Tag: sensemaking_spectrum

The Sensemaking Spectrum for Business Analytics: Translating from Data to Business Through Analysis

June 10th, 2014 — 8:33am

One of the most com­pelling out­comes of our strate­gic research efforts over the past sev­eral years is a grow­ing vocab­u­lary that artic­u­lates our cumu­la­tive under­stand­ing of the deep struc­ture of the domains of dis­cov­ery and busi­ness analytics.

Modes are one exam­ple of the deep struc­ture we’ve found.  After look­ing at dis­cov­ery activ­i­ties across a very wide range of indus­tries, ques­tion types, busi­ness needs, and prob­lem solv­ing approaches, we’ve iden­ti­fied dis­tinct and recur­ring kinds of sense­mak­ing activ­ity, inde­pen­dent of con­text.  We label these activ­i­ties Modes: Explore, com­pare, and com­pre­hend are three of the nine rec­og­niz­able modes.  Modes describe *how* peo­ple go about real­iz­ing insights.  (Read more about the pro­gram­matic research and for­mal aca­d­e­mic ground­ing and dis­cus­sion of the modes here: https://www.researchgate.net/publication/235971352_A_Taxonomy_of_Enterprise_Search_and_Discovery) By anal­ogy to lan­guages, modes are the ‘verbs’ of dis­cov­ery activ­ity.  When applied to the prac­ti­cal ques­tions of prod­uct strat­egy and devel­op­ment, the modes of dis­cov­ery allow one to iden­tify what kinds of ana­lyt­i­cal activ­ity a prod­uct, plat­form, or solu­tion needs to sup­port across a spread of usage sce­nar­ios, and then make con­crete and well-informed deci­sions about every aspect of the solu­tion, from high-level capa­bil­i­ties, to which spe­cific types of infor­ma­tion visu­al­iza­tions bet­ter enable these sce­nar­ios for the types of data users will analyze.

The modes are a pow­er­ful gen­er­a­tive tool for prod­uct mak­ing, but if you’ve spent time with young chil­dren, or had a really bad hang­over (or both at the same time…), you under­stand the dif­fi­cult of com­mu­ni­cat­ing using only verbs.

So I’m happy to share that we’ve found trac­tion on another facet of the deep struc­ture of dis­cov­ery and busi­ness ana­lyt­ics.  Con­tin­u­ing the lan­guage anal­ogy, we’ve iden­ti­fied some of the ‘nouns’ in the lan­guage of dis­cov­ery: specif­i­cally, the con­sis­tently recur­ring aspects of a busi­ness that peo­ple are look­ing for insight into.  We call these dis­cov­ery Sub­jects, since they iden­tify *what* peo­ple focus on dur­ing dis­cov­ery efforts, rather than *how* they go about dis­cov­ery as with the Modes.

Defin­ing the col­lec­tion of Sub­jects peo­ple repeat­edly focus on allows us to under­stand and artic­u­late sense mak­ing needs and activ­ity in more spe­cific, con­sis­tent, and com­plete fash­ion.  In com­bi­na­tion with the Modes, we can use Sub­jects to con­cretely iden­tify and define sce­nar­ios that describe people’s ana­lyt­i­cal needs and goals.  For exam­ple, a sce­nario such as ‘Explore [a Mode] the attri­tion rates [a Mea­sure, one type of Sub­ject] of our largest cus­tomers [Enti­ties, another type of Sub­ject] clearly cap­tures the nature of the activ­ity — explo­ration of trends vs. deep analy­sis of under­ly­ing fac­tors — and the cen­tral focus — attri­tion rates for cus­tomers above a cer­tain set of size cri­te­ria — from which fol­low many of the specifics needed to address this sce­nario in terms of data, ana­lyt­i­cal tools, and methods.

