Algospark Vision Solutions

Algospark image compliance solutions for advertising and labels – helping marketing, legal teams and content agencies. Are you manually compiling and completing tedious check lists at the end of your content creation process?

Increase compliance consistency, reduce costs and ensure your campaigns and labels are on track. Get in touch to discuss how Algospark Vision Solutions can be tailored to help you!


https://algospark.com/vision_solutions

Contact:
info@algospark.com

Next Generation Analytics for Finance Professionals

Are you using Excel sheets stored on shared drives for your reports? Do you forecast based on last year or last month with a x% change? Moving to better ways of managing data and forecasts does not have to be difficult. Algospark works with finance professionals and analytics teams to help them evolve from processes that are “painful, manual and reactive” to “easy, automated and proactive”.

What is “next generation analytics”? The evolution phases for next generation analytics are:

  1. Reporting: what happened to x?
  2. Interactive dashboarding: what impact did y and z have on x?
  3. Predictive analytics: what is going to happen to x?
  4. Prescriptive analytics: what should we do about the prediction for x?
  5. Feedback loops / system learning: did we follow the recommended action, and what was the outcome?

Most organisations are somewhere between reporting and interactive dashboarding. We help define development plans that suit the capabilities, trajectory and budget of an organisation.

So, why bother anyway? The benefits:

  • Consistent data
  • More accurate forecasting
  • Faster time to decision
  • Reduction in analytics time
  • Better insights and increased value add from your analytics team
  • Prescriptive analytics and feedback loops mean that the analytics teams work much more closely with other parts of the organisation to help drive change and improvement.

Excel spreadsheets can get the job done, but not in the most efficient way. The same way that you can use scissors to cut the lawn.

Typical reasons for not changing:

  • We are familiar with Excel. (But new ways of working are similar and much more productive and resilient.)
  • New systems are expensive. (Not really true, a well scoped data architecture and new ways of working will nearly always generate an attractive business case.)
  • The team are too busy. (They are usually working on painful and manual processes, which can be removed by a more efficient way of working with data.)
  • No-one in the team can do this. (Evolving data skills with the support of specialists will make analytics more interesting, increase engagement and deliver more value to the business.)

We always advocate defining a future state and then evolving. “Big bang” introduction for analytics is rarely successful. We find building and evolving a success story in part of an organisation is an excellent way to start the journey and evolution path to next generation analytics.

Still not convinced? Common inefficiencies that we encounter:

  • Lots of similar reports answering similar or related questions
  • Ad-hoc requests and manual workarounds
  • Managing, updating and error checking Excel based “master spreadsheets”
  • Cut and pasting charts and tables into presentations

We have worked with large and small companies, across numerous sectors at varying degrees of data and applied AI maturity. Core Insights (https://algospark.com/core_insights) is how we help accelerate the evolution to next generation analytics.

Core Insights review areas:

  • Existing reporting within the context of key performance indicators and alignment with key business processes
  • Forecasting and recommendations
  • Data storage, data architecture, data processing and reporting
  • Use of technology
  • Team skills (data processing, analytics and data science)

From this we develop a prioritised reporting roadmap and technology path that we can help your team deliver. We are experts in applied analytics and AI. Get in touch now to discuss how we can help you transition to next generation analytics!

info@algospark.com

The Art and Science of New Site Selection

Finding new sites and executing a growth strategy in retail and hospitality is not simple. Good site selection involves reviewing multiple sites and prioritising which sites are likely to be the best performers. Property teams need to compare lots of sites using multiple factors in a consistent manner.  Do you really want to make property selections based on your “best guess”?

With access to some data sources, it is possible to do this yourself. But ranking and prioritising sites can take substantial analysis time and management review time.  With so many factors to consider and modelling options it can be quite a challenge.

  • Existing sites and relevant operating metrics.
  • Choice and span of location data variables.
  • Sourcing, quality and preparation of data.
  • Correlation among variables and the number of variables to include.
  • Location catchment size and footfall considerations.
  • Choice of model(s).
  • Time periods, seasonal impact and pandemic impact.
  • Validation and testing considerations.
  • Point in time sales forecasts and predicted weekly trading patterns.

A model that can accurately prioritise and predict sales at the next 5-10 locations is very valuable, especially if capital expenditure is limited or you are raising new capital. Moreover, you may have come across an opportunity for a great rental deal and want to predict sales and evaluate profitability in a consistent way.

A data driven approach is an excellent foundation, but the final location decision always involves the human touch.  This qualitative validation includes a wide range of factors such as site lay out, parking restrictions, competitor price lists, strange odours and other nuances. This is where property specialists and management teams really shine – the art of making the final forecast adjustment and investment decision.

Algospark is a specialist in delivering AI solutions for new site selection. Find out more about how we helped Gail’s Bakery expand from 35 to 80+ sites.

We believe that understanding key considerations for data collection, data selection, modelling, validation and visualisation is also an art – the art of successful data science.

Algospark becomes Microsoft Power BI Solutions Partner

We are proud to announce that we have been upgraded from a Power BI Partner to a Power BI Solutions Partner. Algospark are able to demonstrate the strength and depth of skills and solutions using Power BI to consistently produce quality insightful dashboards.

Microsoft Power BI is at the heart of our Core Insights service that helps clients get more from their data.

Power BI dashboards are not just about reporting and exploration, they are also an excellent way to present and manage outputs from applied AI projects.

Get in touch so that we can help you get more out of your data, and help you accelerate innovation and process efficiency initiatives using applied AI.

Applied AI: what board members should know and be asking:

Darren Wilkinson presented a webinar to the In Touch Network about applied AI and what they should know and be asking.

