Want to improve your image review process and make your content creation more cost effective? If you work in content design, content management, marketing or legal our new Image Review Engine is for you.
Image Review Engine builds on Algospark’s success in delivering advertising image and label compliance tools. It is a flexible, bespoke AI image review and compliance framework that is offered as as an API that links to content management systems. The service helps organisations check images for rules compliance and generate image meta tags. This means image checks can be performed throughout an image workflow which stops bad early and saves downstream checking processes and rework.
We work with clients to develop rules and image checks they need to serve their needs. Our existing library of rules covers a wide range of industries with a deep library of rules and capabilities. We have already developed hundreds of rules spanning food, drink and health.
Slow reaction to price changes mean that margins suffer. Do you rely on feedback from sales and procurement to identify performance outliers? Are you using Excel sheets on shared drives for your reports? Do you forecast based on last period with a x% change? Moving to more efficient 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”.
Fast changing prices mean that you may be selling at low prices and / or paying higher prices for cost of goods sold. Both lead to operating margin compression. Identifying price impacts and outliers early means being able to react early and better manage profitability.
How does “next generation analytics” help? Most basic reporting gives a backward looking answer to where a business has been. Next generation analytics and applied AI moves the perspective to “what will happen and what should we do”.
Evolution phases to next generation analytics:
Reporting: what happened to x?
Interactive dashboarding: what impact did y and z have on x?
Predictive analytics: what is going to happen to x?
Prescriptive analytics: what should we do about the prediction for x?
Feedback loops / system learning: did we follow the recommended action, and what was the outcome?
We help define development plans that suit the capabilities, trajectory and budget of an organisation. Transitioning to next generation analytics means better insights and increased value add from your analytics team. The team move away from reporting and move towards advising.
Excel spreadsheets can get the job done, but not in the most efficient way. The same way that you can use tissues to clean a car.
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 succeed in volatile price environments using next generation analytics.
Are you a fund or a new acquirer looking to get the most out of a new acquisition? Algospark Deal Support Services can help identify opportunities, value and risks with Data & AI Diligence. We also work with clients post acquisition to accelerate implementation of data & AI roadmaps.
Pre-Deal Services – Data & AI Due Diligence: we identify and quantify data & AI opportunities as part of the due diligence process. This helps understand the value of opportunities and risk from existing use of data & AI. It also allows us to quantify value, prioritise development opportunities and design a roadmap for data and applied AI.
Post-Deal Services – Analytics & AI Enablement: develop and implement a next generation data and applied AI roadmap. We work alongside the management team to agree and build out the roadmap. As part of this, we are also involved in recruiting data specialists and building out internal data capabilities.
We have worked with numerous organisations at various stages of data maturity and have delivered significant value from data and applied AI projects.
Do you work with the hospitality sector? Tired of doom and gloom? Want to plan for great customer experiences and get the most out of your operations?
There is no doubt that cost of living pressures are making customers think twice about spending money. There is also no arguing inflationary pressures on operations. However, this is not the first time we find ourselves in an inflationary environment. When there is volatility in demand and prices, the key to success is focus. This means being informed and making good decisions. It is time to make sure your forecasting and operations are data driven.
Despite the economic back drop, hospitality revenues are generally holding up. There are fewer customers, but customers are spending more. Better demand forecasting and product mix understanding will help better align operations.
Food costs are rising but are they “unpredictable”? No. When prices change faster they can still be forecast. However, models need to become more sophisticated, taking more demand factors and related prices into account.
Labour costs are high! True, but they will not rise exponentially. Better understanding demand and staff requirements will drive better labour productivity. When costs are higher, make sure you are using resources in the best way!
“No-one is expanding in this environment”. Not really true. Fewer operators are expanding, however these are great conditions to secure good deals on new sites. Given the market backdrop, a detailed understanding of what works across different sites will help focus expansion plans on the sites with the highest sales potential.
“You can’t sell a business in this climate”. True that deal volumes are lower and valuation multiples have come off the peaks, but there is always demand for good businesses. A sharp focus on understanding the market, forecasting demand and managing costs will drive value. Any business sale or funding opportunity will always be driven by value.
Algospark is helping the hospitality on numerous fronts:
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!
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:
Reporting: what happened to x?
Interactive dashboarding: what impact did y and z have on x?
Predictive analytics: what is going to happen to x?
Prescriptive analytics: what should we do about the prediction for x?
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!
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.
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.
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.
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.”
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.
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.
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.
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.
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
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.
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 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).
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.
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 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.
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
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:
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
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
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.
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.
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!
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.
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
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!
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.
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.
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.
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.
A good methodology for cloud migration business cases from Microsoft and Forrester. The DBA’s that tell you cloud is more expensive normally do not count themselves as part of the cost savings.
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 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.
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!
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.
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.
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!
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.
“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.
Big thanks to Uber for supporting deck.gl! It facilitates amazing javascript visualisations by bringing together D3 objects, Mapbox, React, GPU rendering and deck layers.
See the link below for a hexagon distribution map of UK eateries built on deck.gl and using Algospark location data.
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.
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
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.
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!
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.
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.
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.
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.
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”.
