In April 2014, a United Nations (UN) supported initiative in Myanmar led to the country’s first census in 30 years. The authorities used 160,000 pencils to capture 41 complex questions across its estimated 60 million population. When the results came in, the census suggested that the country’s population was 15% less than previously estimated. Was the data accurate? If not, where were the mistakes? Should their social programme change be based on the new information? Should they do another exercise? There were no easy answers to these questions. A grand initiative with immense social impact was made significantly less potent due to non-use of technology-led data collection and digital techniques. Yet, in another part of the world in the same year, Germany used cutting-edge big data techniques by mapping the strengths of its best football players with those of their competitors—thereby creating a powerful advantage which experts say was the team’s secret weapon in winning the Football World Cup in Brazil. How we capture, curate and leverage data today is becoming the crucial difference between winning and losing. The world will soon be divided between organizations that have and know how to utilize their data and those who do not. But, in stories like the above, what is important to a business leader is to identify the levers that would help your organizations put objectivity over sensationalism. In my experience, it would be good to have a mix of the five things listed below for the success of a data analytics programme. Mobilizing a great team Powerful data analytics teams require the three elements of method, meaning and madness. A combination of technology, data science and business skills (method) is necessary; one without the other is less useful. The data analytics programme canvas needs to be far-reaching while the goals need to be a series of short-term goals that are tangible (meaning). Finally, the secret sauce would be teams that are inquisitive, creative, agile and hungry. The data and analytics jungle is filled with roadblocks and dead ends. To discover true sights on a regular basis, a dash of madness is essential. Identifying the problem As they say, “If you have six hours to fell a tree, spend four hours in sharpening the saw.” Staying with the problem and looking at it from various frames to uncover opportunities that data can validate or discover is key. For instance, Amazon Prime has been a resounding success. It is perhaps the world’s largest loyalty programme with 80 million subscribers, who actually pay $99 to be a part of the programme, and it has no points system. If one were to use the frame of transaction costs, Prime would make no business sense: unlimited free delivery and unlimited free returns would increase transaction costs significantly and make it financially unviable. But if one takes the frame of customer lifetime value, it makes a lot of sense. Prime members spend nearly 80% more than non-Prime members in a given year. Also, if one takes the frame of reducing transaction friction to change behaviour and induce more online purchases, Prime makes amazing sense. The Prime programme has grown 38% over the previous year. Data and analytics would always close the gap, and provide options and alternatives, making scenario planning more effective. However, the problem needs to be looked at from multiple dimensions. Getting the right data While there is no doubt there is a huge explosion of data, the gap between collected data and useful data is huge. For many firms, the manner in which data has historically been collected is fraught with errors of omission and commission. Hence, the sins of the past have to be paid for: there is no alternative to getting the data corrected. But most organizations think that their data is better than it actually is. Any company that does not mark substantial resources towards the cleansing and enhancing of data will find its investment lagging on real results. To ensure that there are no inaccuracies in data obtained, it is important we check the data is correct and structured in a way that’s usable. Be meticulous with the data on hand, ensuring everything is factually correct before processing it. Looking for partners to collaborate A typical urban user spends 11 hours a day online. We are creating digital and data footprints at a humongous level. However, this footprint is spread across organizations, platforms, countries, languages, and other boundaries. Smart businesses are going to realize the value of sharing data across their value chain, to enhance the quality of their information and the value of their insights. For instance, by mashing up its data with that of a bank in the same region, a telecom company would create richer information from which to derive insights. Furthermore, the enterprise architecture and the systems need to be ready to inter-connect and leverage the buying and sharing of data sets. For Full Story, Please click here. Share this:The post Five things CEOs must know before investing in analytics appeared first on Statii News. from http://news.statii.co.uk/five-things-ceos-must-know-before-investing-in-analytics/
0 Comments
Leave a Reply. |
About Us
Lates News about computer, businesss softwares and much more. Archives
December 2018
Categories |