Privacy Policy

elfware

This Privacy Policy describes Our policies and procedures on the collection, use and disclosure of Your information when You respond to our advertisements and tells You about Your privacy rights and how the law protects You. We use Your Personal Data to contact and support you, as well as to provide and improve the Service. By using the Service, You agree to the collection and use of information in accordance with this Privacy Policy.

Interpretation and Definitions

Interpretation

The words of which the initial letter is capitalized have meanings defined under the following conditions. The following definitions shall have the same meaning regardless of whether they appear in singular or in plural.

Definitions

For the purposes of this Privacy Policy:

• Company (referred to as either "the Company", "We", "Us" or "Our" in this Agreement) refers to elfware.
• Device means any device that can access the Service such as a computer, a cellphone or a digital tablet.
• Personal Data is any information that relates to an identified or identifiable individual.
• Service refers to the advertisement, website, or application.
• Service Provider means any natural or legal person who processes the data on behalf of the Company. It refers to third-party companies or individuals employed by the Company to facilitate the Service, to provide the Service on behalf of the Company, to perform services related to the Service or to assist the Company in analyzing how the Service is used.
• Usage Data refers to data collected automatically, either generated by the use of the Service or from the Service infrastructure itself (for example, the duration of a page visit).
• You means the individual accessing or using the Service, or the company, or other legal entity on behalf of which such individual is accessing or using the Service, as applicable.

Collecting and Using Your Personal Data

Types of Data Collected

Personal Data

While using Our Service, We may ask You to provide Us with certain personally identifiable information that can be used to contact or identify You. Personally identifiable information may include, but is not limited to:

• First name and last name
• Email address
• Phone number
• Location details such as your address, city, or country
• Any other data such as personal preferences, requirements, or comments

Use of Your Personal Data

The Company may use Personal Data for the following purposes:

• To provide and maintain our Service, including to monitor the usage of our Service.
• To manage Your Account: to manage Your registration as a user of the Service. The Personal Data You provide can give You access to different functionalities of the Service that are available to You as a registered user.
• For the performance of a contract: the development, compliance and undertaking of the purchase contract for the products, items or services You have purchased or of any other contract with Us through the Service.
• To contact You: To contact You by email, telephone calls, SMS, or other equivalent forms of electronic communication, such as a mobile application's push notifications regarding updates or informative communications related to the functionalities, products or contracted services, including the security updates, when necessary or reasonable for their implementation.
• To provide You with news, special offers and general information about other goods, services and events which we offer that are similar to those that you have already purchased or enquired about unless You have opted not to receive such information.
• To manage Your requests: To attend and manage Your requests to Us.
• For business transfers: We may use Your information to evaluate or conduct a merger, divestiture, restructuring, reorganization, dissolution, or other sale or transfer of some or all of Our assets, whether as a going concern or as part of bankruptcy, liquidation, or similar proceeding, in which Personal Data held by Us about our Service users is among the assets transferred.
• For other purposes: We may use Your information for other purposes, such as data analysis, identifying usage trends, determining the effectiveness of our promotional campaigns and to evaluate and improve our Service, products, services, marketing and your experience.

We may share Your personal information in the following situations:

• With Service Providers: We may share Your personal information with Service Providers to monitor and analyze the use of our Service, to contact You.
• For business transfers: We may share or transfer Your personal information in connection with, or during negotiations of, any merger, sale of Company assets, financing, or acquisition of all or a portion of Our business to another company.
• With Affiliates: We may share Your information with Our affiliates, in which case we will require those affiliates to honor this Privacy Policy. Affiliates include Our parent company and any other subsidiaries, joint venture partners or other companies that We control or that are under common control with Us.
• With business partners: We may share Your information with Our business partners to offer You certain products, services or promotions.
• With other users: when You share personal information or otherwise interact in the public areas with other users, such information may be viewed by all users and may be publicly distributed outside.
• With Your consent: We may disclose Your personal information for any other purpose with Your consent.

Retention of Your Personal Data

The Company will retain Your Personal Data only for as long as is necessary for the purposes set out in this Privacy Policy. We will retain and use Your Personal Data to the extent necessary to comply with our legal obligations (for example, if we are required to retain your data to comply with applicable laws), resolve disputes, and enforce our legal agreements and policies.

The Company will also retain Usage Data for internal analysis purposes.

Transfer of Your Personal Data

Your information, including Personal Data, is processed at the Company's operating offices and in any other places where the parties involved in the processing are located. It means that this information may be transferred to — and maintained on — computers located outside of Your state, province, country or other governmental jurisdiction where the data protection laws may differ than those from Your jurisdiction.

Your consent to this Privacy Policy followed by Your submission of such information represents Your agreement to that transfer.

The Company will take all steps reasonably necessary to ensure that Your data is treated securely and in accordance with this Privacy Policy and no transfer of Your Personal Data will take place to an organization or a country unless there are adequate controls in place including the security of Your data and other personal information.

Disclosure of Your Personal Data

Law enforcement

Under certain circumstances, the Company may be required to disclose Your Personal Data if required to do so by law or in response to valid requests by public authorities (e.g. a court or a government agency).

Other legal requirements

The Company may disclose Your Personal Data in the good faith belief that such action is necessary to:

• Comply with a legal obligation
• Protect and defend the rights or property of the Company
• Prevent or investigate possible wrongdoing in connection with the Service
• Protect the personal safety of Users of the Service or the public
• Protect against legal liability

Security of Your Personal Data

The security of Your Personal Data is important to Us, but remember that no method of transmission over the Internet, or method of electronic storage is 100% secure. While We strive to use commercially acceptable means to protect Your Personal Data, We cannot guarantee its absolute security.

Links to Other Websites

Our Service may contain links to other websites that are not operated by Us. If You click on a third party link, You will be directed to that third party's site. We strongly advise You to review the Privacy Policy of every site You visit.

We have no control over and assume no responsibility for the content, privacy policies or practices of any third party sites or services.

Changes to this Privacy Policy

We may update Our Privacy Policy from time to time. We will notify You of any changes by posting the new Privacy Policy on this page.

You are advised to review this Privacy Policy periodically for any changes. Changes to this Privacy Policy are effective when they are posted on this page.

This Privacy Policy was last updated on 2024/12/06 00:03:24

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Oracle Retail released their newest patch, Oracle Retail v19.0, in January 2020, marking the first major update to the Retail Merchandising System since v16.0, a touch over 3 years prior. The extensive update begs the question, should a retail organisation migrate to v19?

The answer will differ heavily based on your use of the prior Oracle Retail system. One needs to consider the notable additions and changes prior to making a decision. We’ve gone through and summarized a few of the more significant ones.

Functional Enhancements

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• Oracle listed significant enhancements to Consignment and Concession, including consignment or concession designation and cost management at an item / supplier / country level, and the ability to manage inventory for consignment items.

• 4-6-4 Calendar Support allowing retailers to address the additional week added to the calendar every 7 years.

• Configurable exchange rate dates based on the currency exchange rate in effect on the PO receipt date instead of the rate on the PO itself.

• Multiple enhancements to General Ledger posting and mapping – see documentation in the link at the end of the article for more details.

• Retail for items will always be VAT inclusive when displayed in Merchandising screens going forward, if applicable.

• Support added for the mass reconciliation of transfer and allocation shipments by uploading a spreadsheet.

• Configure bulk upload templates specific to your retailer.

• New system parameters have been added to support disabling the available inventory validation when processing warehouse-sourced transfers created and managed through the external interface, customer orders, and allocations uploaded from an external system.

