New Product Launch; Why Some Businesses Almost Always Nail It

It just seems that way because they have assim­i­lated the art of exper­i­men­ta­tion into their DNA. And why have they adopted this men­tal­ity? To val­i­date learn­ing because what often seems like a no-brainer really isn’t. Intrigued?

 

Mar­ket pen­e­tra­tion strate­gies; from my point of view — hav­ing been charged with deter­min­ing the best path to fol­low — I can offer the fol­low­ing learn­ing. Please note that unlike oth­ers, as some­one who comes out of the finance realm my think­ing is col­ored by a quantitative-bias.

 

Often times when you’re chas­ing busi­ness growth you have to man-up, or is it woman-up, human-up… let’s run with step-up, and pull the trig­ger on some­thing that’s def­i­nitely hang­ing out­side of your com­fort zone. 

 

First, it’s ben­e­fi­cial to under­stand why you believe it to be out of your com­fort zone. If we step back and take an hon­est look it boils down to the fear of the unknown and how we as humans deal with a high level of uncer­tainty. Attempt­ing some­thing new has an inher­ent level of uncer­tainty and there­fore is a source of stress and fear. In the pro­fes­sional envi­ron­ment try­ing some­thing new never goes unno­ticed. Stakeholder’s will have pos­i­tive expec­ta­tions and it is con­cern about the reper­cus­sions of not liv­ing up to their hopes that gen­er­ates fear and often avoid­ance. Quite sim­ply, in sit­u­a­tions where the out­come is unknown and the reper­cus­sions are uncer­tain peo­ple view action as too risky.

 

Risky: the lack of com­plete cer­tainty; the out­come is not known.

 

So what are we to do? Man­age uncer­tainty by tak­ing rea­son­able risk.

 

Um, but weren’t we avoid­ing risk? Not pre­cisely, below is a def­i­n­i­tion of risk.

 

 

We should be will­ing to take risks because risk is quan­tifi­able. This allows us to deter­mine the over­all impact of our actions, set expec­ta­tions, and do a foren­sic analy­sis of the out­come. We gain a feel­ing of pseudo-control, which allows us to act. 

 

Okay, so it’s all about con­trolled expo­sure. How do we achieve it?

 

The cor­rect way to man­age risk expo­sure is to flag the key variable(s) that can be struc­tured to limit the hurt of an ‘oops’ and set them such that the all out con­se­quences can be absorbed. This is where quant-centric indi­vid­u­als might have a slight advan­tage for we have been trained on the art of iden­ti­fy­ing the sta­tis­ti­cally most influ­en­tial variables. 

 

Notice I said might; the one men­tal hur­dle that we have to over­come is an ingrained bias for accu­racy. The best les­son I every learned was pro­vided by one of my men­tors, it took him about a half year but even­tu­ally he suc­ceeded in hav­ing me real­ize that when pro­ject­ing any­thing ‘mag­ni­tude and direc­tion’ will carry you much fur­ther than a spe­cific num­ber. Your argu­ments for and against actions are much more con­vinc­ing when it is com­posed of both here is where I believe it will take us if proven true and these are the vari­ables (both con­trol­lable and uncon­trol­lable) that influ­ence our exposure. 

 

The most widely uti­lized method of rang­ing out­comes and key­ing in on the impor­tant vari­ables is ‘what-if analy­sis’. This is the heart of a busi­ness exper­i­ment, so lets take a lit­tle closer look then get back to the over­all exper­i­men­ta­tion process.

 

 

Today there are numer­ous read­ily avail­able, easy to use tools that facil­i­tate ‘what if’ analy­sis. In fact, one very use­ful toll is at the fin­ger­tips of almost every busi­nessper­son, Excel. The most pow­er­ful tool, how­ever, is your under­stand­ing of the busi­ness model mechan­ics, which can be trans­lated into a finan­cial rep­re­sen­ta­tion. Unlike the days of old – think early 2000’s – when finan­cial plan­ning & analy­sis types banged away for days, if not weeks, to craft a fully cus­tomized model many of these very same tools include numer­ous tem­plates and cal­cu­la­tors that allow you to focus on trans­lat­ing the busi­ness com­po­nent rela­tion­ships not tech­ni­cal spread­sheet mechanics. 

 

In busi­ness and engi­neer­ing the over­all over­ar­ch­ing process of what we have been dis­cussing is typ­i­cally referred to as new prod­uct devel­op­ment (NPD). NPD typ­i­cally involves two par­al­lel paths; one is idea gen­er­a­tion; the other is mar­ket analy­sis. This post focuses more on the latter.

 

Here’s my frame­work for going about it.

 

-  Deter­mine what hypoth­e­sis assump­tion you want to validate

 

-  Develop a test struc­ture the can pro­vide the right insights

-  Deter­mine who has to play with you to gen­er­ate valid data and get them onboard

-  Trans­late the pro­posed busi­ness model into a finan­cial model

-  Iden­tify the key vari­ables and deter­mine their mul­ti­plier fac­tor on the final out­come; in other words clearly com­mu­ni­cate the risk profile

-  Set con­trol para­me­ters (pric­ing, included mar­ket seg­ment, time dura­tion, etc.) on vari­ables to insure a man­age­able outcome

 

-  Reach inter­nal con­sen­sus on deliv­er­ables and commitments

-  Pro­duce a pro­to­type, mock-up, or release a lim­ited time offer to a mar­ket segment

-  Test in typ­i­cal usage/market situations

-  Cap­ture results

 

-  Ana­lyze the out­come and cap­ture what you have learned

-  Adjust or move on to the next, and repeat

 

We all must keep in mind that nearly every attempt at suc­cess will be met with fail­ures along the way, and prop­erly man­ag­ing those fail­ures can actu­ally ben­e­fit an ini­tia­tive. This is just one piece of the puz­zle explained from my per­spec­tive. I encour­age you to hone your skills on this and seek out wis­dom on the others.

 

What say ye, yea or nay? What would you add, sub­tract, or amplify?