Data an­a­lyt­ics

let data speak

The Smart Manager - - Contents - NA­JEEB KU­NIL IS THE EX­EC­U­TIVE DIREC­TOR AT PPZ.

Na­jeeb Ku­nil, PPZ, highlights how real-time data an­a­lyt­ics can help com­pa­nies sur­vive in today’s un­pre­dictable busi­ness en­vi­ron­ment.

We live in times where any in­for­ma­tion is avail­able lit­er­ally at our fin­ger­tips. Easy ac­cess to in­for­ma­tion is an im­per­a­tive for busi­nesses, espe­cially for an un­com­pro­mised facet called ‘speed.’ With each pass­ing day, the pace of busi­ness is ac­cel­er­at­ing, and be­ing aware of all as­pects of your busi­ness—any­time, any­where—is manda­tory to re­main rel­e­vant.

Knowl­edge about your busi­ness or busi­ness in­tel­li­gence not only pro­vides an edge, but also en­ables you to take quick, timely, and in­formed de­ci­sions on the go. This is all the more the case with re­tail busi­nesses, which are

un­pre­dictable and dy­namic. How­ever, de­vel­op­ers/in­vestors have seen re­tail as the most lu­cra­tive an­nu­ity in­come­based real es­tate class. Track­ing con­sumer be­hav­ior and per­for­mance on a daily ba­sis will im­mensely help re­tail busi­nesses strate­gize long-term plans as well as make quick rec­ti­fi­ca­tions. With hun­dreds of shop­ping malls hav­ing come up across the coun­try in nearly a decade, the need for an­a­lyz­ing data for bet­ter ef­fi­ciency—which then leads to suc­cess—is never more im­per­a­tive than now.

Also, this seg­ment is at­tract­ing more in­ter­est than ever be­fore in terms of FDI, new la­bor laws, and more op­er­a­tional hours. Hence, trans­parency and pro­fes­sional man­age­ment have be­come the need of the hour. As we also know, REIT (Real Es­tate In­vest­ment Trust) is to be a re­al­ity soon; this plat­form has been con­cep­tu­al­ized to pro­tect re­tail in­vestors and of­fer them an op­por­tu­nity to own a piece of In­dia’s most suc­cess­ful an­nu­ity in­come-based as­sets. This also be­comes a com­pelling rea­son to cre­ate ro­bust sys­tems to en­sure ac­cu­rate and trans­par­ent data.

This com­fort and trust be­ing built with both in­sti­tu­tional and re­tail in­vestors will only come with process-driven man­age­ment and an in-depth data an­a­lyt­i­cal ap­proach to man­ag­ing as­sets. This is where real-time data an­a­lyt­ics plays an ex­tremely piv­otal role, espe­cially in the shop­ping mall busi­ness.

As we are all aware, re­tail busi­ness is grow­ing to be a pre­dom­i­nantly part­ner­ship ap­proach rather than that of a lessor-lessee one, wherein it is in the de­vel­op­ers’ in­ter­est to en­sure that the re­tailer trades well within their shop­ping mall. The de­vel­op­ers, in turn, en­joy the up­side of ‘turnover rent’ or ‘rev­enue shar­ing’ that has a proven track record. To en­sure that all ad­di­tional in­cen­tivized in­comes are mea­sured, col­lated, and an­a­lyzed ac­cu­rately, data man­age­ment be­comes an ex­tremely crit­i­cal part of own­ing an an­nu­ity-based in­come as­set.

REIT has been con­cep­tu­al­ized to pro­tect re­tail in­vestors and of­fer them an op­por­tu­nity to own a piece of In­dia’s most suc­cess­ful an­nu­ity in­come-based as­sets.

data: the back­bone

With a high num­ber of con­sumers walk­ing into a shop­ping mall, thou­sands of em­ploy­ees, hun­dreds of crores be­ing traded amongst all ten­ants and var­i­ous units of op­er­a­tional con­sump­tion, one thing you can be as­sured of is the fact you are sit­ting on price­less data, wait­ing to be tapped into. This can be ei­ther rel­e­gated to archives or uti­lized well.

