May 17, 2020

Boosting productivity with a culture of data science

Big Data
Matt Aldridge, co-founder and ...
4 min
Organisations are not maximising the ability of current resources where they could be embracing and harnessing technological change
Since the dawn of time, and accelerated through several industrial revolutions, businesses and individuals have aspired to do more with less resources...

Since the dawn of time, and accelerated through several industrial revolutions, businesses and individuals have aspired to do more with less resources. However, with labour-productivity growth figures at an all-time low, perhaps, for the moment at least, organisations are not maximising the ability of current resources where they could be embracing and harnessing technological change. One of the major ‘resources’ of modern businesses, noted for its value but widely regarded as under-utilised, is data.

Boosting productivity with data is one of the biggest challenges in the modern enterprise, and it all comes down to finding a way to extract and maximise value. In the business world, value is all about achieving the maximum productivity possible. This aligns well with the central purposes of data science, which we at Mango define as “the proactive use of data and advanced analytics to drive better decision making.” That is to say, data scientists take existing data resources, and use these to create “more” using analytical techniques. These can be applied to many use cases, but driving productivity from data often falls into a number of key categories – delivering solutions to business problems, reporting in real-time and using trend data to drive future growth.

The first key of successful data science is that it is using data to solve real business problems. This means increasing integration between data and data science teams by fostering collaboration and creative discussions to help them understand what is needed and what is possible. Clarity of purpose and communication enables better understanding of what is needed, and the resources they need to get there. Meanwhile, the business team will not only be able to explain what they need, how and why, but may also know of department-specific or team-specific data sources which could aid in the creation of a new solution. This allows all teams to work more productively, with data scientists better informed about what the solution is for, and business teams more confident that the solution will work.

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However, data science does not always need to be about creating detailed new solutions out of nowhere. Often, given the wealth of data that businesses hold, data scientists can use historical trend data to drive insights in future activities. This can be external facing (such as optimising strategies for engaging with customers) or internal (such as predicting the impact of different hiring patterns or organisational reshuffles). While historical data cannot offer a perfect answer to how a situation may play out in future, previous patterns can help shape models that at least offer a probable explanation of what might happen next. This helps make more informed decisions quicker and more accurately drive company performance.

Thirdly, data scientists can boost productivity both of their own teams and the organisation as a whole by implementing more real-time analytics solutions. These make use of not only historical data, but also look to proactively generate insights alongside action. While data scientists have traditionally been viewed as part of the strategic pipeline – that is, as providers of insight into weighty, considered decisions – the evolution of real-time analytics and streaming data enables data scientists to provide tools that support in a tactical role at great speed in changing conditions. This can support business productivity “on the fly” – such as when dealing with a customer during a complaints call, or with on-tap insights around successes and challenges with existing data science project implementations.

The benefits of data science for boosting productivity are hard to understate. However,  against the grain of our XaaS technology era, data science is more than just a plug-and-play solution.  The productivity of a data science team itself, and the business as a whole, relies on more than just tools or training or the right resources. Instead, it comes down to creating a culture of data science – and this is something championed from the top down. Harnessing data as a resource, and then finding a way to use it effectively within the work environment requires businesses to build a foundation of curiosity and an acceptance of the possibilities around data. Creating a thriving data science culture will be the difference between a vital productivity boom and a state of data overload.

By Matt Aldridge, co-founder and CEO, Mango Solutions

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Jun 4, 2021

Logi Analytics Webinar: Meet the speaker

LogiAnalytics
Webinar
Data
Technology
2 min
Join Technology Magazine and Logi Analytics for this exclusive webinar as we explore the revolutionary power of next-generation embedded analytics

Data allows business owners to leverage digital insights and embrace the power of data-driven business intelligence to make more informed decisions that are better for business growth and evolution. By using data to drive its actions, an organisation can contextualise and/or personalise its messaging to its prospects and customers for a more customer-centric approach.

BizClik Media Group and Logi Analytics invite you to explore next-gen embedded analytics in our live webinar. There’s still time to sign up for the event entitled ‘Application Imperative: How Next-Gen Embedded Analytics Power Data-Driven Action’, which is taking place on 10 June at 4 pm BST.

The webinar will be led by Constellation Research’s Principal Analyst, Doug Henschen, who focuses on data-driven decision-making. Henschen’s Data-to-Decisions research examines how organisations employ data analysis to reimagine their business models and gain a deeper understanding of their customers.

Henschen's research acknowledges that innovative data analysis applications require a multi-disciplinary approach starting with information and orchestration technologies, continuing through business intelligence, data visualisation, and analytics, and moving into NoSQL and big-data analysis, third-party data enrichment, and decision-management technologies.

Constellation Research is a technology research and advisory firm based in Silicon Valley. Prior to joining Constellation, Doug Henschen led analytics, big data, business intelligence, optimisation, smart applications research, and news coverage at InformationWeek.

What will the webinar cover?

This exclusive webinar will explain next-gen embedding capabilities that will enable your company to:

  • Eliminate unproductive toggling between transactional interfaces and purely analytic dashboards
  • Drive two-way interactions between app features and embedded analytics to drive data-driven action
  • The compounding impact of embedded analytics on your overall ROI
  • Harness analytics as triggers for automated workflows and suggested next-best actions
  • Enable developers to build quickly without coding while customising self-service options for end users

Logi Analytics is the only developer-grade analytics solutions provider focused exclusively on embedding analytics in commercial and enterprise applications, empowering the world’s software teams with the most intuitive data analytics solutions and a team of dedicated professionals invested in your company’s success.

Why not sign up today to find out exactly how Logi Analytics can revolutionise your data analytics game?

We look forward to seeing you there!

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