Technical Enhancements

• Improvements to Stock Ledger and Stock Count Record Management; merchandising now only creates records in the stock ledger or for stock counts where necessary, based on the location’s department or subclass.

• CFAS attributes can now be activated online, rather than through the backend process.

• A new data conversion tool that consumes data files from legacy solutions, loading them into pre-production environment staging tables, then using data integrity checks and business validations to eventually promote converted data to a production environment.

• Greater visibility of files during stock count upload and sales processing.

• Automatic temporary data archive when purging.

• Improvements to Customer Configuration Preservation when patches are applied to merchandising.

So, is it worth migrating to V19?

It’s a difficult question to answer holistically. Really, it’s going to depend on your organisation’s use of the RMS right now, and in the future.

For full documentation and more analysis of new Oracle Retail features in V19, see Trevor North’s article in the Cloud Generators blog here - http://cloudgenerators.com/oracle-retail-v19-is-out/

elfware Automation is an IT company specialising in the use of no code and low code to resolve IT Bottlenecks and reduce Total Costs of Ownership for Oracle Retail clients globally.

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Coding is a notoriously laborious task, so it is no wonder that the emergence of the development concept of no-code and low-code approaches - jointly referred to as "codeless" - has numerous companies excited about the opportunities it poses for agile development. Important to a business’ decision making in this area though, is a comprehensive understanding of the differences between the two, and where they can each have the greatest positive impact.

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Low Code

Low Code refers to a development approach whereby an engineer can use minimal hand-coding while still delivering applications quickly and efficiently. Still not completely understanding? Here’s an analogy from another article I wrote here …

Imagine traditional coding like walking. Sure, you get where you’re going, but it’s going to take a while. Low code development is more like driving. You have a vehicle (typically an LCDP - low-code development platform), and obviously you still need an experienced driver behind the wheel who’s going to help direct the vehicle, but you’re going to get to your destination a hell of a lot quicker.

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No Code 

No Code is similar to low code in a lot of ways, but is really differentiated by the complete lack of coding experience required. Applications can be developed purely based on pre-existing components, meaning that development becomes a logic issue, as opposed to a coding one. This is a key factor that ensures agility within tech teams at elfware.

A No Code application is quintessentially a piece of software that writes other software.The system for no code development is similar to the use of blogging, e-commerce, and other drag and drop website builders.

For a more basic understanding of no code, we can use the analogy previously used in the low code section above. No-code development can be (like low-code development), compared to a car, in that it gets you where you need to go faster. Except this time, there is one, straight road going all the way to the destination. You'll arrive faster, but it leaves very little room for making adjustments during development. A developers adjustments are limited unless they change the original no-code application - almost like changing the road.

Forrester predicts that no-code development platform market will grow from $3.8 billion in 2017 to $21.2 billion in 2022.

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Key Differences

As we’ve just established, the key difference is how much hand-coding is required between the two concepts. The differences certainly don’t stop there, and a team needs to consider many of these distinctions before deciding to use either no code or low code;

• Low Code is capable of developing more complex applications due to greater developer control

• No Code is better suited to apps that require regular updates due to greater agility

• No Code is often used for analytics and reporting where Low Code can be applied to more important, foundational applications

• No Code is often cited as being better suited to citizen developers (non-technical employees who use drag-and-drop software to create applications for others within their organisation, sanctioned by the IT department), whereas low code combines a capacity to develop complex applications with greater agility, making it more useful to organizations and experienced developers

Case Study

Where better to conduct our case study than within our own doors? At elfware, we’re an IT Automation company that uses both low-code and no-code in providing Retail Automation solutions to our clients. On a daily basis, we need to decide which one is more applicable to a project in progress.  

Internally, for each of these development principles, we create a mapping template, which is later adjusted based on logical decisions suited to the project.

The main differentiation point within elfware for these two concepts is that where no-code is fully automated in carrying out its role, low-code rather provides a greater degree of control to an analyst due to opportunities to insert code that can be replicated throughout the system, or it provides a series of ‘macros’ (macroinstructions) that specify a task that an analyst can assign to different areas of the template.

A case study like ours’ shows that a company is capable of utilizing the benefits of both no-code and low-code, significantly reducing requirements for hand-coding and resulting in a logic focused IT team, as opposed to one that’s focused on manual development.

A now heavily discussed topic with regard to innovation and technology, big data has become a focus for some of the world’s largest retailers, proving to be a viable solution to margin pressures and ever-increasing retail competition.

Big data is a relatively broad phrase to describe large data sets that are too large, fast or complex to be processed using traditional methods. But the phrase has come to be synonymous with the field of systematically processing and analyzing the information to reveal patterns and trends, particularly relating to human behaviour.

What is important is what organizations can do with this data, optimizing for cost efficiency and revenue increases in efforts to increase margins. 

While the phrase ‘big data’ was coined in the early 2000’s by industry analyst Doug Laney – who attributed to big data three main attributes, volume, velocity and variety – the field has really hit its stride in conjunction with advancements in machine learning.

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The Role of Big Data in Retail

For the retail industry specifically, Big Data has the capacity to track consumer trends in order to attract new customers and, arguably more importantly, increase the lifetime value of existing customers through targeted offers and loyalty programs.

However, critical to a retailers ability to utilise the benefits is “a robust and methodical way of collecting, managing and interpreting data, then linking that insight to the overarching business strategy,” according to KPMG. With this capacity, a retailer has numerous opportunities.

Targeted Recommendations and Advertising

The extensive analysis of a large consumer dataset allows a retailer to predict what a customer is likely to purchase next. A retailer can study a consumer’s previous purchases, purchases of similar customer segments, how they interact with online stores/apps/social media accounts, and even significant other factors like the weather. Using this data, they can personalise recommendations and advertising to ensure the greatest rate of return on marketing expenditure possible.

Brands like Walgreens and Pantene in the United States partnered with the Weather Channel to anticipate weather patterns and shift marketing strategies accordingly. Seeing a period of high humidity coming, Walgreens began to market anti-frizz products more heavily to women due to the increased demand during these conditions, resulting in a 4% increase in hair product sales over a 2 month period.

Similarly, with regard to the point about studying purchases of similar customer segments, Amazon attributes 29% of sales to their recommendation engine. The engine studies the data sets of 150 million customers to recommend products to customers throughout their website.

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Merchandising and Stock Levels

In a similar manner to targeted recommendations and offers, a retailer can study data extensively to optimize stock variety and the availability/presentation of stock between outlets.

At the most basic level, a retailer can study data down to the day of the week to determine their allocation of stock. By optimizing stock allocation, the retailer can simultaneously avoid lost revenue as a result of a lack of in-demand products and reduce the costs associated with holding stock, such as storage costs (utilities, warehousing etc.) and shrinkage.

Walmart, the world’s largest brick and mortar retailer by both revenue and number of stores, is investing heavily in what will be the world’s largest private cloud system, capable of managing 2.5 petabytes of data an hour. One of the major focuses of the Arkansas based analytics hub analyzing and optimizing stock levels.

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Turning Trends into Revenue

The analysis and response to consumer trends has proved to be a lucrative option for industries globally. A study of the car industry and Tesla’s rapid growth as a result of a growing number of drivers turning to eco-friendly options, provides ample proof of this fact.

The issue then is the reactive stance retailers have often taken; adapting to trends too late and missing out on revenue opportunities. Big Data provides a retailer with the capacity to be proactive with regard to trends. Studying large datasets gathered from social media, forums and existing customers, can reveal growing trends before they really accelerate, unlocking vast revenue opportunities.

