"By: Ibrahim Kholilul Rohman[1] , Moinul Islam Zaber [2]   Inflation is one of the most important anchor indicators particularly in the emerging economies where bundle of consumption is predominantly foods. Consequently, increasing price might directly oppress those in the lower-income bracket forcing them to tighten their belts and crimp spending on other consumption resulting a slower economic growth. The recent release of Badan Pusat Statitik (BPS) seems to reflect a steady inflation rate in Indonesia. We experienced a low inflation rate of 0.66% in March 2022 (month-to-month), after a deflation of 0.02% a month prior.  The core inflation measured without taking food and energy consumption into account was recorded even lower at 0.30% in March 2022-an almost constant rate compared to February 2022 at 0.31%. The reality check might be somewhat different. Thanks to price apps such as Indomaret and Segari, we can observe approximate increases of prices in some commodities during February-March, for instance sugar (about Rp 1.500/kg), bread (Rp 1000/pack), flour (Rp 1000/kg), eggs (Rp 3000/10 eggs), and chicken (Rp 3.000/kg). These are adding to the infamous increase of cooking oil and cooking gas prices. The blue gas has increased three times just in two months in from Rp 160.000 to Rp 180.000 and eventually reaches Rp 200.000 per 12 kg, whereas Bimoli cooking oil hikes up from Rp 27.000 to Rp 47.000/2 liters. Is there any bottleneck in the calculation? Why do the official statistics report a steadier price than what we might observe in the market? To recall, inflation rate is measured based on the change in the Consumer price index (CPI) over time. It indicates of the overall cost of goods and services purchased by a society to portray the changes in the cost of living. Gregory Mankiw in Principle of Economics divides five steps to calculate inflation. The statistic authority needs to firstly determine the basket of goods being calculated to best mimic the overall cost of living standard. The basket might be different across regions. For example, some regions might be weighted-up with a greater volume of rice whereas others with flour. Once the basket has been decided, the basket cost is calculated by multiplying the price and quantity to obtain the total spending of consumption. The authority then decides the base year to calculate the inflation rate as the percentage change in the CPI over the years using the same determined base year. The challenges might concern with the selection of basket index. There are commonly two indexes being used: the Laspeyres and Paasche Indexes. In principle, both methods aim at picturing the ratio of spending in the current year compared with the base year. The main difference lies on the quantities being used: the Laspeyres index uses the quantity in the base year, whereas the Paasche index uses quantities in the current period. BPS adopts the Modified-Laspayres method to portray the price index. With this approach, authority might prioritize to monitor solely price without necessarily paying attention about the availability of stock. It means whether the quantity of goods is available at a particular price level is not being observed. To illustrate; the government has introduced a price intervention of cooking oil about Rp 14.000/liter in March before abolishing the intervention. However, the quantity has been extremely limited at that price. People are queuing for  it or to buy at a more expensive price level elsewhere than the price intervention. Nonetheless, implying the Lespeyres method, official statistics will only report the intervened price at Rp 14.000 in the basket expenses whereas the quantity is set fixed based on the living survey held during some years prior. Consequently, while theoretically Lespeyres index tends to overstate the inflation, in Indonesia the opposite could happen. The index might understate the inflation as the administrative price fails to reflect the real market price for people at large. This problem is not specific for Indonesia but also in other countries using indexation to measure inflation. With the advent of computational power, new machine learning and data scientific mechanisms, it is possible to complement the traditional process by optimizing automatically generated quantity and price data via any point of sales (POS). These include data gathered from supermarkets or any e-commerce transaction via gadgets such as iPad, mobile phones or computers at home. This information is processed through big data containing massive volume of both structured and unstructured information so that voids concerning real-time quantity and price can be better tackled Some initiatives are already introduced to mitigate these challenges by international organization and central statistics.  UN ESCAPs statistic division has been arguing in favour of using these alternative sources to be included in official statistics for long time which due to the pandemic became more prominent.  In the US, the Bureau of Labour statistics have been working with alternative data sources such as using retail seller’s data which is more timely and cost saving. In Japan, Abe and Shinozaki on their study in 2018  have shown that alternative data of commodity prices from various comparison websites may give a higher accuracy than that of the traditional survey. Some developing countries have also introduced this initiative to take up. Bank of Armenia had started their Big Data initiative in 2016 to complement the survey data for more accurate information. A robust information about inflation is crucial especially for a developing country to allow a better remedy and to prevent further severity. The IFG Progress study details that inflation might be transitory or persistent requiring correct measures. Either way, it brings potential impacts on the labor market developments and economic growth. As what a famous management guru Peter Drucker once said, “If you can't measure it, you can't manage it.” It is the best timing to incorporate big data technology to help measuring inflation. Note: This article published by The Jakarta Post on April 18th, 2022. [1] Senior Research Associate IFG Progress and Lecturer of Digital Economics- FEBUI [2] Researcher at United Nations University on Policy Driven Electronic Governance (UNU-EGOV), Portugal"