Blogs home Featured Image

Mango’s ‘Meet-Up’ at Big Data London on 22nd September features guest speaker Adam Hughes, Data Scientist for The Bank of England, whose remit involves working with incredibly rich datasets, feeding into strategic decision-making on monetary policy. You can read about Adam’s incredibly interesting data remit and his team’s journey through Covid-19, in this short Q&A.

Can you tell us about your interest in data and your role at Bank of England?

Working at the Bank it’s hard not to be interested in data! So much of what we do as an organisation is data driven, with access to some incredibly rich datasets enabling interesting analysis. In Advanced Analytics, we leverage a variety of data science skills to support policy-making and facilitate the effective use of big, complex and granular data sets. As a data scientist, I get involved in all of this, working across the data science workflow.

What’s the inspiration for your talk  – effectively data science at speed?

As with so much recently – Covid. With how fast things have been moving and changing, traditional data sources that policymakers were relying on weren’t being updated fast enough to reflect the situation.

Can you tell us about your data team’s journey through covid-19 and the impact it has had?

In a recent survey, the Bank of England sought to understand how Covid has affected the adoption and use of ML and DS across UK Banks. Half of the banks surveyed reported an increase in the importance of ML and DS as a result of the pandemic. Covid created a lot of demand for DS skills and expertise within the Bank of England too. Initially this led to some long hours, but it was motivating and generally rewarding to work on something so clearly important. Working remotely 100% of the time was a challenge at first, but generally the transition away from the office has been remarkably smooth in terms of day-to-day working (though there are still disadvantages due to the lack of face-to-face contact). As outputs have subsequently been developed and shared widely in the organisation, they have been an excellent advert for data science, showing the value it can add. In particular, it’s been great to see the business areas we worked with building up their local data science skills as a consequence.

What’s the talk about and what are the key takeaways?

The talk will cover some of the techniques we used to get, process and use new data sources under time pressure, including what we’ve learnt from the process. The key takeaways are:

  • Non-traditional datasets contain some really useful information – and can form part of the toolkit even in normal times;
  • Building partnerships is key;
  • A suite of useful building blocks, such as helper packages or code adapted from cleverer people helps speed things up;
  • Working fast doesn’t mean worse outcomes.

We look forward to seeing you at Mango’s Big Data London, Meet Up, 22nd September 6-8pm, Olympia ML Ops Theatre. You can sign up here.

Guest speaker, Adam Hughes is one of The Bank of England’s Data Scientists,

successful strategies to navigate your team
Blogs home Featured Image

Having access to the right data, at the right time, and in the right format, in order to inform your business strategy has always been critical in defining commercial success.  But in today’s exceptionally challenging business environment, where market conditions are changing daily (and in some industries, such as oil and gas, hourly), the availability of business-critical data, and the insights derived from it, is the key determinant in ensuring commercial survival.

Truly, we are in uncharted territory for the world economy and there are no precedents to refer to for those businesses trying to navigate a path to survival.  This means that the ability to understand trends to predict outcomes and to measure progress – through data management and analysis – is essential for senior executives to make the right decisions about the direction of their businesses.

In short, never has data science been more important – and having immediate, short and long term data strategies in place will help create the agility required for long term commercial success.

Here are five key data initiatives to focus on during this period:

1. Management Information (MI)

i) If your MI is based on retrospective data that was extrapolated manually through Excel wrangling and presented in a way that is not relevant to the situation because of a time lag, or worse possible errors and therefore counter intuitive, then it will be ignored versus

ii) having the right (MI) and metrics.  You can’t make good decisions without good data, so get your data & analytic teams focused on rethinking your MI suite, injecting forward-looking insight, and ensure it is automated

2. Business scenario simulation

The only thing that is certain right now is that nothing is certain. And if nothing is certain, then scenario planning can help and asking the right questions will be key to success:  what would happen if this situation lasts 3 months?  Or 6 months?  Or 9 months?  What happens if the ‘new normal’ is more, or less suited to your business?  Analytic teams can help you simulate and understand the impact of different scenarios on your business so you can better plan for the future.

3. Prepare for success

How do you ideally plan for your escape velocity to ensure you are in the best position to succeed post Covid-19?  For example, how do you best behave to regain and retain your clients if you’ve recently undergone significant churn?  Data science can help you plan the best approach and strategy to optimise the outcome commercially.

4. Data-driven transformation

A positive side effect of Covid-19 in the business world is that the situation will serve as the catalyst needed to accelerate digital transformation for many organisations, and thus reducing the time to becoming data-driven.  Are you prepared for this change?  If not, you may find the competitive landscape in the ‘new normal’ has shifted, with technology enabling other companies to make better, data-driven decisions and reduce costs. Could you compete with that?  Now is the time to focus on your transformation strategy to prepare you for life post-Covid.

5. Data & Analytic Literacy

Part of becoming data-driven is changing the culture within your organisation to make data-driven decision-making part of the DNA, rather than something that comes ‘from the top’ and trickles down, possibly getting lost on the way. Now is the time to teach your workforce the language of data & analytics, so you can devolve more decision making and give people the skills to thrive in the new data-driven future.  Upskilling, buddying and mentoring schemes can all help with this.

Now is perhaps the right time to make decisions using your data. The Covid-19 situation has become a numbers story on all levels, and it’s the data behind those numbers that is driving many Government, business and personal decisions.  We know from watching the news how regularly those numbers change, and the same will apply to your business.  Remember, agility is the new currency for business and putting effective data strategies into place now will help you emerge on the other side of this as healthy as you were when you went in.

Author Rich Pugh, Chief Data Scientist

Related content

Blog: Future Proofing your Data Science Team