The heavily publicized Dollar Shave Club capitalized on the consumer’s increased engagement with subscription boxes for items they would otherwise have to purchase regularly. Combined with a remarkably effective satirical marketing approach, the company has managed to acquire 3.2 million subscribers, including 12,000 customers in its first 24 hours. In 2016 the company was acquired by Unilever for an estimated $1 Billion USD.

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The future of big data in retail

The field of Big Data is still relatively new to the retail sector; but is becoming exponentially more important. The revenue and cost reduction potential of Big Data is growing exponentially, and numerous retailers and startups are running extensive experiments in hopes of utilizing Big Data for new benefits. This is what we can expect to see from Big Data in the future.

Natural Language Processing (Unstructured Data)

Retailers have made significant inroads to the study of unstructured data such as that which comes from social media; however, there is still a way to go.

Natural Language Processing (NLP), is a branch of artificial intelligence with the objective of understanding how humans communicate; from reading to understanding. It becomes remarkably difficult for computers to understand human communication due to numerous abstract tendencies humans undertake in order to pass information. One such issue is sarcasm.

A comprehensive understanding of the human language involves connecting the words spoken/written and associated concepts.

As major developments are made in the area of artificial intelligence, computers may be able to use syntax (how a sentence is structured), and/or semantics (the meaning conveyed by a text), to process natural language. 

This will result in a significant improvement to the capacity for computers to make sense of unstructured data, as previously mentioned, providing more accurate datasets from information-rich environments like social media, linking closely to trend analysis and targeted recommendations.

Machine Learning and Predictive Analytics

One of the most important benefits of the study of large data sets is predictive analytics. Retailers of all sizes already do this – with or without the help of computers – when conducting general tasks like financial planning or stock purchasing. Predictive analytics links directly to the benefits previously established.

However, the future of Big Data holds large potential for predictive analytics to improve its accuracy, predominantly due to the impact of machine learning. The nature of effective machine learning algorithms dictates that they will only become more influential in retail planning, particularly in areas like merchandising. Greater accuracy in predictions will result in more effective optimization for revenue and cost reductions.

Customer Identification

Similar to the use of Machine Learning and Predictive Analytics, in store customer identification has the capacity to enhance how data can be used to drive revenue. Retailers can combine targeted offers and advertising in stores with customer identification to drive in store sales.

The highly publicized Amazon Go concept has drawn attention toward in-store customer identification; using body mapping technology to track dozens of customers and recognising what a customer picks off the shelf and purchases.

If retailers can link this customer identification with existing customer databases they can link online and offline activities, they can increase average customer spend; similar to Amazon’s remarkably successful recommendation engine.  

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Conclusion

McKinsey, in their report 'Big data: The next frontier for innovation, competition, and productivity,' found that, "a retailer using big data to the full could increase its operating margin by more than 60 percent". Therefore, while it is important to consider that Big Data may have limits in terms of its effectiveness, on its current trajectory, it will have numerous benefits in the near future; from highly targeted offers/advertisements to predictive analytics.

Retailers who capitalize on Big Data may be able to stay ahead of competitors, fighting off ever increasing margin pressure by lowering costs and improving revenue. Big Data may soon not become an option for retailers, but rather a necessity.

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What is IT Automation?

Automation in IT involves using software to create repeatable processes that allow a task to be completed without the need for human interaction.

From a business’ perspective, IT automation can involve taking repetitive, manual processes out of the hands of employees, freeing up their time for complicated IT bottlenecks within your organisation, while also reducing error and accelerating delivery across the board.

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“Automation gives the administrator tools to effectively deploy scalable workloads, without a commensurate increase in staff.” - Ned Bellavance, director of cloud solutions at Anexinet.

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As a general rule, the vast majority of IT tasks have some level of applicable automation.

It will likely have the capacity to aid in provisioning, configuration management, application deployment, security and more. In the modern environment, automation proves itself the viable option for dealing with the speed and scale of IT issues that teams are currently managing.

At elfware, we’ve taken on large projects with publicly listed companies across the globe. IT Automation allows us to tackle complex problems quickly and effectively.

Benefits of Automation in IT

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Cost Savings

First and foremost, automation in any context reduces the need for manual labour. Particularly for automation in IT, engineers can be stuck spending needless hours on configuring thousands of similar servers (as an example), manually. A team also runs the risk of human error in this case, having similarly negative impacts on the cost of a project.

Time Savings 

By automating the most repetitive and laborious tasks, a team of engineers frees up a considerable amount of their time. They can rather automate basic, time consuming tasks and focus on higher level, complicated issues, or strategic work (at elfware, it means our engineers can spend more time focusing on improving and adding features to the elfCafé platform, improving our value proposition without hampering productivity). An automated environment has the capacity to reduce delivery time for projects from months to a matter of days.

Reduced Human Error

This was mentioned previously in cost-savings, but still proves one of the biggest benefits of automation. It ensures consistency throughout large projects by taking out the capacity for human error. Once an automation environment has been effectively developed, businesses can focus on complex, higher order tasks without fearing the significant impediment of human error in more repetitive, time-consuming errors.

Efficient Application Deployment 

With Automation, organisations are able to confidently deploy applications at an accelerated speed, configuring necessary services from the outset, while still being transparent and understandable for an entire IT team. This is due to their capacity to systematically progress from commit and build to testing and finally deployment.

System Availability

A priority of IT operations is ensuring system availability. The automation of several tasks; save and recovery systems, system monitoring and remote communication, can significantly reduce downtime and efficiently facilitate incident management.

Challenges of IT Automation

Now, it’s tough to pick out any negatives of Automation in IT, because if done right it can have such prolific positive impacts on the performance of an IT team. But, the key is that it has to be done right. There are certainly numerous issues that can prevent this from happening.

It’s Automated, Not Intelligent

Automation involves establishing a process through which tasks can be repeated and completed effectively without human intervention. But, the automated system is still only capable of doing what a human programmed it to do, it is not intelligent. Therefore, if there is a fault in the original programming at the hands of the engineer, then it may not be able to effectively automate the completion of tasks.

Flexibility Relies on Continued System Updates

Processes evolve over time as technology and IT infrastructure grows and changes. Automated processes can be easily left idle and fall behind the times. IT teams need to ensure the continued monitoring and updating of automation systems so as to ensure its continued relevance.

Automation is a Long Term Game 

Teams can’t expect to be seeing results in the first few weeks of an automation effort. It requires a significant investment in terms of time due to the initial development and a trial and error phase. Rather, over the space of months a team can optimize complicated processes which will result in significant savings and productivity gains in the long term.

The Future of Automation – Machine Learning

IT process automation already provides a team with the capacity to vastly improve productivity and reduce the unnecessary costs of employees’ hours and human error – but the future of automation may have even further positive impacts due to machine learning.

While it’s still early days for machine learning, as our technology gradually advances, we may reach a time where automation software can make decisions that would otherwise be the responsibility of an engineer.

It's hard to predict the benefits, but an automated system that can learn and grow could have numerous positive impacts on the work of an IT team.

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Automation has been at the forefront of the minds of retail executives for years; proving to be both an opportunity and a threat to retailer margins and competitiveness.

Retail margin pressure is ever-mounting due to increasing competition, the meteoric rise of e-commerce, and rising wage demands. Thus, the most successful retailers of the decade have evidently looked to stay ahead by improving customer experience and internal efficiency. Just look at Amazon Go.