In today’s ‘light­ning-speed ex­pec­ta­tions’, data is the back­bone to any con­sumer-driven prod­uct. Shop­ping malls are a clas­sic ex­am­ple; dif­fer­ent forms of data are avail­able, through var­i­ous modes such as:

■ Foot­falls

Two- and four-wheeler counts or turn­arounds in a day Re­tail cat­e­gory sales

Util­ity units con­sump­tion

Op­er­a­tional mon­i­tor­ing

Other in­come gen­er­a­tors

Exit sur­veys (RSI and CSI) Cross-plat­form mar­ket­ing (OHH and On­line)

With a plethora of ac­tiv­i­ties to track comes the mil­lion­dol­lar ques­tion—how best to make use of the in­for­ma­tion avail­able?

The smart way is to cap­ture rel­e­vant data, and cre­ate dash­boards that en­able quick ac­tion on the way for­ward, to­wards the key ob­jec­tives and vi­sion of the busi­ness. For ex­am­ple, data on con­sump­tion at the cen­ter seen against that cor­re­spond­ing to the same month the pre­vi­ous year helps in an­a­lyz­ing growth in in­come.

If the num­ber of foot­falls has gone down and con­sump­tion in­creased, it means the per per­son spend has gone up and the cen­ter has qual­ity cus­tomers. The foot­falls and sales pat­tern of var­i­ous re­tail­ers in­di­cate which scheme, cat­e­gory, or event has worked in a par­tic­u­lar month. The num­ber of two- and four-wheel­ers on a daily, weekly, and monthly ba­sis help an­a­lyze the trend of park­ing con­sump­tion and re­quire­ments.

The ones men­tioned above and other in­for­ma­tion aid well-in­formed de­ci­sions and rec­ti­fi­ca­tions on the go, which in turn help to keep a track on the cen­ter growth year on year.

In today’s ‘light­ningspeed ex­pec­ta­tions’, data is the back­bone to any con­sumer­driven prod­uct.

big­gest chal­lenge

With ex­po­sure to the on­line boom in the last cou­ple of years, the bricks and mor­tar op­er­a­tor has learnt that get­ting to know the cus­tomers’ be­hav­ioral pat­tern is the key to en­gag­ing them within the shop­ping mall. One thing on­line play­ers have is data, and they know how to use it best. What off­line play­ers have is an op­por­tu­nity to cre­ate valu­able ex­pe­ri­ences and the vi­sion to adapt data early enough, to fight the war be­tween two com­pelling plat­forms. The world­wide trend seems to be a well-de­vel­oped com­bi­na­tion of both of­fered to the end cus­tomer be­cause as al­ways ‘cus­tomer is king’.

Cap­tur­ing data is a big con­cern ow­ing to the lack of req­ui­site in­fra­struc­ture, which is mostly the case in In­dia— it has ei­ther not been de­signed up­front or the need for cre­at­ing it not un­der­stood. The in­fra­struc­ture in­cludes both hard­ware and soft­ware:


High-speed fi­bre op­tic net­work WiFi based bea­cons

Foot­fall coun­ters

Car park­ing man­age­ment sys­tems Smart me­ter­ing sys­tems

Smart hand­helds (tab’s or smart­phones) Video con­fer­enc­ing fa­cil­i­ties Bio­met­rics sys­tems

RFID ac­cess points Heat-map­ping cam­eras


Au­to­mated Daily Sales Re­port soft­ware (ADSR) Exit survey mod­ules (CSI / RSI)

Ten­ant fit-out mod­ules

Op­er­a­tional snag­ging plat­form

Fi­nan­cial mod­ules

HRIS mod­ules

Loy­alty pro­grams

Car park­ing man­age­ment

Food court man­age­ment En­ter­tain­ment man­age­ment

In­ven­tory man­age­ment (stores, kiosks and SOH) Gam­ing and en­ter­tain­ment plat­form Omni-chan­nel re­tail­ing

All of these are ei­ther time con­sum­ing or in­vest­ment in­ten­sive, and have al­ways been a bar­rier for the de­vel­oper. It is not too far away, when these will be­come the cri­te­ria for any in­ter­na­tional brand or in­sti­tu­tional in­vestor to eval­u­ate new op­por­tu­ni­ties in the an­nu­ity in­come-based as­set class.