We can also use Sub­jects to trans­late effec­tively between the dif­fer­ent per­spec­tives that shape dis­cov­ery efforts, reduc­ing ambi­gu­ity and increas­ing impact on both sides the per­spec­tive divide.  For exam­ple, from the lan­guage of busi­ness, which often moti­vates ana­lyt­i­cal work by ask­ing ques­tions in busi­ness terms, to the per­spec­tive of analy­sis.  The ques­tion posed to a Data Sci­en­tist or ana­lyst may be some­thing like “Why are sales of our new kinds of potato chips to our largest cus­tomers fluc­tu­at­ing unex­pect­edly this year?” or “Where can inno­vate, by expand­ing our prod­uct port­fo­lio to meet unmet needs?”.  Ana­lysts trans­late ques­tions and beliefs like these into one or more empir­i­cal dis­cov­ery efforts that more for­mally and gran­u­larly indi­cate the plan, meth­ods, tools, and desired out­comes of analy­sis.  From the per­spec­tive of analy­sis this sec­ond ques­tion might become, “Which cus­tomer needs of type ‘A’, iden­ti­fied and mea­sured in terms of ‘B’, that are not directly or indi­rectly addressed by any of our cur­rent prod­ucts, offer ‘X’ poten­tial for ‘Y’ pos­i­tive return on the invest­ment ‘Z’ required to launch a new offer­ing, in time frame ‘W’?  And how do these com­pare to each other?”.  Trans­la­tion also hap­pens from the per­spec­tive of analy­sis to the per­spec­tive of data; in terms of avail­abil­ity, qual­ity, com­plete­ness, for­mat, vol­ume, etc.

By impli­ca­tion, we are propos­ing that most work­ing orga­ni­za­tions — small and large, for profit and non-profit, domes­tic and inter­na­tional, and in the major­ity of indus­tries — can be described for ana­lyt­i­cal pur­poses using this col­lec­tion of Sub­jects.  This is a bold claim, but sim­pli­fied artic­u­la­tion of com­plex­ity is one of the pri­mary goals of sense­mak­ing frame­works such as this one.  (And, yes, this is in fact a frame­work for mak­ing sense of sense­mak­ing as a cat­e­gory of activ­ity — but we’re not con­sid­er­ing the recur­sive aspects of this exer­cise at the moment.)

Com­pellingly, we can place the col­lec­tion of sub­jects on a sin­gle con­tin­uüm — we call it the Sense­mak­ing Spec­trum — that sim­ply and coher­ently illus­trates some of the most impor­tant rela­tion­ships between the dif­fer­ent types of Sub­jects, and also illu­mi­nates sev­eral of the fun­da­men­tal dynam­ics shap­ing busi­ness ana­lyt­ics as a domain.  As a corol­lary, the Sense­mak­ing Spec­trum also sug­gests inno­va­tion oppor­tu­ni­ties for prod­ucts and ser­vices related to busi­ness analytics.

The first illus­tra­tion below shows Sub­jects arrayed along the Sense­mak­ing Spec­trum; the sec­ond illus­tra­tion presents exam­ples of each kind of Sub­ject.  Sub­jects appear in col­ors rang­ing from blue to reddish-orange, reflect­ing their place along the Spec­trum, which indi­cates whether a Sub­ject addresses more the view­point of sys­tems and data (Data cen­tric and blue), or peo­ple (User cen­tric and orange).  This axis is shown explic­itly above the Spec­trum.  Anno­ta­tions sug­gest how Sub­jects align with the three sig­nif­i­cant per­spec­tives of Data, Analy­sis, and Busi­ness that shape busi­ness ana­lyt­ics activ­ity.  This ren­der­ing makes explicit the trans­la­tion and bridg­ing func­tion of Ana­lysts as a role, and analy­sis as an activity.