Where many retailers have jumped on the self-service checkout trend, Amazon leapt ahead of the automation game with their brick and mortar play; a convenience store that uses computer vision, deep learning algorithms and sensor fusion to completely remove the need for a checkout system, which was rather replaced by the Amazon Go app.

While numerous kinks need to be ironed out, the stores prove the possibility of the complete removal of staff from a brick and mortar store with the help of automation. Combining this with electronic shelf labels, self-checkout terminals, shelf-scanning robots, and partially automated backroom unloading, a physical store can reduce costs by 55%-65% according to McKinsey.

In store automation is on the rise, but will likely soon take a back seat to merchandising automation.

“The winners of the sector will be those who understand [the implications of automation] and act quickly to address them” (McKinsey)

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McKinsey suggests, “automatable activities account for approximately 30 to 40 percent of the time of merchants”. Their extensive report lists numerous opportune areas through which retailers can access the benefits of merchandising automation.

The merchandiser’s role differs between organisations, but for the most part involves the holistic management of product appearance and supply in pursuit of long term sales increases.

Merchandise planning, accounting for roughly 20% of a merchandiser’s time, can be optimised through the automation of extensive historical analytics used to create accurate predictive scenarios that empower faster and better decision making for merchandisers.

In addition, predictive impact analytics have the capacity to significantly increase revenue through targeted and personalized promotions. An Oracle Retail spokesperson explains they have, “seen more than a $75 million increase in revenue at a medium-sized retailer turning over between 500 million and a billion dollars, just by optimizing targeted offers at the point of pickup”. Oracle Retail is often touted as a leading enterprise resource planning solution for realizing the benefits of automation. Other areas within merchandising that strive to widen margins and enhance sales include macro space optimization, inventory allocation and invoice matching.

It's difficult to estimate the value automation will have in merchandising specifically as of yet, but if anything is a surety, it’s that retailers are beginning to realise the possible benefits of merchandising automation, and it is those companies that appear to be forging a new age of retail.

Films and the media like to paint a picture of the committed software engineer who slaves away on a computer till the early hours of the morning in efforts to develop systems. For a long time, that’s what it took to complete projects; talented and committed developers with an extensive understanding of math, digital logic and programming languages. While this is often still true, a sort of saving grace has emerged in the form of the low code movement.

Software systems are becoming more complicated, requiring more and more complex development. As a result, numerous engineers and organisations are considering the benefits of low code. But few of us really understand what it is.

That’s probably because companies will try to overcomplicate the concept, telling you things like: “low code is a development movement where time-consuming manual processes are automated, without hand-coding, using a visual IDE environment, an automation that connects to backends and some kind of application lifestyle management system” *

Really, low code just refers to any case in which an engineer uses a system to generate code, meaning that they don’t have to do it all manually, low-ering the amount of hand-coding required.

They say Rome wasn’t built in a day, but what if software could be?

Let’s look at low code through an analogy.

Imagine traditional coding like walking. Sure, you get where you’re going, but it’s going to take a while.

Low code development is more like driving. If you have a vehicle (typically an LCDP — low-code development platform), and an experienced driver behind the wheel directing the vehicle, you’re going to get to your destination a hell of a lot quicker.

So, low code automates the tasks that developers would typically find complicated, time-consuming… or straight-up irritating. A developer narrows the scope of their work and can focus on higher-value logic-based issues, as opposed to technical ones.

What are the benefits of low code?

• Faster development and greater technical agility to adapt to market needs
• Reduced human error
• Decreased costs

Developers access these benefits through low code development platforms, but no two low code tools are ever really alike. Typically they have some sort of visual aid, a development environment and automatically handle backend services.

Some low code development platforms are available to the public, such as Salesforce Lightning, or KiSSFLOW, while others are used for in house development.

elfware Automation uses a custom low code platform called elfCafé, developed in house. Our engineers are constantly adapting the platform to meet the services our customers require, typically relating to Retail ERP, data integration/validation, automated testing and more.

What does low code mean for the future of IT?

Short answer; we don’t know.

In some scenarios, like at elfware, low code has meant clients can get substantial results without large investments of time and money. With a specific retail focus, we’ve been able to validate typically years’ worth of data in months and run millions of scenarios in hours. Just take the example of a US Specialty Retailer whose data we managed to prototype into Oracle Retail v16 from Oracle Retail v11 in just 2 weeks. But, some industries haven’t been able to capitalise on its benefits as of yet.

Many companies are still using Agile and DevOps to fuel faster development, with varying degrees of success. But more and more are pushing toward integrating low code development into their technical model, including Shell Downstream, Harvard, MIT, ING Bank, PricewaterhouseCoopers, Yahoo and more.

This rapidly growing demand has led to Forrester Research estimating a 40% compounding annual market growth for low code development platforms, leading to a market value of $21.2 Billion by 2022.

Will it put engineers out of work? Probably not. If anything, low code is an aid that will make engineers more productive and more agile, making them capable of producing more output at greater efficiency.

elfware Automation is an IT Company specializing in retail automation solutions. We have headquarters in Sydney and London, with clients from across the globe. If you’d like to learn more, visit www.elfware.com or contact us.

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References:

* - https://www.bmc.com/blogs/low-code-vs-no-code/

This article contains an explanation from elfware CEO Hamish Cameron of various Oracle Retail cutover strategies, previously an answer to a question in a Q&A. In particular, it focuses on the different features of a phased cutover versus a ‘Big Bang’ cutover, as well as offering methods to reduce project costs and ensure cutover success.

Hamish is concerned with understanding and communicating the transition risk landscape and agreeing a combination of cutover approach and mitigation activities which appropriately balance risk and cost for an organisation.

Q: "We are implementing Oracle Retail, replacing an in-house legacy application suite in which retail applications such as Merchandising, Inventory Management, Pricing, Allocations, Assortment planning etc are tightly coupled to core Master Data tables.

We are steering away from big bang, but can you advise on what approaches we could take?"

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Response

“The biggest two questions to consider when cutting over are: how agile is your current legacy and integration landscape and how big is the appetite for mitigation?

Typically I believe phasing a cutover actually adds more risk, as it requires significantly extra work and the costs escalate and/or the quality processes going in to each state then reduce.

Phasing an implementation reduces cutover risk but has other big impacts I'll refer to later.

In particular doing anything apart from Big Bang requires a significant amount of:

1. Transition planning - define the states, what is performed where in each and how will you transition from one to the next
2. Change and Training - you will need to prepare change activities for each state including preparing and executing training. This is not just for users but also application support and integration teams.
3. Testing - end to end testing is required for processes and integration in each state, including reporting visibility. That means UAT (User Acceptance Testing) as well as technical and integration testing 
4. Development - Mostly this should be legacy and integration plus interim reporting, but you'll typically be surprised by how many downstream systems are impacted that hadn't been considered. It really depends upon your organisation's ability and appetite for decoupling existing capabilities into multiple transition states.
5. Support - I've been going in reverse order, but after each state transition it is key to stabilise support for the state, and validations, reconciliations and operational reporting may well change between each state.  Data integrity issues may well also cause delays to the next transition.

So you need time, capability, organisational commitment, Oracle Retail and Legacy architectural expertise and budget to make it feasible to mitigate by phasing your implementation or your cutover.

Alternative 1: Phasing your Implementation 

If you have plenty of time then you can plan upfront and execute each state as a sequentially separate project over a timeframe - it becomes a significant Programme Executive undertaking to persuade business stakeholders why a long running project with a large price tag is unlikely to deliver benefits in a typical retail timespan.