Darren’s career extends over 20+ years specialising in strategy, corporate finance, technology and quantitative analytics. This webinar explores artificial intelligence, the key drivers and approach, how to implement AI, how to scope opportunities within a business, questions for your board and an interactive Q&A session.

In the words of an attendee, “Thanks to Darren for the presentation. To be perfectly honest I thought I had an idea what AI was about. I quickly discovered my perception was wrong. For me he explained it in a simple, unjargonised manner which highlighted the benefits – nothing sinister, just a better way to source and use data.”

Link to the recording: https://www.brighttalk.com/webcast/14157/532663

Algospark Microsoft Gold and Cyber Secure

Algospark are proud to renew our Microsoft Gold Data Analytics & Data Platform credentials. We have also re-certified for Cyber Essentials, developed by the UK National Cyber Security Centre. Get in touch so that we can help you get the most out of your data and analytics.

Helping Hospitality Grow

Looking to expand to new sites?

Finding the right sites time consuming and difficult? Gail’s Bakery are executing their expansion strategy using AI and analytics. We have helped them grow from 35-80 sites in a short time frame, with more sites to come.

“Data analytics has transformed the way we do new site selection. Our partnership with Algospark over the last 3 years has been an important element to our successful expansion.” Tom Molnar Co-founder and CEO Bread Holding Ltd.

Read more here: https://algospark.com/gails_locationspark/

Remove the Complex from Image Compliance

Did you know that there are 415 rules that apply to UK advertising? Some are conditional to specific industries. Ensuring your ads meet all rules is complex. We can help. Our Vision UK AI software (currently in beta) will review your image compliance. We think it’s so good we want to share it. Get in touch for a free trial.

https://algospark.com/vision_uk/

info@algospark-com

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Accelerate Innovation with Applied AI

Artificial intelligence brings together the best of data, maths and technology. AI is a key driver for strategic innovation. What better way to deliver process efficiencies and new opportunity discovery? At Algospark, we use “workflow mapping discovery” that allows us to pin-point exactly where organisations are likely to get most benefit from applied AI. We take the “AI Use Case Grid” below and tailor to specific industries so that we recommend the most appropriate and highest value-adding opportunities.

Our clients benefit from an extensive catalogue of existing frameworks and tools to help them fast track innovation projects using applied AI. Recent frameworks development include:

  • Retail and hospitality solutions (site selection and operational efficiency)
  • Vision solutions targeting compliance in advertising and labels
  • Proactive customer management
  • Dynamic pricing for fixed inventory (travel and hotels)
  • Machine reading to help discover and prioritise key findings.

More examples and more information on frameworks can be found here.

Innovation projects spanning opportunity identification and process efficiency will be key themes for development in 2022. Get in touch to discuss how we can help you.

Free Trial of Vision UK: Advertising Standards Rules Checker

Do you want to save time and money on image review for advertising in the UK? Do you work in legal, marketing or an ad agency? Algospark has beta launched Vision UK, a tool for UK advertising image compliance. We are looking for companies to help refine the product ahead of launch later this year.

Please get in touch to get free access. info@algospark.com

https://algospark.com/vision_uk

#ai #visionai #computervision #advertising #uk #compliance #legal #marketing

Happy 2022! Algospark frameworks for fast track AI implementation in the New Year

Happy New Year! We are driving forward in 2022 with a strong set of applied AI frameworks to help clients fast track delivery of applied AI solutions.

Hospitality: Location Spark (new site selection tool) and Retail Cube (coordinated forecasting framework for operational excellence).

Image compliance: we have significantly developed our computer vision frameworks during 2021. These now support fast track development for image compliance and label compliance solutions.

Customer experience: proactive customer management framework (rather than typical reactive customer service) and our “Xuuu” customer insights framework.

Inventory management: next generation tools for yield optimisation that support airlines, hotel chains and other businesses with services for sale at given points in time.

Machine reading: frameworks that deliver document summarisation, reading prioritisation and comparison. These have been developed for the finance and healthcare sectors.

Our wider range of frameworks spans sales, operations and innovation across multiple industries. In addition, we offer applied analytics and bespoke development and implementation services for AI solutions.

Get in touch to discuss how we can help you!

https://algospark.com/#frameworks

Helping the hospitality sector bounce back

The hospitality sector has been once of the hardest hit sectors during the pandemic. We are helping hospitality clients reset, allowing them to get back to growth and more efficient operations.

We do this with two core hospitality sector offerings:

  • Location Spark: site analytics and new site / expansion evaluation tool
  • Retail Cube: integrated sales forecasting, ordering and staffing

These services bring together data and applied AI to make the best informed decisions around site planning and operation.

Location Spark delivers a solid quantitative approach to new site selection, leaving your team more time to focus on location specifics and much less time on data gathering, benchmarking and forecasting.

Retail Cube uses applied AI for sales forecasting. We combine operating data with external data to ensure you have the most realistic baseline sales forecasts. We then link these forecasts to ordering and staffing so that you can optimise resources to deliver your sales forecasts.

Get in touch to discuss how we can use data and applied AI to help your hospitality operations and growth plans.

Algospark Core Insights with Azure and the Power Platform

Algospark Core Insights is a service that designs and deliver dashboards. This means organisations receive key insights quicker and easier. Core Insights consultancy is typically a 4 week engagement that brings together the best of business analytics and visualisation. We define a reporting roadmap and deliver the highest priority dashboards.

Core Insights is an excellent launch pad for enhancing the value of your data and the skills in your analytics team. Many clients also use Core Insights to identify and validate key opportunities for applied AI.