Sub­jects are best under­stood as fuzzy cat­e­gories [http://georgelakoff.files.wordpress.com/2011/01/hedges-a-study-in-meaning-criteria-and-the-logic-of-fuzzy-concepts-journal-of-philosophical-logic-2-lakoff-19731.pdf], rather than tightly defined buck­ets.  For each Sub­ject, we sug­gest some of the most com­mon exam­ples: Enti­ties may be phys­i­cal things such as named prod­ucts, or loca­tions (a build­ing, or a city); they could be Con­cepts, such as sat­is­fac­tion; or they could be Rela­tion­ships between enti­ties, such as the vari­ety of pos­si­ble con­nec­tions that define link­age in social net­works.  Like­wise, Events may indi­cate a time and place in the dic­tio­nary sense; or they may be Trans­ac­tions involv­ing named enti­ties; or take the form of Sig­nals, such as ‘some Mea­sure had some value at some time’ — what many enter­prises under­stand as alerts.

The cen­tral story of the Spec­trum is that though con­sumers of ana­lyt­i­cal insights (rep­re­sented here by the Busi­ness per­spec­tive) need to work in terms of Sub­jects that are directly mean­ing­ful to their per­spec­tive — such as Themes, Plans, and Goals — the work­ing real­i­ties of data (con­di­tion, struc­ture, avail­abil­ity, com­plete­ness, cost) and the chang­ing nature of most dis­cov­ery efforts make direct engage­ment with source data in this fash­ion impos­si­ble.  Accord­ingly, busi­ness ana­lyt­ics as a domain is struc­tured around the fun­da­men­tal assump­tion that sense mak­ing depends on ana­lyt­i­cal trans­for­ma­tion of data.  Ana­lyt­i­cal activ­ity incre­men­tally syn­the­sizes more com­plex and larger scope Sub­jects from data in its start­ing con­di­tion, accu­mu­lat­ing insight (and value) by mov­ing through a pro­gres­sion of stages in which increas­ingly mean­ing­ful Sub­jects are iter­a­tively syn­the­sized from the data, and recom­bined with other Sub­jects.  The end goal of  ‘lad­der­ing’ suc­ces­sive trans­for­ma­tions is to enable sense mak­ing from the busi­ness per­spec­tive, rather than the ana­lyt­i­cal perspective.

Syn­the­sis through lad­der­ing is typ­i­cally accom­plished by spe­cial­ized Ana­lysts using ded­i­cated tools and meth­ods. Begin­ning with some moti­vat­ing ques­tion such as seek­ing oppor­tu­ni­ties to increase the effi­ciency (a Theme) of ful­fill­ment processes to reach some level of prof­itabil­ity by the end of the year (Plan), Ana­lysts will iter­a­tively wran­gle and trans­form source data Records, Val­ues and Attrib­utes into rec­og­niz­able Enti­ties, such as Prod­ucts, that can be com­bined with Mea­sures or other data into the Events (ship­ment of orders) that indi­cate the work­ings of the business.

More com­plex Sub­jects (to the right of the Spec­trum) are com­posed of or make ref­er­ence to less com­plex Sub­jects: a busi­ness Process such as Ful­fill­ment will include Activ­i­ties such as con­firm­ing, pack­ing, and then ship­ping orders.  These Activ­i­ties occur within or are con­ducted by orga­ni­za­tional units such as teams of staff or part­ner firms (Net­works), com­posed of Enti­ties which are struc­tured via Rela­tion­ships, such as sup­plier and buyer.  The ful­fill­ment process will involve other types of Enti­ties, such as the prod­ucts or ser­vices the busi­ness pro­vides.  The suc­cess of the ful­fill­ment process over­all may be judged accord­ing to a sophis­ti­cated oper­at­ing effi­ciency Model, which includes tiered Mea­sures of busi­ness activ­ity and health for the trans­ac­tions and activ­i­ties included.  All of this may be inter­preted through an under­stand­ing of the oper­a­tional domain of the busi­nesses sup­ply chain (a Domain).

We’ll dis­cuss the Spec­trum in more depth in suc­ceed­ing posts.

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