Alternative 2: Phasing your Cutover

If you don't have plenty of time, then you will need to execute in parallel ... and that's where the fun really begins with people designing, building and testing for multiple states in parallel across multiple environments in order to be ready to execute the cutover sequentially.

With that said I've been involved with different approaches over the years, for example:

1. Decouple by System

This is the most advisable approach where possible.  It really comes down to ensuring all processes in each system are covered in the relevant transition state and that interface commissioning/decommissioning is well planned and executed.

2. Decouple by Division/Merchandise Group

Works where the divisions have largely separate legacy systems with low levels of overlap, so probably not feasible for you.  If you try this by splitting out from a single integrated application I suspect you will open a ‘Pandora’s box ’of modifications and testing.  Normally the issues will come in POS, sales transaction auditing and reporting, but depending upon your current legacy systems, it may also impact purchasing, invoice matching (and/or accounts payable), inventory, transfers/allocations, pricing/promotions, e-commerce, planning and finance ... you name it.

3. Decouple by Location e.g. Brand/Country

This really has similar characteristics to decoupling by Division/Merchandise Group, however usually purchasing, invoice matching, transfers and allocations are your key pain points.

4. Decouple by process area/functionality

e.g. Item and Master Data followed by pricing/promotions, purchasing etc in some order and then the transactional layer.  

This is the most common approach taken.  It absolutely works but I'd refer you back to points 1. to 5. above - it is very expensive and has fundamentally undermined projects at a number of retailers causing the implementations to be paused and not achieving objectives.

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Other mitigation approaches we have taken:

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5. Simulate transition to production and production runs a multitude of times

Automating all aspects of integration testing, validation, reconciliation and transition allows it to be tested within an inch of its life through transition and a month plus of realistic data a multitude of times.

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6. Parallel Run

Execute an automated parallel run where data is fed into RMS (Retail Merchandising System) via a combination of data migration scripts and the integration layer from legacy with isolated processes double keyed or enriched in the RMS (Retail Merchandising System).

This can be significant effort and can be fraught with complexities in the mappings and integrity between legacy and RMS, typically resulting in quarantining which requires legacy, mapping or RMS correction to release.  That can be an overhead and result in reconciliation difficulties due to timing etc.  So as the parallel run continues more data will typically get out of whack.

Conclusion

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The most appropriate implementation mitigation approach depends upon a number of factors, not all of which are covered in this brief overview.

Absent very good reasons for doing otherwise (such as disparate application and integration landscapes) generally I would recommend approach 5. Simulate transition to production and production runs a multitude of times as the automation tools are readily available to implement this strategy.

To offer a greater level of risk mitigation this can be done in combination with 6. Parallel Run, but it does require a greater appetite for such mitigation as it will take both additional time and budget.

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---

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Hopefully Hamish's discussion helps you to understand a little more about the transition options for an Oracle Retail Implementation. If you have further questions, feel free to contact him on LinkedIn or send him an email.

Oracle Retail Implementation and automation related IT services are elfware’s forte. Using our implementation experience in combination with the elfCafè platform and approaches, our team will optimise your implementation, application management and resolutions for your most complicated bottlenecks, as we have for similar organisations from all over the globe.

Click here to visit our main site, or here to contact us and discuss how we can assist with your Oracle Retail journey.

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Oracle Retail is widely regarded as the best ERP suite for the retail sector, but why is that and what solutions do they offer? You'll find Oracle consistently ranked very highly across their retail offerings, and the best in a number.

“Oracle has been recognised as a Leader in the Gartner Magic Quadrant for Digital Commerce for the 10th consecutive time”.

And there is good reasoning as to why.

At elfware we specialise in Oracle Retail, and particularly in resolving related implementation, delivery and maintenance challenges through low code and automation. Having had such exposure to Oracle Retail, we thought it would be helpful to put together a basic summary of what Oracle Retail is.

Contents:

1. Overview - What is Oracle Retail?
2. Benefits
3. Challenges
4. Case Study: KOJ
5. Oracle Retail's Product Suite

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Overview — What is Oracle Retail?

As the largest business software vendor globally, Oracle offers a huge library of products, including database services, platforms, software, hardware and more.

Oracle Retail is a division of Oracle focused on providing specialised retail application capabilities.  You may have also heard the arm referred to as the RGBU - or Retail Global Business Unit. At the time of writing Oracle Retail claim over 5,000 retail clients.

One of the major reasons that people get confused as to what exactly Oracle Retail does is because of the sheer number of offerings that come under its umbrella. These products are split up into a series of categories, each fulfilling a different purpose - merchandising, insights and science, omni-channel, planning and optimisation, supply chain and hardware.

They boast software application modules to support pretty much any process that retail organisations require to run their company effectively. Predominantly, the software is used to enhance the company’s capacity to manage stock, reduce waste, improve customer experience and, importantly; to increase revenue and profit.

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Benefits

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Product Variety

As has just been discussed, the fact that Oracle Retail has such a large offering of fully integrated products is a big drawcard.

They cover just about everything retail-related there, and they have a whole suite of integrated products that more generally cater to enterprise wide process support. This links into the next benefit…

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Retail Solutions Integration

Retailers don’t have to worry about cross-party integration, given that one suite of products can cater to just about every aspect of the business.

All aspects of the business’ retail function are therefore inextricably linked, allowing for a more agile and streamlined operation. This can lead to reduced costs and, more importantly…

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Higher Quality Customer Experience

Oracle Retail has focused heavily on improving the capacity for retailers to cater to an omnichannel, connected, and highly personalised customer experience. They use data and automation to ensure that customers feel valued by the business and have an experience that fits their archetype, resulting in incremental revenue and profit increases.

An Oracle employee explains that they’ve, “seen more than a $75 million increase in revenue at a medium-sized retailer turning over between 500 million and a billion dollars, just by optimising targeted offers at the point of pickup,” merely one aspect of the targeted customer experience.

According to a recent article by SuperOffice (https://www.superoffice.com/blog/customer-experience-statistics/), 86% of customers will pay more for a better experience, and keeping an existing customer happy is 14 times more profitable than landing a new customer.

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Data-Driven Approach

A lot of the benefits of Oracle Retail spur from its data-driven approach. Recommendations from the Oracle Retail software are based off millions of data points used to gradually optimise and improve a business’ operations.

“Retailers all know they need advanced analytics and retail science to drive their business forward, but they don’t all have the luxury of hiring on a data science team,” said Marc Koehler, solution director, Oracle Retail, “We continue to enhance Oracle Retail Insights and Science Suite to provide retailers with packaged insights and science applications”.

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AI and Machine Learning Integration

Oracle has made it very clear in recent years that they want to lead the innovation front, and have done so with regard to AI and Machine Learning in retail solutions. Their AI solutions can be used in conjunction with Oracle Retail to improve processes.

However, Oracle emphasises AI and Machine Learning are not a completely effective solution alone, and require concerted focus and cultural change; “most machine learning projects fall short on delivering tangible business benefits. Not because the innovation is misaligned with a business objective but because it is difficult to operationalise innovation,” said Jeff Warren, vice president, Oracle Retail,“the Retail Science Platform delivers the standardisation and controls that enterprises need to accelerate their new offerings and swiftly integrate them into their business workflows. With the addition of notebook-based tools, our solution is a force to be reckoned with in predictive analytics and machine learning for the retail industry.”