Algospark Azure Core Insights brings together the optimal mix of PowerBI, the Power Platform and Azure Synapse (Azure Data Warehousing).

https://algospark.com/core_insights/

We are a Microsoft AI Global Partner, PowerBI Partner, Gold Data Analytics and Gold Data Platform partner. Microsoft continually develop their data services and applications so that we can deliver even better services too.

Get in touch so that we can help you with Core Insights and your applied AI journey.

https://algospark.com/

Algospark @ Impact Hub

We’re back in the office and have our name on the board at the Impact Hub in Kings Cross! Come and meet us at our new working space in Central London. We would love to discuss how we can help you drive more value from your data, and how we can empower your organization with predictive analytics and applied artificial intelligence solutions.

We are at the Impact Hub King’s Cross, 34b York Way, King’s Cross, London, N1 9AB. United Kingdom.

Algospark Double Gold

Algospark has been awarded another gold level Microsoft competency! We are proud to be Microsoft Gold Partner for Data Analytics and Data Platform.

This gold level competency demonstrates our data skills throughout the applied AI development cycle. Our approach spans analytics, rapid prototyping, delivery and management of production systems. A big congratulations goes to our team of applied AI specialists. https://algospark.com/#who

Get in touch to discuss how we can help you drive value with applied analytics and AI solutions.

info@algospark.com

Super powering your analytics team

Ever thought you could get more of your analytics team? Most businesses rely on the analytics team having a great understanding of how the business generates value. They also assume they generate the best insights using the best data that they have. But are you enabling them with the best tools and processes?

Many organisations are still taking Excel file dumps from SQL databases and then painfully pulling together periodic management reports. Management do not like the time required to prepare reports (reporting lag),  and analysts are frustrated by the process of pulling together reports. This is before we even consider the potential for data errors and data inconsistencies to creep in.  

At Algospark, we use a fast track framework to help super power analysts and reporting systems. Our Core Insights framework helps analysts move from process enablers to insights specialists.

Core Insights is designed to move analytics from reporting to insights. We do this through automated procedures and prioritisation of key impact drivers. Once this framework is in place, analytics teams can move beyond Excel. Your analysts will spend more time on insights. It will also enable them to quickly move into the realm of predictive analytics (what will happen?) and prescriptive analytics (what should I do?).

Our Core Insights service not only focuses on enabling processes and systems, but also the skills and capability of your analysts. We help analysts move beyond Excel to deepen their data skills in SQL, R and Python.

Get in touch! Let us help you super power your analytics team. Contact us at info@algospark.com

Demonstrating data expertise with Microsoft certifications

Microsoft offers a wide range of certifications for many types of technology domains and roles. Earning a Microsoft certification proves your knowledge and proficiency. Microsoft offers three different certification categories: fundamentals (knowledge of a particular domain), role-based and speciality (advanced).

Preparation for exams is through hands-on experience and study with either free Microsoft learning paths or paid instructor-led training. Certification requires passing an exam.

Data certifications

We believe the most useful Microsoft certifications for data and AI professionals are:

  • Azure Data Scientist Associate
  • Azure Data Engineer Associate
  • Data Analyst Associate

We also really like the following for a wider understanding of applied solutions in Azure and the Power Platform:

  • Power Platform App Maker Associate
  • Azure AI Engineer Associate
  • Azure AI Fundamentals
  • Azure Data Fundamentals
  • Power Platform Functional Consultant Associate
  • Azure Administrators

For more information on certifications: https://docs.microsoft.com/en-us/learn/certifications/browse/

Value

When you spend time and energy learning or using a technology, a certification is an excellent way to prove your understanding.

Algospark Microsoft Certifications

Our staff hold numerous Microsoft certifications. This contributes to our status as a Global AI Inner Circle Partner, Power BI Partner and Gold Microsoft Partner.

At Algospark, we apply our data knowledge and expertise to deliver value adding applied analytics and artificial intelligence solutions. Our fast-track implementation means we launch and iterate quickly, saving you time and money. Get in touch for more information! https://algospark.com

Algospark earns Cyber Essentials Certification

Cyber Essentials is UK certification from the National Cyber Security Centre. It defines minimum IT security policies and helps guard organisations against cyber attack. It also demonstrates ongoing commitment to cyber security.

Cyber attacks come in many shapes and sizes, but the vast majority are very basic in nature, carried out by relatively unskilled individuals. They’re the digital equivalent of a thief trying your front door to see if it’s unlocked. Cyber Essentials is designed to prevent these attacks.

Benefits of certification:

  • Reassure customers
  • Attract new business
  • Define parameters of organisation level cyber security
  • Some Government contracts require Cyber Essentials certification

Found out more: https://www.ncsc.gov.uk/

Benefits of a proactive customer management approach

Customer management can be a difficult process if we do not understand why our customers behave the way they do. Why are they leaving us? Is it because they are not satisfied? Could we have anticipated it and take action before it was too late? Moving from a reactive customer management to a proactive customer management strategy can help you identify customers that are likely to stop buying, or customers that are displaying unusual trends.

Making the most of your data by using applied AI we can help you identify key customers and prioritise those your team should focus on, minimising revenue at risk. Simultaneously, our Azure Proactive Customer Management tool also integrates a recommender engine that suggests what products or services your customer is more likely to buy, and consequently increasing revenue opportunities.

Identifying risk

For each customer, we use several AI models to calculate risk probabilities and the potential value at risk. Using data you are already have, such as historical transactions, customer and product details, customer support history, etc. you can take a data-driven proactive customer management approach and take action now, not when it is too late.

Intuitive dashboard

After the AI models have finished computing the predictions, the results are delivered in an easy-to-use dashboard where you will find all the information you need to start reaching out to your key customers, focusing on fixing problems and driving revenue growth.

Is it for me?

