitable acci­dent pro­vide a good exam­ple of the com­plex­i­ty future prod­ucts will create.

Smart Prod­uct Devel­op­ment For Smart Things

Now — what are the impli­ca­tions of smart things and the IoT on new prod­uct devel­op­ment? The answer is pret­ty easy — we just have to look at the dis­cus­sions regard­ing the IoT: pri­va­cy, respon­si­bil­i­ty, sus­tain­abil­i­ty, aware­ness, accep­tance, rel­e­vance, and ethics. Is my data secure? Who takes the respon­si­bil­i­ty for data prove­nance? Do I want this thing to be smart? Do I accept a thing’s deci­sion? Do things add value? Do oth­ers accept me using my smart thing? Can I defend using my smart thing against my beliefs?
We can sort these crit­i­cal ques­tions into three categories:

  • phi­los­o­phy (eth­i­cal aspects),
  • soci­ol­o­gy (responsibility/acceptance aspects) and
  • psy­chol­o­gy (awareness/relevance aspects).

Phi­los­o­phy, soci­ol­o­gy, and psy­chol­o­gy are the “new” fields for bench­mark­ing new prod­uct ideas. As dis­tinct from present tech­niques of find­ing new prod­uct ideas, cor­po­rate inno­va­tion man­agers will have to broad­en their scopes, and com­pa­nies will have to adapt by hir­ing and train­ing their inno­va­tion depart­ments towards these fields of exper­tise. Today, only very few com­pa­nies seem to have inher­it­ed this new way of think­ing: just look at how Apple cre­ates and mar­kets its prod­ucts: there is no talk of prod­uct fea­tures, but of sus­tain­able pro­duc­tion chains, of fam­i­ly accounts or enhanced well-being.

New Prod­uct Devel­op­ment In The Age Of Smart Things

Would you have thought that phi­los­o­phy, soci­ol­o­gy, and psy­chol­o­gy would play a piv­otal role in new prod­uct devel­op­ment? Could that mean that philoso­phers sleep­ing in ceram­ic jars now can afford posh apart­ments, or for­mer­ly unem­ployed soci­ol­o­gists can choose their employ­ers, or psy­chol­o­gists leave their uni­ver­si­ties to actu­al­ly devel­op new prod­ucts? Does this require the enter­prise to devel­op a new model, or to enter a new phase in its own evo­lu­tion? And — will we see a lot more use­ful, mean­ing­ful, usable, and accept­ed prod­ucts? I think so.

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