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Challenges

So we’ve established that there are numerous benefits to Oracle Retail, but it’s important to be pragmatic about potential challenges as well, challenges it shares with other organisations.  Here are some comments which have been made:

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It’s Expensive

Now, this point is very dependent on how you’re using Oracle Retail.

Oracle Retail can be expensive, particularly for small to medium retailers. But, many large enterprises see extensive revenue and profitability benefits that by far outweigh the cost of Oracle Retail. It's also important to consider that this isn't an Oracle Retail specific issue; rather one that applies to all Enterprise Resource Planning products.

Whilst licensing and support costs must be considered as an input cost, the primary impacts to the Total Cost of Ownership (TCO) are from the initial implementation - see this discussed below - and from the on-going run costs from teams who lack experience in managing high performance Oracle retail sites. At elfware we specialise in delivering and maintaining high performance Oracle Retail installations.  We reduce Total Cost of Ownership through automation, making Oracle Retail a value buy for all retailers, irrespective of size.

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Complexity in the Ongoing Use

Oracle Retail is far from simple and requires extensive technical expertise to use. This can result in extra costs or a lack of valuable input from Oracle Retail products.

Typically, retailers will look to bring on full-time Oracle Retail administrators, and external technical teams for more complex projects.

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Difficulty in Moving from Legacy Systems to Oracle

Moving between systems entails any number of issues.

A retailer may need to go through extensive retraining of staff that will result in short term productivity shortfalls, but typically the cost comes in the movement of data from legacy systems to Oracle Retail.

At elfware, a project we’re currently working on with a large UK Based retailer moving to Oracle Retail, involves integrating and validating existing, unstructured data into Oracle Retail to ensure the long term success of their new system.

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Case Study: KOJ

I don’t want to go extensively into Oracle Retail case studies.

But, we’re an IT Automation company that specialises in Oracle Retail services and resolving the issues involved, so we just want you to understand how retailers have got around some of Oracle Retail’s challenges and what happened to the business as a result.

KOJ is certainly a success story for Oracle Retail.

A Dubai based retail conglomerate, KOJ operates more than 700 stores between 7 countries.

Oracle listed a few statistics in a success story profile of the company, citing that KOJ had seen 99.9% accuracy in real-time inventory data for stock online, and 98.5% for in-store.

Statistics like these have prompted numerous global retailers to utilise the Oracle Retail product suite, including Louis Vuitton, Walmart, Prada, Cape Union Mart and Myer.

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Oracle Retail’s Product Suite

Note that we have split up the product offerings into the categories listed by Oracle Retail. At the time of writing, each of the below categories have multiple product offerings under their umbrella.

Insights and Science

Oracle Retail emphasises that in modern retail, great products aren't enough. Rather, retailers need to anticipate and adapt based on advanced analytics to optimise and personalise their offers.

Thus, Oracle's insights and science product suite focuses on using analytics to drive customer engagement and loyalty.

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Merchandising

Arguably Oracle Retail's most significant offering is there Retail Merchandising System. Merchandising solutions like Oracle's provide an organisation with the means to accurately monitor, and thus control, the success of their retail business.

The system has the capacity to reduce the cost and time required for day-to-day activities - from the maintenance of stock ledgers, to new product introductions, to automated replenishment and much more.

Oracle Retail emphasises that the benefits of their merchandising system are; operational support, scalability, agility over numerous verticals, and data integrity.

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Omnichannel

Omnichannel services focus on orchestrating activities across a retailer to improve customer experience. It provides a customer with a unified experience across numerous channels and touch points.

Oracle Retail emphasises that data-led decision making using their platform can drive conversions and foster brand loyalty. The integration of their various products provides a retailer with the capacity to personalize the shopping experience.

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Planning and Optimisation Process

Oracle's Retail platform combines advanced retail analytics, artificial intelligence and machine learning to plan, and gradually optimise a retailer's operations. This includes use of space, category optimisation, financial planning, pricing and more. Gradually, a retailer can optimise to increase revenue and reduce waste.

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Supply Chain

Oracle's modern system for Supply Chain Management is designed to reduce inventory requirements and waste while meeting supply requirements to maintain or improve revenue. Again they utilise embedded AI to assist in decision making and claim the capability to reduce inventory requirements by 30%.

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Hardware

In 2014, Oracle acquired MICROS systems and inherited their hardware products, an important factor in their omni-channel approach.

Their point of sale systems allow Oracle Retail to cover the complete customer experience. Oracle focuses on simplicity, flexibility and durability in their systems, that integrate with their other services to offer an end-to-end optimised customer experience.

In the context of software engineering, Code Printing refers to:

The transformation of requirements into code by an algorithm

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Code Printing is a broad term to cover a range of offerings, examples include:

• No Code approaches such as mail merge and simple code patterns

• Low Code approaches which provide more complex patterns which can be extended through exits

• Enterprise Low Code approaches which enable enterprises to deliver their in-house code patterns using a Low Code approach

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This is a different paradigm to traditional programming, which is based on:

The transformation of requirements into code by a person

‍

You see, traditional software engineering is focused on micro-delivery, so essentially:

Hand crafted delivery of individual code artefacts

You can think of it as:

A sequential process of delivering one program or change after another

And similar to  hand crafted techniques in furniture making, tool making or manufacturing, each artefact has it's own idiosyncrasies associated with the craftsperson and that particular construction effort.

‍

Related Articles

• Enterprise Low Code vs Traditional Software Delivery

• Why has In-house Low Code now become feasible for an enterprise?

• How much complexity can Enterprise Low Code support?

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How does Code Printing work?

Code Printing is analogous to the capability a 3-D printer provides in the physical realm.

A 3-D printer can deliver any structure you need based on design meta-data, each instance of which may be configured slightly differently from the last. So there is a focus on the meta-data and it's transformation directly into a predictable target structure.

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Code Printing does this for code artefacts, but because there are no physical constraints on the artefacts printed, the complexity is limited only by:

• The fidelity of the design template
• Support in the code pattern

And of course, a code artefact can evolve rapidly – without wasting any physical material.

The key difference with a hand crafted approach is that the construction process is both very rapid and completely deterministic - every artefact will be delivered 100% consistently against its design, without idiosyncrasies or alternate implementations.

So like 3-D printing and CAD-CAM manufacturing it is particularly suited as an approach to large scale production against high precision requirements.

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"Why would anyone implement Code Printing?"

I hear you, why put additional effort into writing an algorithm to print code rather than just writing the code yourself?

I'm sure you would be familiar with Low Code and No Code (Codeless) platforms. Code Printing is exactly what they do!

These platforms have large user bases, so their transformation algorithms are used a lot! That's how they can deliver like magic - and how they can keep improving your work without you having to make any changes.

So why do they refer to No Code if they are printing code? Because their code patterns are proprietary - the code they print only works within their platforms, so you don't need to see it.

And of course if you ever want to change your platform you can't take that code with you, you will have to start again

So you are left with No Code.

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Low Code / No Code as an Enterprise delivery option

Enterprises have many examples of their own internal code patterns. For example, an initial interface, pipeline, microservice or report may lead to 20 or 50 variations based on a similar theme.

And for any enterprise, software delivery is all about speed, consistency and scale.

So when a modern enterprise has a family of modules with similar requirements they try to focus on macro-delivery:

Rapid, consistent delivery of easily maintained code which can readily evolve.

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Pattern based delivery is a key macro-delivery enabling strategy implemented by enterprises.

But it's something the best software engineers are not typically good at - talented engineers want to keep improving solutions or solving new problems, not continually solving the same problem the same way!