Over and above these bar­ri­ers, there are also is­sues re­gard­ing col­lat­ing in­for­ma­tion from the di­rect source, as they are ei­ther frag­mented or con­fi­den­tial. Re­tail­ers, who are the big­gest source for data tap­ping, are fairly open with their data as long as it is re­stricted to sales. Op­er­a­tional data is cap­tured through var­i­ous plat­forms and is close to ac­cu­rate, but quite frag­mented and la­bor in­ten­sive. The real chal­lenge is posed by the con­sumers be­cause only 30-40% of the data can be tapped and the rest are guessti­mates. Within In­dia, dif­fer­ent re­gions have dif­fer­ent be­hav­ioral pat­terns which makes it more dif­fi­cult to make pre­dic­tions.

About a year ago, there was re­sis­tance from op­er­a­tional teams to shift from Ex­cel or man­ual spread­sheets to soft­ware-based sys­tems, but the ap­proach is slowly chang­ing. The ben­e­fits of a tech­nol­ogy-en­abled sys­tem any day wins over the mun­dane way of work­ing and re­port­ing.

the big change

So far, au­to­ma­tion has been lim­ited to fa­cil­i­ties in any as­set wherein the up­keep and func­tion­ing of var­i­ous equip­ment are be­ing mon­i­tored by soft­ware-en­abled sys­tems. This seems to be a ba­sic req­ui­site now, and the need is to have

The bricks and mor­tar op­er­a­tor has learnt that get­ting to know the cus­tomers’ be­hav­ioral pat­tern is the key to en­gag­ing them within the shop­ping mall.

real-time in­tel­li­gence at your fin­ger­tips which serves as a live win­dow to the as­sets per­for­mance. Over the last five years, Prop­erty Zone (PPZ) has been de­vel­op­ing in-house tools to en­able man­ag­ing our malls across the coun­try. Some of these plat­forms are built in house and some in col­lab­o­ra­tion with the finest in the world. Some of the prod­ucts al­ready in the mar­ket in­clude PASCAL, PPZ’s in-house de­vel­oped plat­form that of­fers re­tailer data­base, shop­ping mall data­base, exit sur­veys, fi­nan­cial bud­get­ing, car park man­age­ment, op­er­a­tional mon­i­tor­ing, and loy­alty pro­grams. In­ven­tory man­age­ment, food court and en­ter­tain­ment man­age­ment, omni-chan­nel re­tail­ing, and heat-map­ping anal­y­sis are among those be­ing in­tro­duced in the next six months.

The two most tan­gi­ble ef­fects of soft­ware adop­tion have been ef­fi­ciency en­hance­ment and ac­cu­racy. The num­ber of peo­ple re­quired for man­age­ment of tasks has gone down con­sid­er­ably. User ac­cep­tance and change of mind­set take man­age­ment to the next level where the teams are hands on with in­for­ma­tion.

Re­duc­tion of man­ual in­ter­ven­tion in main­tain­ing data leads to re­duc­ing the risk of er­rors. Var­i­ous re­ports are avail­able on smart­phones with real-time ac­cess to data and there is no de­pen­dence on peo­ple.

data is ‘king’

Data an­a­lyt­ics in the re­tail real es­tate seg­ment in In­dia is at a nascent stage and all the stake­hold­ers are striv­ing to cre­ate bet­ter ex­pe­ri­en­tial spa­ces for their end users. This in­dus­try has learnt the im­por­tance and use of data that is ex­trap­o­lated cor­rectly, and new av­enues are be­ing ex­plored to fur­ther mon­e­tize this. Data with­out an­a­lyt­ics is mean­ing­less, but we are yet to see how the bricks and mor­tar seg­ment de­liver their stake­hold­ers the best val­ued re­turn us­ing data an­a­lyt­ics. ■

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