Developing a Data Science Strategy for Organizations

1. DevelopingaDataScienceStrategyfor Organizations Strategyplaysacrucialroleinanybusiness.So,whentheorganizationsentered theBigDataspace, adatasciencestrategywasrequiredtohelpthemmake insightfuldecisions. Butwhatisdatasciencestrategy?Andwhyisitindispensableinthepresent world?Let’sunderstand! DataScienceStrategy:Definition, Importance forPresent-dayEnterprises! In simple words, the Data Science Strategy puts an organization to contemplate on thebusinessgrowthwithinformeddecision-making,hence creatingademand within the organization to invest in data science. The data science strategy will include areas like overall data science objectives, and strategic choices, regulatory strategies, and the data needs of the organization. It also includes data architecture, skillsetsandcompetences,notforgettingthemechanismtomeasuretheresults. With the definition or the concept of data science strategy clear, let’s understand why data science strategy has gained so much prominence in the current business world. Over the years, data science has become one of the most important part of the day- to-day processes of the business. Reason: Swift adoption of disruptive technologies thatenabledorganizationstoboosttheiragilityandgrowth. Data is the new black and organizations that have aced the data game are able to makewell-thoughtdecisionsandgainintelligentinsights aswell.Various organizations have different methods to use and optimize the available data to take better decisions. And this is what industry experts refer as data science strategy. To understandtheimportanceofdatasciencestrategyitisimportanttounderstand howitwillhelporganizationsdrivegrowthandstayclosetotheirclients. How OrganizationsUseDataTheirDatatoDriveDataScienceStrategy? To understand how organization usetheir datalet’s have a lookat the report released byDeloitte.According tothereport ‘DigitalTransformationthrough

2. data,’ it was revealed that while most of the well-to-do organizations use their data to drive innovation across both business as well as revenue strategies, there are still huge number of organizations, which are struggling with their data.Reason:Lack of knowledge to give more prominence to the data investment as compared to other pressingneeds ofbusiness.Basedon thereport,Deloitte hascategorized organizationintofourstagesofdatasciencestrategyjourney– • Nascent: Organizations that are in their first stages of data science journey are said to be in nascent stage. These organizations collect the data, but data scienceisnotthetopprioritywiththemanagement. • Developing:Organizationsthathavereapedsomebenefitswithdata implementation but are still struggling to use updated technologies and tools. Thesetypesoforganizations are knowntobe indevelopingstage. • Mature:Businessesthathaveunderstoodthevalue of databut arenot making decisions based on the data available to them are said to be in the maturestage.Mostoftheorganizationscomeunderthiscategory–where the importance is given to data-driven decision-making tools, but when it comestodecisionmaking,thetopmanagementstilldependsongutfeeling or othertraditionalmethodtodrivetheirbusiness. • Leading: Organizations which not only understand the importance of data sciencestrategybutalsotakedata-drivendecisionscomeunderthis category. These are the organizations that don’t shy away from growth- minded culture. Result: A culture that encourages and boosts ever-growing innovation and research. There are by far organizations that come under this category. • Oncetheorganizationshaveunderstoodwheretheystandintheirdatascience strategyitisimportantforthemtounderstandbenefitsofdata sciencestrategy. • AdvantagesofData ScienceStrategyImplementation • Therearethreemajorbenefitsofimplyingdatasciencetechnologysuccessfully andseetheresultsforyourself. So, whatarethoseadvantages,let’shavea look. • YouwillbeabletoPredictYourCustomers’Needsandwillbeabletoserve them bettertimeandagain. • YouwillbeabletoRetainYourClientsBetterwiththerightdatascience strategy.

3. Right data science strategy will help youIdentify Your Target Audienceand make advertisementsthattargetthem. • Withbenefitsclear, areyouwonderinghow canorganizationdevelop adata science strategy?Well, keep reading to know how you can develop a good data science strategy. • HowtoDevelopData Science Strategy? • In order to develop an effective data science strategy, the first and foremost thing organizationneedtodoisto– • Identifytheirbusinessgoals.Aclearlyarticulatedgoalwillhelpin developingrightandeffectivedatasciencestrategy. • Nextstepintheprocessistofindtherightdatasciencetalentakaresources whoknowdatascience. • Onceallthesestepshavebeencompleteditisnowtimetodevelopdata science strategy. • Inordertodevelopadatasciencestrategy,itisimportanttodefinethegoals and collect relevant data around it. The goal should be measurable as well as sustainable. • There are fivemainactions organizationscan take to developdata science strategy. • Associatingwiththebusinesstofindoutwheredatasciencecanhelp. • Your next step should be to first identify the existing talent within the organization and upskill them on the latest tools and technologies. Data ScienceCertificationsisoneofthebestwaytoupskillthecurrenttalent inyourorganization. • Once that is done you can also hire new or fresh talent to add fresh perspective tothedata science strategy. • Thisiswhereyoubuildadatascienceteam–afirststeptowardcreating a datasciencestrategy. • After all this hiring is done it is time for data analyst to analyze the gathereddatatomakeinsightfuldecisions.

4. Developing a data science strategy is crucial for businesses that want to stay ahead ofthecompetition.Itisimperativefororganizationstounderstandthevalueof data and what a right data science strategy can do for their businesses in relation to better customersupport,bettermarketreach, andhappyandsatisfiedclients.