And between two code artefacts any engineer will evolve their approach slightly, as they learn, familiarise with the pattern and innovate. When you engage multiple engineers for large scale delivery, especially over a period of time, each with their own experience and preferences, consistency goes out the window - even with the best QA efforts.

Without consistency, an organisation's ability to evolve and improve a code pattern becomes that much harder and more expensive - leading to technical debt which impedes both delivery and innovation.

So enterprises should love Low Code platforms right?

It turns out ... not so much.

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Why not?

Enterprises tend to prefer sovereignty over their code base, because they need to be flexible with their IT partners and be able to differentiate from competitors. Also, with any Low Code and No Code solution there will be constraints in the design meta-data model and code pattern capabilities, so enterprises need to use Low Code platforms in which they can customise the outcomes.

Of course customisation becomes an additional software engineering effort, especially for complex requirements, which further erodes the attraction of commercial platforms.

But should that make code printing inaccessible to an enterprise - the very organisations for whom it can have the greatest impact? Of course not!

‍

Code Printing and Enterprise Low Code

Code Printing for an enterprise is known as Enterprise Low Code and focuses directly on the macro-delivery requirement.

By its nature it is an evolutionary, innovation-oriented approach to optimise not just for:

• Delivery speed for individual code artefacts

But also for:

• Innovation and evolution of the code pattern

Whilst

• Minimising the resource effort and maintenance costs

Code printing is unique in enabling this as it:

• Delivers any new code artefact module lightning fast
• Only needs a technical analyst for any code artefact, not a chain of team members supporting a complex SDLC
• Each iteration of the code pattern can immediately be applied to the whole class of artefacts - eliminating technical debt

And unlike traditional Low Code and No Code platforms:

• Code patterns are owned by the enterprise and can be tailored to their requirements
• Any code delivered is also owned by the enterprise, so there is no constraint to work with a platform or partner

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How do we get started with Enterprise Low Code for in-house patterns?

‍elfware is an IT automation company specialising in using Code Printing to accelerate delivery for enterprise clients in their own code patterns.

We leverage mojoh.io to rapidly print code artefacts consistent with client specific code patterns - a truly Enterprise Low Code platform.

We have headquarters in Sydney and clients across the globe.

If you’d like to learn more, visit www.elfware.com or contact us for:

• ‍Technical platform replacement
• Project rescue
• IT delivery acceleration

‍

Traditional Software Delivery

In an enterprise software delivery is traditionally undertaken by a software engineer / programmer / developer who will hand craft each program based upon:

• A design specification from an analyst

• Discussions with the designer

• Their own experience of the language or platform

• Their own understanding of the enterprise

• Interpretation and application of a code pattern and enterprise standards

And may iterate the output a number of times based on:

• Evolving requirements

• Quality issues identified through a technical QA process

• Defects or gaps identified by a test team or users

Once the engineer is finished an artefact they may start another of the same family, or potentially of a different family altogether.

Each time the engineer undertakes delivery of a new artefact they will improve their delivery a little from familiarity and from learning.

Inconsistencies within a code family arise because:

• Improvements by a software engineer typically won’t be retrofitted to previous examples of a pattern

• If two software engineers deliver different instances from the same family there will be limited fidelity between them.

So consistency is limited by the nature of this delivery approach and the engineers who specialise in it.

Enterprises will implement code patterns QA processes to various degrees to mitigate these risks, however pattern evolution and innovation is impeded because the expense of retrofitting innovation typically cannot be justified through either cost or priority.

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How does Enterprise Low Code differ?

Taking a Code Printing  approach with Enterprise Low Code means focussing on any code artefact as being a representative of a family.

The family is represented by a rigorous code pattern and a formalised design specification template.  For any member of the family the two are combined via a transformation algorithm to deliver a code artefact with 100% predictability and fidelity.

That means analysts can fill out the design template as a predictable process with only the information required specifically for the task. They can also be assisted by information merged in from other sources such as data structure definitions and API or micros service contracts rather than spending time on wordy descriptions of the requirements which may be misinterpreted.

Once a module is specified the analyst can immediately print and test the code artefact(s) arising from it without the handover and delivery delays associated with hand crafted delivery by a software engineer.

This approach encourages the best software engineers to place their whole focus on evolving and improving code patterns i.e. on hardening and innovating the code structure because:

• Software engineers have the bandwidth because are no longer involved in delivery of individual code artefacts

• Each improvement they make to a code pattern can be automatically applied to the whole family

And the delivery approach changes from:

• A few analysts bottle necked as they document, evolve and explain requirements to

• a number of software engineers who slowly iterate through the SDLC process and associated meetings and reviews

• with each set of requirements repetitively delivering different code that broadly addresses the same problem

• When a pattern change evolves for a module it results in inconsistencies and technical debt

Instead:

• Each analyst can rapidly specify, deliver and iterate their own code based on a best practice pattern

• There is no need for extended delivery timeframes and the possibility for different interpretations between analyst, engineer and test analyst

• Patterns are expected to evolve and improve so they can improve the whole family of code

This approach allows an IT organisation to always be working on what is important, on delivery and innovation, without constraint from a legacy code base.

It also facilitates speed, agility and flexibility in the enterprise.

See also: Why is In-House Low Code now feasible for an Enterprise?

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Transitioning Enterprise Delivery to Low Code

Follow these steps to transition pattern based delivery for an existing code pattern to Enterprise Low Code:

Step 1. Identify key delivery patterns, prioritised by total delivery effort (i.e. # modules* delivery effort per module)

Step 2. From sample specs and code define a Design Configuration Template and a Code Printing transformation Algorithm

Step 3. Specify structured configs for target modules using the Design Configuration Template, replacing place of unstructured design specs, and generate the code

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Step 4. Identify test automation patterns and transition those also to printed code

‍

How do we get started with Enterprise Low Code for in-house patterns?

‍elfware is an IT automation company specialising in using Code Printing to accelerate delivery for enterprise clients in their own code patterns.

We leverage mojoh.io to rapidly print code artefacts consistent with client specific code patterns - a truly Enterprise Low Code platform.

We have headquarters in Sydney and clients across the globe.

If you’d like to learn more, visit www.elfware.com or contact us for:

• ‍Technical platform replacement
• Project rescue
• IT delivery acceleration

As previously described in What is Code Printing?, Low Code is a form of Code Printing which should be attractive to an enterprise, but has only been partially adopted because:

• Enterprises tend to prefer sovereignty over their code base
• Enterprises need to customise their code outcomes, which erodes the attraction of commercial platforms.
• If they decide to leave a platform, they leave with No Code

But since enterprises will benefit the most from Low Code solutions, there must be a way to solve these constraints.

You'll be happy to know, there is!!

So what is it and how has become feasible?

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The past ...

For some years elf has been providing code printed services for data migration, data maintenance and parallel runs for large and medium sized transformation programmes across the globe - from mid-market programmes taking less than a year up to Tier 1 programmes running for 3-4 years.

These services rely upon proprietary patterns and templates which work together to provide rapid, rich, cohesive and auditable data related outcomes.

Implementing these was justifiable due to:

• The volume of modules required for any single programme
• The savings in resources, time and effort for each programme
• The reusability of patterns across programmes for many clients and
• The substantial benefits that early population of target applications with real data can provide in:
  • Shifting left in validating solution decisions - at the earliest and cheapest possible time
  • Identifying process edge cases that would otherwise be missed
  • Providing early visibility and trajectory for legacy data quality

The templates and patterns have provided enormous value to our customer base during large, high pressure transformation programmes.