If you have a large number of products and / or customers, Azure Proactive Customer Management is for you. Examples include:

  • Manufacturers with hundreds of products and customers.
  • Retailers with in-store and online customers.
  • Hospitality, travel and leisure businesses.
  • Service providers such as telecoms, utilities, insurance and financial services.

Demo

Sounds good? You can access a demo version of the Azure Proactive Customer Management dashboard in the link below:

https://algospark.com/azure_proactive_customer_management/

At Algospark we deliver applied analytics and artificial intelligence solutions focusing on business value. Our fast track approach means we can launch and iterate quickly, saving you money and time. Get in touch for more information!

Forecasting throughout Covid and beyond

Algospark is an applied analytics and artificial intelligence solutions consultancy. Back in 2019, we were not predicting a pandemic, and neither were many others. But this article is not about pandemic predictions, rather how to plan and predict in times of high uncertainty and fundamental change.

The reaction and impact of the current corona virus pandemic has presented huge challenges to society and the economy. During times of fundamental change, businesses still need to plan, forecast and deliver. Fast changing rules with huge economic impact have made for highly uncertain times. We have seen high volatility in economic activity and broken forecasting models across many industries.

However, successful planning and delivery in highly volatile times means data preparation reviews and changes to modelling. We follow these steps:

  • Understand key impact areas
  • Use distinct time periods mapped to specific phases
  • Prepare data with new labels and context
  • Explore new model approaches and review look back periods
  • Review, revise and update models

Organizations that have successfully adapted are outperforming during the pandemic. We have worked with several clients during this period to review and update their applied analytics.

The volatility over the last few months has led to several “data regime” changes that have been defined by changing rules and economic behaviour. The mistake is to interpret data from different regimes as useless. There is significant value in “regime modelling” and the insights that it can generate.

Another mistake is waiting until there is a return to pre-pandemic conditions. We believe there will be a gradual evolution, and that adaptive forecasting and proactive customer management is the best way to respond to evolving conditions.

In addition to making business planning much more difficult, the pandemic has also increased focus and pressure on customer service. For many individuals, the pandemic has meant more free time. Unfortunately this has come at the same time as many customer support teams have moved to new ways of working (remotely), with less head count and higher levels of customer calls. Succeeding in this environment underlines the importance of good planning, predicting and prioritizing. After all, good customer service is routed in anticipation of needs.

We have a portfolio of data science led frameworks to solve the challenges of the pandemic. If you are looking to review a forecasting process, refresh your applied analytics approach or wanting to proactively re-engage with your customers then get in touch!

We are building for pandemic recovery and would love to help you.

darren@algospark.com

Azure Proactive Customer Management

We are proud to launch Algospark Azure Proactive Customer Management. We enable you to move from reactive customer management to proactive customer management. Put more simply, get ahead of customer issues before you are called about them. Get in touch to discuss how we can help you!

Value of proactive customer management:

  • Increased revenue per customer, increased customer satisfaction and reduction in churn.
  • Anticipation – move away from reactively responding to calls to proactively managing calls.
  • Prioritise the order of calls based on value. Identify and minimise customer value at risk.
  • Map insights to action, and align to promotions and pricing policies.
  • Create a virtuous learning loop for insights and successful actions.

Azure Proactive Customer Management builds on: Azure Cloud, Azure Machine Learning, Synapse, Power BI, Power Apps and Power Automate. We also have easy connectors to align with existing activities and processes with Customer Relationship Management (CRM) systems and other customer support applications.

Please get in touch for a full demonstration. We would love to discuss how we can help tailor Azure Proactive Customer Management to meet your specific needs. Contact us at info@algospark.com

Find out more and see a demo here: https://algospark.com/azure_proactive_customer_management/

Algospark becomes Microsoft Gold Partner

Well done to the team! We are proud to demonstrate our competence across Azure solutions to become a Microsoft Gold Partner for Data Analytics. This is in addition to our status of Global AI Inner Circle Partner, Power BI Partner and Silver Partner Microsoft Data Platforms.

Algospark helps clients identify opportunities and fast track value using predictive analytics and applied AI. Get in touch!

Algospark enters UK Government AI Dynamic Purchasing System

The UK Government Dynamic Purchasing System (DPS) Marketplace provides access to all procurement run by Crown Commercial Service. Buyers access framework agreements that meet common purchasing requirements across government.

Benefits for buyers :
● Aligns to government standards and guidelines, including the Data Ethics Framework and the Office for AI’s Guidelines for AI Procurement.
● Promotes standards and criteria for artificial intelligence and data.
● Ethical considerations when innovating and buying artificial intelligence.
● Intellectual Property Rights in the AI market.
● Ensures the appropriate suppliers are accessible to provide the right service offerings, to reduce procurement timescales and ultimately to provide an easier route to market for the type of AI.

Get in touch with us to discuss how we can help deliver applied analytics and artificial intelligence solutions for government.

info@algospark.com

See more here: https://www.crowncommercial.gov.uk/agreements/RM6200

Building on the shoulders of giants: transfer learning in NLP

Transfer learning is a way for data science experiments to build on existing successful models. It has been popular in Computer Vision where open source deep learning models trained on ImageNet are commonly used as a base for training more specialised models. Using the same methodology in NLP (Natural Language Processing) means next generation machine comprehension models do not have to start from a blank canvas.

Open source models for machine comprehension are now widely used as a viable alternative to building new projects without a base model.

Transfer learning usually follows one of three paths. 1) Re-train all weights of an existing model architecture, 2) freeze some layers and train others or 3) freeze the entire architecture and model layers. The easiest starting point is usually the last method, particularly when your training data set is small. The other approaches to transfer learning are typically used as part of later stage model testing and tuning.

