ARE YOU AN EARLY ADOPTOR
in your industry?
We work with companies in your industry who are using Robotic process automation (RPA) and Artificial Intelligence aka intelligent automation, to digitally transform their business
If you are new to RPA and ran some Proofs of Concept, or are already involved in automation but want to automate faster and at scale, then we are ready to help
Our industries
Finance
Legal
Utility & Telecom
Healthcare
Government
Manufacturing
Retail & eCom
Supply Chain & Logistics
Financial Services
The banking sector is probably one of the most focused on developing RPA and Ai technology for its own benefit.
The possibilities of gaining a competitive edge through Ai in improvements to speed, time, cost and efficiency and customer needs is driving the growth in these new technologies.
Some examples of these are Chat Bots – automated virtual assistants which are resolving customer queries through online messaging systems and some of these chat bots can undertake over 200 tasks and continue to improve through machine learning.
The use of Bots in trading to quickly identify trading patterns and formulate new trading strategies and management of the vast quantities of customer data financial companies have access to.
Utility
The Utilities industry has wide scope to benefit from RPA and Ai. Some of these uses could include:
Load forecasting
Being able to have advanced knowledge of supply and demand forecast would optimize the economics of load dispatch and machine learning can be used to undertake this.
Yields
Optimising yields Ai can assist power providers with power generation efficiency with real time adjustments which can greatly increase energy production.
Theft
A major issue in developing countries is the theft of energy so Ai can be used to detect usage patterns and abnormal patterns to identify possible theft.
Customers
Knowledge of customers through the use of machine learning would enable utilities to maximise their price and margin options and reduce customer churn.
Legal
With RPA and Ai in the legal sector is beginning to change the legal profession by assisting the work humans do but speeding this up allowing humans to free up time and take on higher level tasks such as advising, negotiating deals and appearing in court.
Some of the time saving can be in document analysis, so machines can review and flag up documents that are relevant to particular cases. They can undertake due diligence, so confirming facts and figures and evaluating decisions and even predict legal outcomes and arguments.
Insurance
AI and RPA in the insurance industry can contribute to change of insurance business model of detect and repair to one of predict and prevent model.
The technology has already begun entering insurance systems and processes, and started to deliver efficiencies, whilst improving customer experience.
Automating claims processing through AI solutions is an example of how time and speed can be reduced
Government
With budgets continuing to get squeezed govern organisations are in need of ways to save costs, increase speed of service as well as enhancing accuracy.
But Ai in manufacturing can be a lot more than shop floor automation as Ai can automate supply chains, just in time deliveries and ordering and help companies to anticipate marketing changes.
Manufacturing
Manufacturing is probably one of the first robotics and AI users that people think of, the car production lines with multiple robotic arms building cars.
But Ai in manufacturing can be a lot more than shop floor automation as Ai can automate supply chains, just in time deliveries and ordering and help companies to anticipate marketing changes.
Some of these could be –
People Keeping Healthy – Technology applications and apps encourage healthier behaviour in individuals and help with the proactive management of a healthy lifestyle. It puts consumers in control of health and well-being.
Making a Diagnosis
Large amounts of data can be quickly unlocked to present medical information from many sources and technology can be combined to build powerful learning algorithms to solve healthcare issues.
Making Decisions
Pattern recognition can identify patients at risk of developing a condition so allowing action to remedy this.
Early Detection
Consumer wearables and other medical devices combined with Ai to recognise early disease signs
Treatment
Ai can be used to manage drug discovery, creation and testing to cut time to market.
Training
Ai can implement training anywhere with the power of Ai included in a smartphone a trainee can undertake training at any time.
