A lot of data is generated in the Kenyan economy every day. With trailblazing platforms such as M-Pesa, which has disrupted financial services and access to money, the volume of data we are looking at is immense. All businesses in one way or the other are constantly churning new data.
For businesses that are data-driven, such data has been stored in clouds, servers and data warehouses and has been extracted from systems on a high-level basis to determine change in strategy or for control purposes to ensure businesses are hitting set targets.
With the new era of data code-named “Big Data”, the way businesses are looking at data and extracting insights from it has drastically evolved. No longer will businesses rely on the traditional approach of shooting from the hip decision making. Now, more than ever, they will be required to use an evidence-based approach. In the words of Jim Barksdale, former Netscape CEO, “If we have data, let’s look at data. If all we have are opinions, let’s go with mine.”
As we move into this exciting new space, much like its cousin Blockchain which gave rise to the notorious cryptocurrency craze, Big Data will need some demystifying going forward. This article seeks to outline some key areas around Big Data and analytics.
CLEAR OBJECTIVES: As with any project, organisations setting up Big Data solutions need to be clear on what business needs Big Data and analytics are going to solve. Many organisations might be tempted, in a bid to oust their competition and get to market ahead of them, to create capacity and Big Data solutions without really understanding what problem it is going to solve. At the onset, many organisations who go about it with no set objectives may suffer losses due to the risky nature of such undertakings.
CHANGE MANAGEMENT: From the onset, many organisations will grapple with whether existing infrastructure and linkages will be suited to capture and more importantly relay insights arising from Big Data in good time to allow for decision making. Some organisations may be lucky enough to have compatible systems and data environments and as such will be able to create value faster. Companies can also programme Big Data applications with existing languages such as SQL.
Big Data is going to change the dynamics of how most departments in organisations will relate. Think of it as the missing piece of the jigsaw puzzle. Perhaps one of the biggest advantages that will accrue to businesses which adopt Big Data and analytics would be predictive analytics. Gaining deeper insights on customer tastes and preferences coupled with predicting demand more accurately is undoubtedly every business’ headache.
Reducing the expectations gap and gaining a deeper understanding of consumer needs will lead to segmentation of consumers and thus produce goods/services that accurately meet consumer needs. The result is increased sales revenues, reduced costs and an impressive bottom-line for businesses.
INVESTMENT DECISION: Boardroom conversations with the C-suite will always ask the return on investment (ROI) question. Will the company’s investment in Big Data and analytics have a positive return? The answer to this question is beyond a shadow of a doubt a resounding yes! Ability to predict demand more accurately, more flexibility on the pricing continuum and even predictive maintenance just to mention a few, has a direct impact on the bottom-line. The issue on ROI does not lie on whether Big Data and analytics are necessary but on how companies will go about the entire process. A data strategy is important to ensure money and time is not lost in creating systems that will not result in a positive ROI.
PRIVACY: Big Data, as the name suggests, uses data to come up with new insights for companies. A lot of this data is consumer/customer data. Some of this information may be private and confidential and governed by certain laws. Particularly, the EU General Data Protection Regulation (GDPR), that came into effect on May 25, 2018, and locally the Data Protection Bill 2018 are enforceable.
Any company storing customer information will be required to seek consent before collecting, processing or storing personal data. The purpose for collecting the data also needs to be clear and for how long it will be stored. Customers will also have the right to be ‘forgotten’ on demand by being permanently deleted from the database.
HUMAN CAPITAL: Investment in highly skilled personnel is inevitable. Data scientists, data analysts and many other occupations within the data field within the country are few and may not possess all the necessary skills to be able to harness the power of Big Data and analytics. Companies will need to reskill their current personnel who handle data and hire more talent.
Also, proper job descriptions need to be developed to capture the scope of work to avoid any confusion of roles. New positions will emerge such as chief data officers, which will change the power dynamics in organisations. Remuneration would need to match industry standards, and benchmarking with companies abroad might be necessary. The value-add of this new personnel is not to be taken lightly.
In conclusion, Big Data and analytics are a game changer and will need many businesses to make open and candid decisions on how they will compete in this ever-changing and dynamic market. When it is all said and done, in the words of Mike Schmoker, “Things get done only if the data we gather can inform and inspire those in a position to make [a] difference.”