BERT (Bidirectional Encoder Representations from Transformers) is a popular model for machine comprehension. Developed by Google AI, it also has several specialised flavours (eg RoBERTa for sentiment). BERT has been trained on a large amount of unlabelled text including Wikipedia and Book Corpus (over 3 billion words). A quick web search will explain how to implement BERT for numerous NLP (Natural Language Processing) tasks such as spam detection or chat bot.

Beyond BERT there are many more open source NLP base models. HuggingFace is particularly active in providing access to libraries and API’s. As they state on their site, “solving NLP, one commit at a time”.

OpenAI‘s model GPT3 (Generative Pre-trained Transformer) is also a popular starting point. It has been trained using 175 billion parameters. The size of such models naturally limit the ability for NLP practioners to import and build, so API’s are the natural interface.

There are numerous approaches to solving NLP challenges. These include, but are not limited to: language used, time periods, technical considerations, size of data sets and general considerations of the use case. However, building on the shoulders of NLP giant models is certainly a good consideration for many use cases in NLP.

Algospark Becomes Microsoft PowerBI Partner and Launches Core Insights Service

We are proud to be a Microsoft Power BI partner.

PowerBI is at the heart of Algospark Core Insights Consultancy. We map, prioritise, design and deliver dashboards so that organisations receive key insights quicker and easier. Core Insights saves time on key report preparation and reduces time from insight to action. It can also identify opportunities for applied AI projects. A simple PowerBI example of model outputs can be found here . Get in touch to discuss how Core Insights can help you.

Algospark AI Use Case Grid

Here is our AI Use Case Grid. We use this to shape early discussions about where AI can drive most value from an organisation. It allows us to explore opportunities, quantify value and develop project prioritisation and roadmaps.

The grid maps to high level organisation processes and then links to core outputs  of AI models to help understand existing organisational capabilities. This allows us to frame potential gaps and determine the value add from applied analytics and AI.

Get in touch to learn how we can help you fast track value from analytics and artificial intelligence.

Using AI to drive growth in asset management

Algospark recently gave a presentation to CEO’s and industry pioneers at the YPO organization about how to fast track benefits from applied artificial intelligence in the asset management sector. We kept use cases broad so that they would be relevant across the asset management industry, i.e. from large retail focused wealth managers through to boutique fund managers.

Here is a summary of the use cases that we covered.

  •  Use Case 1 : Customer and idea clustering
    • Focus area: New sales opportunities,
    • Why: Increase sales funnel size and quality
    • Benefits: Sales increase by x%
  • Use Case 2: AI driven insight – news analytics
    • Improved trading performance
    • Why: Generate insights, focus on the right things at the right time
    • Benefits: Consistent analytics framework and analyst time saving of x%
  • Use Case 3: Outlier detection / compliance monitoring
    • Risk mitigation
    • Why: Spot bad early
    • Benefits: Regulatory compliance, reduce existential threats and compliance review time saving of x%

When evaluating the most effective way to implement AI solutions we nearly always advocate a business transformation approach using micro-services architecture. This ensures good business adoption and reduces time to solution. It also makes sure that the solutions are scaleable and flexible.

  • AI solutions:
    • High value add AI is rarely “off-the-shelf”
    • Needs to be defined by business priorities and impact assessed across: process, roles, data and technology
  • Transformation approach:
    • Define a future state
    • Build a change map, prioritised list of solution requirements, business case and project plan
    • Define and build a rapid working prototype (R, Python, Shiny, Django)
    • Develop the prototype in a sand-box for low early IT dependency
    • Use agile delivery to iteratively deliver every 2 weeks
  • Micro-services architecture:
    • Each service is self-contained and implement a single capability (avoid creating IT “Gordian knots”)
    • Interface across stand alone micro-services using API (Application Programming Interfaces)
    • Use a “pick and mix” approach of micro-services to deliver overall service functionality

Use Case 1 Overview: Customer and Idea Clustering

  • What: clustering customers and ideas to increase sales success and productivity
  • Why: improving sales idea success by x% and reducing overall ideas sales time by y%
  • How:
    • Clustering customers and ideas to prioritise target lists for investment ideas
    • Run through an appropriateness filter for idea / customer suitability (classifier)
    • Use recommender systems to determine probabilities of sales
  • Considerations:
    • Quality of CRM data (customer type, portfolio, objectives, recent activity)
    • CRM data architecture and API
    • Personal data protection using pseudonymisation
    • Data hosting and computation (legislation)
    • In-house data and analytics capabilities vs third party provider

Customer and ideas heatmap / dendrograms:

 

Key considerations for project delivery success:

  • Clear owner
  • Realistic assessment of in-house capabilities and support
  • Speed to insight considerations, not everything needs to be real-time
  • Process and focus of roles will need to change to realise benefits
  • Good data is good solutions: the impact of data governance, data architecture and maintenance
  • Data security
  • Regulatory regimes
  • Flexible technology (transition to API driven micro-services)

If you are interested in learning more about this use case, the other use cases, or successful approaches to AI implementation, please do not hesitate to get in touch.

Algospark: applied analytics and artificial intelligence solutions.

 

 

 

Federated learning: using personal data without seeing the data

Federated learning is a form of distributed model training where data remains on client devices. This means data is not passed directly to the coordinating server. By implication, models learn (ie train) using personal data sets without actually seeing the underlying data. Currently there are limited results from federated learning using models actually in production. However, in a world of GDPR and increased data protection legislation overall, this model training methodology is likely to receive much more attention in the world of AI and machine learning.

See an example of federated learning approach with R and Tensorflow at the link below.