Retail and Supply Chain
eCommerce is growing fast, and COVID19 lockdowns havw accelerated this growth. Retailers need to keep up with the online stores and leverage cutting-edge technologies to learn faster and how customer better
SOME CASE STUDIES
UTILITY
RPA CANDIDATE ASSESSMENT, £1m-4M IDENTIFIED
Led automation programme to build business unit wide Automation Catalogue
Situation:
Identify all automation opportunities for the entire business unit in less than 2 week
Actions:
Engaged with over 30 key stakeholders (senior department managers, team leads and subject matter experts)
Liaised with the RPA development team, arranged demonstrations of Blue Prism’s capabilities
Created toolkit to assist sub-teams with collating data which was assessed and prioritised
Outcome:
Led the major automation programme to identify potential savings of £1 m – £4 m
FTE COST avoidance, £300k saved
Synchronising data between legacy systems (large company)
Situation:
Manual move data between two legacy systems, because systems stopped talking to each other
Team manager didn’t have the budget to hire 10 more staff, to cope with the forecasted increase in demand
Overwhelming backlog and increase in SMART meters required an addition 30 FTE+
Actions:
Listed all the teams processes
Collated cycle time and volume data the team had collected over the year (sense checked by timing a sample)
Filtered out only RPS suitable processes (ran a workshop)
Out of the 100 tasks, used a Pareto graph to calculate the few tasks (7) which took up 80% of the team’s time
Ran solution design workshop to re-design certain processes (using 5 Whys, and 5Rs)
Created Process Definition Documents to build the bots
Outcome:
Identified savings over £300k, avoiding the need to hire 60+ new staff
FINANCE
Take on new clients, £30k save
Automating deviations off the happy path (small company)
Situation:
The normal process is automated, missing data created deviations from the ‘happy path
Different missing data created deviations at various points along the process – creating manually work to add missing data
Team manager wanted to allow team to cope with new customers who would invariably provide suboptimal information
Actions:
Map out the process End-to-End and identify the deviation areas
Zoom into areas and compile a list of manual processes
Run root cause workshops to identify the true reason (customers? outside our control? What Influence do we have?)
Filtered out only RPS suitable processes (ran group interviews with manager and SMEs)
Created Process design documents to build the bots
Outcome:
Bots deployed on several manual tasks (assisting multiple teams at once) removing mundane tasks for staff to focus on adding value
Realised benefits and monitored bots to sustain future success
Artificial intelligent automation
ICR + NLP + DATALAKES
Situation:
Team received hundreds of paper forms from Independant Financial Advisors (IFA), which they needed to scan for record-keeping and manually enter data into the CRM system
Actions:
Facilitated the collection of high quality scanned forms which were saved in a datalake
the ICR (intelligent character recognition) engine digested the data and converted both text and handwritten data into standardised information
conditions were set of each field and the engine learnt of the correct type of information. e.g. if the handwriting was read ‘LODNON’ the intelligent engine would know that for a UK address this had an acceptably high probablity of being ‘LONDON’
Outcome:
Bots deployed on several manual tasks (assisting multiple teams at once) removing mundane tasks for staff to focus on adding value
Realised benefits and monitored bots to sustain future success
FUNCTIONAL
Govern and support bots
Manage support team for UiPath, Blue Prism, AA bots for various clients
Situation:
Newly formed RPA support team taking on new client bots in Automation Anywhere, UiPath and Blue Prism for departments in Finance and HR
Actions:
Co-managed a team of 10 robotics engineers supporting digital workers (bots) for several clients in Blue Prism, UiPath or Automation Anywhere
Assisted with: Invoicing, Capacity management, Client relationship management, team Capability management and tracking (working closely with Technical lead to identify skill gaps and carrying out interviews)
Assist in setting up KPI tracking and reporting. Developing processes and controls to ensure consistency and quality of service
Facilitated the build of complexity matrix to assess the complexity of supporting RPA bots and making bot changes
Outcome:
Improved governance and performance tracking
Created a robust process for Release Management of new robots and new changes to existing robots
MANUFACTURING
Price-to-WIN OF £MILLION AND £BILLION GOVERNMENT CONTRACTS
Process improvement to centre manufacturing to assist BOMs and contract analysis
Situation:
Create competitive build of materials (BoMs) for winning £multi-million and £billion tenders
Actions:
Compiled all historical publically available contract data into a central repository
Segmented contract builds into components and estimated component costs
Reverse engineered historical contracts to verify calculations
Uploaded data onto SharePoint to assist business development department