We refer to this platform as our Prototype Code Printing platform, because whilst it was fully functional for the patterns we implemented, it was not readily extensible to patterns unique to a customer beyond these Data Stream requirements, or for more patterns involving recursively complex sub-patterns.

We saw the enormous value of expanding Code Printing support beyond these proprietary patterns, but to make it feasible the effort relating to implementing new patterns and their design templates needed to be substantially reduced.

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The present ...

So we undertook the task of building an enterprise information modelling and transformation platform which is:

• ‍Extensible
  ‍Readily models any type of information and complexity, supporting the modelling for any design configuration which may be required for printing pattern based code.
  This also means it can readily ingest and use information from existing enterprise knowledge sources, such as data structures, API and micro-service contracts, code etc.
  ‍
• ‍Self Constructing
  Prints API and UI/UX based on it's own information model configuration which also enables configurable interaction with the models - to suit the design template process requirements for any code pattern.
  So there is very limited effort required to configure individual pattern related design processes.
  ‍
• ‍Polymorphic
  ‍Any information model can be treated as or transformed into any other
  That means a series of high level requirements can readily morph into a design configuration for pattern A, or a series of design configurations for pattern B ... and then some may be changed to pattern C, which may be an extension of pattern B.

Optimised for Code Printing

From the ground up every mote, which is the basic unit of knowledge in the platform, can be leveraged by transformation algorithms to:

• Initialise design configuration templates
• Become attributes of design configurations
• Be transformed into pattern based code artefacts
• .... readily support any level of complexity!

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elf have begun to use it for client project acceleration with great success.  For example our code printing team have recently:

1. Delivered pattern changes to 100+ APIs in a day
   ‍
2. Transformed 300+ GoCD Bitbucket CI/CD pipelines to Azure DevOps in 2 weeks

Each example cuts code delivery times for the projects by at least an order of magnitude.

The rapid delivery timeframes have allowed time for evolution of the patterns, and where pattern changes have been required they are delivered 100% consistently within hours across all hundreds of code artefacts.

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The future ... mojoh.io

We see a future in which small IT organisations and small teams deliver change, value and enterprise agility beyond anything that is possible today with large teams.

The future of enterprise delivery is Code Printing and the platform that enables it is mojoh.io - please follow the link to join the community of early adopters or visit www.elfware.com or contact us to help turn around your IT project delivery today.

‍

How do we get started with Enterprise Low Code for in-house patterns?

‍elfware is an IT automation company specialising in using Code Printing to accelerate delivery for enterprise clients in their own code patterns.

We leverage mojoh.io to rapidly print code artefacts consistent with client specific code patterns - a truly Enterprise Low Code platform.

We have headquarters in Sydney and clients across the globe.

If you’d like to learn more, visit www.elfware.com or contact us for:

• ‍Technical platform replacement
• Project rescue
• IT delivery acceleration

‍

Design Configuration Template Examples from mojoh.io

Below are a sample design configuration template and a library of designs from the mojoh.io platform which enables Code Printing for enterprises for their in-house patterns:

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By their nature:

Low Code and No Code solutions minimise the number of decisions a user needs to make in order to simplify the design process, but maximise the leverage of those decisions to speed up the outcome.

They do this by making assumptions to transform the smaller number of decisions into their proprietary pattern based code.

But every enterprise has unique requirements, which cannot all be met by a standard commercial platforms with proprietary patterns optimised for a mass customer base.

So major considerations for enterprises when considering Low Code and No Code options are:

• The level of complexity they can support out of the box, and
• how much customisation and extension effort will be required to meet enterprise objectives

Generalised Code Printing complexity, however, is only limited by the complexity that its information model can readily support.

Simple Information Models

Where design templates are implemented in a simple text file, or a database or spreadsheet table, their complexity is heavily constrained. They may be associated with a simple form to assist a person to use them correctly.

A target pattern based on these structures will necessarily be simple and limited support can be provided to prefill parts of the structures from existing enterprise knowledge assets such as:

• Enterprise Data Structures

• API contracts

• Enterprise rules etc.

A mail merge is a good example of a simple information model and pattern.

The information model is just a list of names and address related fields and these are processed into a target pattern that takes the form of a letter or email.

‍

Multi-Dimensional Information Models

Implementing information models in spreadsheets is flexible and allows for much greater levels of complexity as a spreadsheet provides natural support for mappings between data sources, API contracts etc.

Additionally, with multiple sheets per spreadsheet and the ability to refer between spreadsheets it can support:

• Reasonably complex modules with different pattern components

• Chains of modules representing more than one pattern

Additionally mapping designs can be automatically initiated and prefilled to speed up the decision-making process for an analyst.  That is:

Existing enterprise knowledge assets can be selected by an analyst to rapidly flesh out designs and provide greater accuracy

As flexible as a spreadsheet is, that very flexibility can create limitations in its usability:

• It is difficult to make a spreadsheet template easy to understand so on-boarding is more complex

• Changes in design decisions are difficult to track

• Changes to templates can’t readily be retrofitted to existing designs

• It is not straightforward to add access to external knowledge assets

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Complex Information Models

A markup document such as XML, JSON or YAML can provide the virtually infinite complexity required by an Enterprise.

However:

• They are not very analyst friendly

• It is difficult to merge in enterprise knowledge

• It is difficult to reuse these component designs for multiple purposes

What can resolve these challenges is to implement UI/UX guide user input in the design process and provide access to enterprise knowledge. However:

• The effort to design, deliver, train and maintain and application can be significant

• It is still difficult to reuse these component designs for multiple purposes

Delivering an application to guide the design process is the most fit for purpose approach, as virtually any level of complexity can be supported in the application data structures and the optimal process can be implemented in UI/UX for any given pattern.

However, the very effort to build and maintain these applications has historically been a major barrier to adopting an internal Low Code approach.

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The reality for Enterprise Low Code

The challenges in designing, delivering, training and maintaining low code in the enterprise make it almost inaccessible as an option.

Enterprises may implement point solutions for high value and volume patterns, often without UI/UX support which leaves a high on-boarding effort for new resources and undermines the sustainability of solutions.

Instead enterprises typically opt for a combination of commercial Low Code platform offerings combined with Pro Code extensions which provide some benefits, but don't enable a change in the way they deliver.

More often, they stay with the traditional hand crafted Pro Code approach, with all its shortcomings.

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The future of Enterprise Low Code

Enterprise Low Code is the future of enterprise delivery for the reasons we discussed in What is Code Printing?

And the future of Enterprise Low Code has to be enabling platforms which:

• Simplify implementation of complex information models to support Low Code patterns

• Enable UI/UX configuration to optimise design processes for code pattern delivery

• Enable access to enterprise knowledge through API's or as an enterprise knowledge platform themselves

• Deliver code in enterprise specific patterns, acting as an in-house Enterprise Low Code platform

That future is here as we discuss in Why has In-house Low Code now become feasible for an enterprise?

That future is mojoh.io, which had been built from the ground up to be an Enterprise Knowledge Base and In House Low Code platform.

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How do we get started with Enterprise Low Code for in-house patterns?

‍elfware is an IT automation company specialising in using Code Printing to accelerate delivery for enterprise clients in their own code patterns.

We leverage mojoh.io to rapidly print code artefacts consistent with client specific code patterns - a truly Enterprise Low Code platform.

We have headquarters in Sydney and clients across the globe.

If you’d like to learn more, visit www.elfware.com or contact us for:

• ‍Technical platform replacement
• Project rescue
• IT delivery acceleration

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