R Blog Tensorflow Federated Learning

Algospark becomes Microsoft Silver Partner for Data Analytics

We are proud to demonstrate our competence across Azure machine learning solutions and become a Microsoft Silver Partner for Data Analytics. Algospark is a predictive analytics and applied Artificial Intelligence (AI) specialist. We help clients identify opportunities and fast track value from AI. Get in touch!

   

 

Algospark joins Microsoft AI Inner Circle Partners

We are proud to announce that Algospark has joined Microsoft’s AI Inner Circle Partner program. The program includes specialists that are able to provide custom services or enhanced AI product solutions using Microsoft AI technologies.

Algospark works with numerous delivery partners to deliver the best solutions for our clients. We are excited to be working with, and to be recognised as an AI specialist by one of the industry leading companies in AI technology development.

Directory of Microsoft AI Partners

Legal Week Innovation Through Technology Finalist

Congratulations to the visionary Legal Team at Pernod Ricard Global Travel Retail for their “highly commended” award at the British Legal Awards 2019! Algospark are proud to have designed and delivered the enabling AI technology and service.

The “AI Approve Tool” reviews advertising image compliance with laws and corporate standards. It delivers multiple rule checks across multiple countries to generate an approve, refer or reject decision. This ensures decision consistency and  significantly faster process time.

The web based solution brings together a suite of translation, natural language processing, computer vision and classification algorithms. It has been built to scale using a micro-services design with containers to facilitate a fast production ready AI service.

Well done to all involved!

https://www.event.law.com/legalweek-british-legal-awards/winners

State of AI in the UK

As part of the launch of “Future Decoded 2019”, Microsoft UK have released this report, Accelerating Competitive Advantage with AI.  It contains tips on successful approaches to applied AI, survey results from UK enterprises and use cases. It also reiterates key messages that we use at Algospark:

  • AI is beyond data, it is part of a business transformation process.
  • AI is key to competitive advantage.
  • AI needs change management to ensure success.

Happy reading! Get in touch with us to discuss how we can help you accelerate innovation using applied AI!

 

Fast Track AI Solutions

There has never been a better time to explore new innovation opportunities using analytics and applied AI solutions! How do you get started? At Algospark we use a portfolio of existing solutions and fast prototyping to minimise time to solution discovery. It is OK to aim for 80% of the solution. It can be iterated later. If you’ve launched at 99% accuracy, you’ve launched too late.

Another method to accelerate the time to solution is to develop in a sand pit. These are also called innovation spaces, test beds or labs. It means using an environment that does not need to fully integrate with existing IT systems from the beginning. Using prototypes in these environments helps quickly migrate to full solutions further down the road.

We also use a modular approach, also called a “micro-services perspective”, when we build solutions. This means that each component in the solution is added with minimal dependency on other components. It makes the solution much more flexible and easier to align with other systems and processes later in the development cycle.

The development methodology should be agile and iterative. It should also have a DevOps perspective, ie quick to update and deploy, and easy to manage. It should also have a DataOps perspective. This is a set of processes used to improve quality and reduce the cycle time of data analytics.

Throughout the solution building process it is critical to ensure end user adoption. This is where applied data science meets business transformation. New process and services always need to be in context of user adoption. They also need to be developed within a strong  business transformation and change management framework.

Contact Algospark! We have a portfolio of solutions, frameworks and existing products that minimise development risk. We use tried and tested methods of quickly realising value. Speak with us about how we can help you.

info@algospark.com

 

Data Innovation: shortage of specialist skills and competencies to ask the right questions and spot the opportunities

Excellent summary in report from CBI and Nexus University of Leeds: “Changing nature of R&D: building an innovation ecosystem for the data age”.

“A significant constraint facing firms looking to grow their analytics
capabilities is their ability to acquire the right talent. After identifying what talent and skills are needed, businesses are then finding
that these skills are in short supply.”

“With demand outstripping supply, individual businesses are faced with the challenge of how to attract highly sought-after talent. In many cases, although the skills being sought after are highly specialised, often they are sector agnostic. As a result, firms across sectors are fishing in the same pool for talent.”

“In a competitive market where analytics skills can command high salaries, companies struggle to compete with the world’s leading digital companies. Companies whose brands aren’t known for providing exciting opportunities for employees to use their data and analytical skills find it hard to reach their target audience. ”

Speak with us at Algospark to discuss how we can help fast track your innovation initiatives using applied analytics and artificial intelligence solutions.

 

Fun in the Playground

Why write a blog about how to build a neural net classifier when you can visualize how it works in the awesome Tensorflow Playground? See the link to start playing.

https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle&regDataset=reg-plane&learningRate=0.03&regularizationRate=0&noise=0&networkShape=4,2&seed=0.70210&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false

Value from Verbatim

Want to reduce complaints, focus on customer priorities and reduce churn? You can do this by using Natural Language Processing (NLP) and customer profiling. We convert text to metrics, and then to emotions. This helps quantify what is important, and then allows tracking of impact to ensure the best reactions to customer feedback.

There is no point listening if there is no action! Algospark build tailored frameworks for feedback that track, aggregate and map insights. Verbatim feedback quantification is a key foundation to building strong customer relations. See a basic example here

https://wilkinsondi.shinyapps.io/verbatim_insights/

Get in touch to discuss how this can help you improve your monitoring and response to the voice of the customer.

Premier League AI

Football is predictable?

We are predicting that Arsenal win the Arsenal v Chelsea fixture this weekend. We use an ensemble of three AI models to predict home, draw or win results. Our models use player data, manager data and 5 year historic fixtures data to determine most likely outcomes.

https://algospark.shinyapps.io/premierleague/

We calculate match outcome probabilities, decimal odds implied from these probabilities and how the predictions performed last week. The matches are ranked in order of confidence of the prediction (from high to low).

Don’t hesitate to get in touch to discuss further. info@algospark.com

DISCLAIMER: These predictions are guidelines only, Algospark takes no responsbility for the accuracy of information or any losses incurred resulting from decisions are actions taken using these predictions.

AI Innovation Hubs – Bridging the Gap Between Opportunity and Action

Data is everywhere, the insights are exciting and it can power the next generation of systems investment. This is the accepted wisdom, but how do you get started? Unless you work in a technology led business, IT teams rarely lead business innovation, yet they are typically the key gatekeeper to unlocking the power of organizational data. The evolution of IT to cloud, dev-ops, micro-services and containers should be keeping the IT team busy. This is even before considering master data, data lakes, governance and moving away from traditional Extract Transfer Load (ETL) procedures.

Exploiting new revenue opportunities and cost savings from data needs to be driven using a business transformation lens. The priorities and needs of the business balanced against speed and risks of implementation are critical success factors for any data science initiative. This is difficult for most people to conceptualize and is why rapid prototyping in “AI Innovation Hubs” is an excellent way to demonstrate concepts and likely benefits. Seeing the results of a prototype along a business case and agile implementation plan is excellent way to rally key stakeholders to further develop and launch the initiative. This should be done outside existing IT and data architecture, but mapped into how it can be “productionized” as part of the plan.

AI Innovation Hubs are key to kick starting new and exciting applied data science projects. Working within the confines of existing data insight normally means working within processes and parameters of existing IT. So it is much better to work outside existing frameworks, but co-developed with data insight teams in the AI Innovation Hub. This ensures:

  • Innovative new projects help uplift and augment current procedures.
  • Upskill priorities are easily identified and implemented with exciting hands on  training initiatives for analysts.
  • Learnings from prototypes can drive incremental changes to wider data engineering and approaches to ELT.

Overall, these benefits will lead to wider organisation efficiencies from faster access to more relevant data using less processing time and less analyst time. This ultimately results in significantly raising efficacy from insight, and substantially lowering costs.

Want to get started with an Innovation Hub? Get in touch!

https://algospark.com

Crime Predictor

Looking to take your cycle to work? Buying a new house? Worried about your walk to work? Take a look at the Algospark crime predictor that pulls together the crime data patterns from the last 3 years in the UK to predict crime hot spots.

https://algospark.shinyapps.io/crime_predictor

Algospark Crime Predictor has been designed to predict crime by type and by postcode sector using AI. Not only does it help with better crime prevention planning, it also feeds investment decision frameworks to improve outcomes regarding new properties and new business locations.

 

New Radical Empiricism

The new age of computing and data has unleashed a whole new approach to scientific discovery. I was lucky enough to spend a few hours at CogX18 and listen to Zavain Dar (https://twitter.com/zavaindar) at Lux Capital explain how thinkers of old can move away from the basis of ground truths towards a data driven relationship, free interpretation of how things link together. There is no need to understand the ground truths, nor the myriad of supporting hypotheses and assumptions in order to prove a concept. It is now possible to apply cognition beyond human understanding to map input X to outcome Y using machine learning / deep learning / cognitive computing.

Pick an historic scientific legend, eg Newton. Imagine the steps, process, ground truth understanding and empirical proofs required to explain gravity! Now imagine taking readings, mapping to outcomes and feeding the results into a deep learning model. With enough iterations, the core concepts and relationships will be implicitly mapped.

In medicine, for example in the field of dermatology, applied machine learning is already yielding diagnoses that are better than those obtained from human specialists. This is saving lives and reducing the amount of specialist input for critical diagnoses.

New radical empiricism is here! It’s real and can be applied to a wide range of fields. However, it is especially relevant with use cases in which ground truths are notoriously difficult to prove. Healthcare and complex system outcome prediction are perfect. This also implies that economics and investment management with their myriad of nested assumptions are also front and centre of the new radical empiricism wave.

Algospark are developing predictive analytics solutions across equity investment, retail location investment and complex systems prediction. These are front and centre for applied new radical empiricism. NRE is nascent, but a great concept and one that will receive increasing focus in coming months and years.

 

Crime Pays!

Algospark has just released Crime Explorer which is an interactive crime exploration tool for the UK. Developed for use on desktops, it is a visualisation tool that shows reported crime data by type and location across the UK during 2017.

Knowing and understanding crime patterns is invaluable for location analytics and to support investment decisions into new areas and locations. Data used by Crime Explorer is from data.police.uk and categorized by month, location and type of crime. The data is rich and can be quickly interpreted and compliments the suite of predictive analytics tools of Location Spark.

https://algospark.shinyapps.io/crime_explorer/

Crime data + location analytics = value.

Map Explorer for Location Analytics

Map Explorer is a free visualisation tool for UK wide views of key location metrics.

https://algospark.shinyapps.io/mapexplorer/

The demo version includes data on demography, house prices and concentration of eateries. It is an interactive tool that provides data at the national level and pop-up data at the postcode level across the UK. It has been developed for use on larger screens and for presenting snapshots to compliment wider location analytics projects.

Map Explorer is a great compliment to Location Spark which is a mobile centric, sales pattern prediction tool for any given postcode.

https://algospark.com/locationspark/

Data in the demo version of Map Explorer:

  • Demographics, classifications by postcode based on ONS Census Open Area Classification.
  • House Prices, adjusted average transaction price HM Land Registry Price Paid Data
  • Eateries, count of restaurants, food outlets, coffee shops and bars. Based on adjusted OpenStreetMap data.

Enjoy the exploration, and get in touch for more information on sources, methodology and customisation requirements.

https://algospark.shinyapps.io/mapexplorer/

https://algospark.com

Launching Location Spark

Location Spark is a new service from Algospark. Location Spark provides location analytics for investment decisions in new retail sites. It is a flexible framework that has been co-developed with fast growing UK retail networks. Location Spark brings together a multitude of location data sources, operational metrics and artificial intelligence to predict sales, the type of store and trading patterns.

Key benefits:

  • Reduced analysis time (20-40%).
  • Increased speed to decision using robust and repeatable process.
  • Increased forecasting accuracy and minimised probability of poor new site selection.
  • Rapid automated site evaluation at low cost with great “return on analytics”.

Read more about Location Spark here: https://algospark.com/locationspark/index.html

Try the demo: https://algospark.shinyapps.io/locationspark

Proactive Account Management with Churn Prediction & Recommenders

Proactive account management means that events and opportunities are predicted so that customer engagement and service offerings can be optimised.

When implementing a proactive approach, questions your account management team should be considering:

  • Which accounts are most likely to leave?
  • Which customers have a very high probability of buying additional products?
  • What products should I recommend to potential leavers?

It’s worth remembering that all the problems do not need answering at once. It is not necessary to launch a programme with large investment project teams, CRM and IT infrastructure. At Algospark, we generate insights from data and then develop rapid prototypes to fast track value from artificial intelligence solutions.

How does this approach work with the proactive account management questions?

  • Which customers are most likely to leave? This link shows an example of a churn management solution uses a Value at Risk (VaR) approach to prioritise client contact.
  • Which customers have a very high probability of buying additional products? This link shows an example of customer centric product recommendation. It uses a hybrid collaborative filtering approach to determine the products with the highest chance of purchase.
  • What products should I recommend to potential leavers? The solutions above can be combined so that customer management teams have a script that is highly personalised to the client in terms of behaviour and preferences.

The links above and other sales, product and process solutions can be found here: https://algospark.com/#sales

Getting proactive does not need to be difficult! Get in touch to discuss further.

 

Deep Neural Nets and Amazing New Image Generation

Deep learning networks are infamous for their ability to detect cats in images. Advances in computer vision and the application of Convolutional Neural Networks (CNN’s) have yielded exciting advances in image classification and computer vision applications. CNN’s are used to classify images and identify the objects that are in them. They essentially translate pixels values to information about what is in the image. There are often many layers between pixel values and outcomes. The layers in these networks can be used to determine the style of an image. Early layers tend to identify lines or colours, whereas later layers identify more complex objects and derivations.

Combining data that has been generated from 2 images that have passed through CNN’s allows a principal content image to be mixed with style from another image. Content and style are weighted, and the algorithm iterates through numerous passes of the images to align the images. The style of an image is derived from comparing convolutional channels filters and the correlation between them to produce gram matrices. Further details on the approach and specification can be found here.

We have been experimenting with various content images and style images over the 2017 holiday period. Although the commercial value of such image generation is difficult to quantify (as with traditional art), the neural style transfer approach allows AI to generate amazing new vivid images by combining a “content” image and a “style” image. We have posted various examples to the Algospark Neural Style Transfer Art gallery. These can be found here:

https://algospark.com/algoart/

The implication is that an already large image library of content and style can be combined using AI to generate exciting new computer art derived art libraries.

Great service without the exploding product list

How can you offer great service without an exploding product list? Meeting an increasing number of customer needs from a growing list of customers can lead to exponential growth in product offerings. Do you really want to be the one stop shop for everybody for everything?

Most organisations follow the 80:20 product rule. This means that 80% of customers buy 20% of the product offerings. Products that are not in the top 20% make up part of the “product long tail”. Whenever there is an efficiency drive, these products typically appear in the cost saving table of a PowerPoint presentation. But these products have been developed to meet customer requirements, and are nearly always part of a portfolio of products that customers buy. How can product investment or divestment opportunities be made for specific products without jeopardising customer relationships? How should the product tail be cut? Or more importantly, what new products should I recommend to customers? The answer is learn from supermarkets and shopping baskets.

Market basket analytics and product graph analytics are excellent ways to determine “hero products” and the dependencies with other products. These type of analytics measure products by their support (% of transactions in which the product appears), confidence (probability of buying product X if you also buy  product Y) and lift (strength of product inter-relationships). Product portfolio dashboards are an excellent way to visualise these metrics. They allow fast understanding of key product relationships that make it easy to determine core product clusters and the most important product associations. This can then be linked to evaluation of product financials (ie sell products that make money) and development of recommender systems (suggest products that customers want).

So using a product portfolio analytics tool will help keep product development in line with demand patterns. It also helps guide customers to more consistent product portfolios without “exploding” the product list.

See an example of an Algospark product portfolio dashboard here: https://wilkinsondi.shinyapps.io/newproddev/

This forms part of a suite of optimisation tools for sales, product and process. Further details are here: https://algospark.com/#sales

Blogging, scraping, Google Analytics and traffic impact

Do you write a blog? How does it fit with your marketing and content strategy? How does your blog impact new traffic that visits your site? OK, enough questions. At Algospark, we were interested in a fast prototype to assess web traffic and how the blog is driving interest. We pulled together blog scraping, Google Analytics, predictive analytics and rapid dashboard prototyping to assess what is going on with the Algospark blog. As usual data, analytics and prediction are at the core of our interest. Having a better understanding of our content mix and traffic impact should help improve this blog. Read more about the concept here: https:\\algospark.com\#ideation

This is a simplistic first step, but gives great insight into the content mix and how it drives traffic. The application is predicting an 8% uplift in traffic over the next 4 weeks from this article. You can see how the impact evolves, our traffic dynamics and the updated forecast here.

Here’s to our evolving and improving blog posts!